source: Public author profile is associated with University of Bari Aldo Moro. Recent work in quantitative social science and economics includes 'Violence Against Women: a pilot study on the perception of Apulian High school students'. Violence Against Women (VAW) is a widespread issue deeply rooted in social and cultural structures... OpenAlex concept tags include "biology, statistics, geography, ecology '.

c00: YC batch S2023 founder at Parea. Role: Founder. Published first paper in the highest-ranked number theory journal at age 17. M.Sc. from NYU as a Fulbright scholar. Researched applications of deep learning to medical imaging at Covera Health. Built semantic search systems and automatic code generation software at Jina AI.

c01: Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "computer science, artificial intelligence, computer vision, computer graphics (images) '.

c02:
[person] (@[person]). base in Bristol, UK; works with University of Bristol.

Climate, glaciers, and programming.

Representative projects and topics: Open Global Glacier Model; Add geolocalised subsetting, masking, and plotting operations to xarray; N-D labeled arrays and datasets in Python; Lectures notes of the scientific programming course at the University of Innsbruck; Educational material about glaciers, powered by OGGM and MyBinder; Class activities and notebooks for the MSc "Quantifying Climate Risks" class taught at Uni Bristol.

c03: Recent work in ai and machine learning includes 'Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought?'. Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems... OpenAlex concept tags include "situation awareness, software deployment, risk analysis (engineering), psychology '.

c05:
[person] (@[person]). base in San Francisco; works with @langchain-ai.

Building agent frameworks @langchain-ai. Head of the @webdriverio project. Open source & open standards advocate.

Representative projects and topics: Next-gen browser and mobile automation test framework for Node.js; A curated list of delightful Selenium resources.; Boilerplate project to run WebdriverIO tests with Cucumber; a lightweight rgb/rgba to hex parser; A Node.js based package and CLI library for launching Selenium with WebDrivers support (Chrome, Firefox, IE, Edge); Boilerplate project to run WebdriverIO tests with Appium to test native applications on iOS and Android.

Open Source & Open Standards Advocate.

🔭 I’m currently working at **LangChain** building Agent Frameworks

🤝 I’m automating things with **WebdriverIO

📝 I regulary write articles in **my blog

🧠 I'm learning Video Editing with Final Cut Pro

💬 Ask me about **WebdriverIO / Test Automation / VSCode Extension Development / Node.js / TypeScript

⚡ Fun fact **I grew up on the country side in Germany next to 🐮 and 🐔

Skills

c06: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "materials science, computer science, engineering, medicine '.

c07: Recent work in ai and machine learning includes 'Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought?'. Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems... OpenAlex concept tags include "reinforcement learning, computer science, artificial intelligence, machine learning '.

c08:
[person] (@[person]). base in Mountain View, California; works with Google.

Engineering Lead at Google working on Chrome & Web Platform

Representative projects and topics: ⚡Faster subsequent page-loads by prefetching in-viewport links during idle time; 📦 Workbox: JavaScript libraries for Progressive Web Apps; Extract & Inline Critical-path CSS in HTML pages; Material Design Components in HTML/CSS/JS; Helping you select a JavaScript framework - Todo apps for React.js, Angular, Vue and many more; Yeoman - a set of tools for automating development workflow.

🔭 I’m currently working on AI at Google (Gemini, Agents, Vertex)
👯 I’m looking to collaborate on Developer Tooling
🤔 I’m looking for help with Framework collaborations
💬 Ask me about anything

c09:
[person] (@[person]). base in Singapore; works with VoidZero.

Founder @voidzero-dev, author of @vuejs and @vitejs. Connoisseur of sushi.

Representative projects and topics: 🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.; Next generation frontend tooling. It's fast!; Vite & Vue powered static site generator.; Fast Rust bundler for JavaScript/TypeScript with Rollup-compatible API.; This is the repo for Vue 2. For Vue 3, go to; 6kb subset of Vue optimized for progressive enhancement.

c10: Recent work in computational biology includes 'Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction'. We investigate the parameter space of transformer models trained on protein sequence data using a statistical mechanics framework, sampling the loss landscape at varying temperatures by Langevin dynamics to characterize the low-loss manifold and understand the mechanisms underlying the superior performance of transformers in protein structure prediction... OpenAlex concept tags include "computational biology, computer science, biology '.

c11: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "computer science, artificial intelligence, machine learning, task (project management) '.

c12:
[person] (@[person]). base in Half Moon Bay, California; works with Datasette.

Representative projects and topics: An open source multi-tool for exploring and publishing data; Python CLI utility and library for manipulating SQLite databases; Access large language models from the command-line; A command-line utility for taking automated screenshots of websites; Concatenate a directory full of files into a single prompt for use with LLMs; A tool for creating credentials for accessing S3 buckets.

c13:
[person] (@[person]). base in Austria; works with Earendil.

Software developer and Open Source nut. Creator of the Flask framework. Founder of @earendil-works. Other things of interest: @pallets and @getsentry

Representative projects and topics: The Python micro framework for building web applications.; MiniJinja is a powerful but minimal dependency template engine for Rust compatible with Jinja/Jinja2; A snapshot testing library for rust; A very fast and expressive template engine.; Python composable command line interface toolkit; These are commands I use with agents, mostly Claude.

c14:
[person] (@[person]). base in Santa Clara, CA; works with @BentoML.

CNCF Ambassador & KubeVela Maintainer (,,• ₃ •,,)

Representative projects and topics: A self-evolving personal AI assistant.; The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!; Declarative Workflow of KubeVela which can run as standalone.; A cloud-native Pipeline resource.; The Modern Application Platform.; Docker for Your ML/DL Models Based on OCI Artifacts.

[person]

I'm currently working on KubeVela & BentoML :sparkles:.

c15: Recent work in computational biology includes 'A Hierarchical Sheaf Spectral Embedding Framework for Single-Cell RNA-seq Analysis'. Single-cell RNA-seq data analysis typically requires representations that capture heterogeneous local structure across multiple scales while remaining stable and interpretable... OpenAlex concept tags include "betti number, physics, combinatorics, algorithm '.

c16:
[person] (@[person]). base in Catania, Sicily, Italy; works with Redis Labs.

Computer programmer based in Sicily, Italy. I mostly write OSS software. Born 1977. Not a puritan.

Representative projects and topics: A radix tree implementation in ANSI C; Dump1090 is a simple Mode S decoder for RTLSDR devices; A small self-contained alternative to readline and libedit; A text editor in less than 1000 LOC with syntax highlight and search.; Simple Dynamic Strings library for C; Disque is a distributed message broker.

c17:
[person] (@[person]). base in Amsterdam.

Software Engineer

Representative projects and topics: Template for DuckDB extensions to help you develop, test and deploy a custom extension; DuckDB is an in-process SQL OLAP Database Management System; duckdb-go provides a database/sql driver for the DuckDB database engine.; for testing purposes; intended for testing conflicting extension loads / functions; DuckLake is an integrated data lake and catalog format.

Charlotte (Lotte) Felius

Publications

G-ALP: Rethinking Light-weight Encodings for GPUs at DaMoN @ SIGMOD 2025
VCrypt: Leveraging Vectorized and Compressed Execution for Client-Side Encryption at EDBT 2025
Enhancing Security for Columnar Storage and Data Lakes at VLDB 2024
DuckDB-SGX2: The Good, The Bad and The Ugly within Confidential Analytical Query Processing at DaMoN @ SIGMOD 2024
Accelerating GPU Data Processing using FastLanes Compression at DaMoN @ SIGMOD 2024

Education
PhD Student at CWI in the Database Architectures Group working on secure query processing
MSc Computational Science (Joint Degree) at University of Amsterdam & Vrije Universiteit Amsterdam
BSc Systems Engineering, Policy Analysis & Management at Delft University of Technology

c18:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c19:
[person] (@[person]). base in SF & Utah; works with LangChain.

honey I think we left the k8s autoscaler on

Representative projects and topics: The agent engineering platform; Framework to build resilient language agents as graphs.; Deep Agents in JS; Declarative streams for Typescript; 🦤 My personal website; The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents.

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Public author profile is associated with Yeshiva University. Recent work in computational biology includes 'Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design'. Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale... OpenAlex concept tags include "medicine, computer science, physics, optics '.

c00: Recent work in ai and machine learning includes 'Do covariates explain why these groups differ? The choice of reference group can reverse conclusions in the Oaxaca-Blinder decomposition'. Scientists often want to explain why an outcome is different in two groups... OpenAlex concept tags include "computer science, mathematics, bayesian probability, statistics '.

c01: Recent work in ai and machine learning includes 'Do covariates explain why these groups differ? The choice of reference group can reverse conclusions in the Oaxaca-Blinder decomposition'. Scientists often want to explain why an outcome is different in two groups... OpenAlex concept tags include "psychology, public economics, outbreak, philosophy '.

c02:
[person] (@[person]). base in SF & Utah; works with LangChain.

honey I think we left the k8s autoscaler on

Representative projects and topics: The agent engineering platform; Framework to build resilient language agents as graphs.; Deep Agents in JS; Declarative streams for Typescript; 🦤 My personal website; The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents.

c03: Recent work in ai and machine learning includes 'Tracking Equivalent Mechanistic Interpretations Across Neural Networks'. Mechanistic interpretability (MI) is an emerging framework for interpreting neural networks... OpenAlex concept tags include "computer science, artificial intelligence, psychology, natural language processing '.

c04:
[person] (@[person]). base in San Francisco; works with @langchain-ai.

Building agent frameworks @langchain-ai. Head of the @webdriverio project. Open source & open standards advocate.

Representative projects and topics: Next-gen browser and mobile automation test framework for Node.js; A curated list of delightful Selenium resources.; Boilerplate project to run WebdriverIO tests with Cucumber; a lightweight rgb/rgba to hex parser; A Node.js based package and CLI library for launching Selenium with WebDrivers support (Chrome, Firefox, IE, Edge); Boilerplate project to run WebdriverIO tests with Appium to test native applications on iOS and Android.

Open Source & Open Standards Advocate.

🔭 I’m currently working at **LangChain** building Agent Frameworks

🤝 I’m automating things with **WebdriverIO

📝 I regulary write articles in **my blog

🧠 I'm learning Video Editing with Final Cut Pro

💬 Ask me about **WebdriverIO / Test Automation / VSCode Extension Development / Node.js / TypeScript

⚡ Fun fact **I grew up on the country side in Germany next to 🐮 and 🐔

Skills

c05: Recent work in computer vision includes 'Benchmarking PhD-Level Coding in 3D Geometric Computer Vision'. AI-assisted coding has rapidly reshaped software practice and research workflows, yet today's models still struggle to produce correct code for complex 3D geometric vision... OpenAlex concept tags include "computer science, artificial intelligence, computer vision, machine learning '.

c06: Recent work in ai and machine learning includes 'Think Anywhere in Code Generation'. Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer... OpenAlex concept tags include "artificial intelligence, generative model, algorithm, algebra over a field '.

c08: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "materials science, computer science, engineering, medicine '.

c09:
[person] (@[person]). base in Minneapolis; works with University of Washington.

Open source developer, trained in phonetics and auditory neuroscience.

Representative projects and topics: MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python; A clean, three-column Sphinx theme with Bootstrap for the PyData community; PHOIBLE data and development.; Praat scripts for streamlining manual measurements in acoustic analysis; tools for phoneticians and phonologists; the scripts and files used to generate my personal website.

I am a developer of open-source scientific software, and a scientist trained in acoustic phonetics, speech perception, and auditory neuroscience.
My scientific interest broadly centers on the perception and representation of speech sounds.
I'm (probably) most known for my work on MNE-Python.

c10: Recent work in computational biology includes 'Quantifying Memorization and Privacy Risks in Genomic Language Models'. Genomic language models (GLMs) have emerged as powerful tools for learning representations of DNA sequences, enabling advances in variant prediction, regulatory element identification, and cross-task transfer learning.

c11:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c12: Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "quantum dot, physics, optoelectronics, materials science '.

c13: YC batch W2026 founder at CellType. Role: Co-Founder & CEO. Co-Founder & CEO of CellType (W26). Yale Professor, 11,000+ citations. Built biological foundation models with Google. Building the agentic drug company.

c14: Recent work in ai and machine learning includes 'Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought?'. Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems... OpenAlex concept tags include "situation awareness, software deployment, risk analysis (engineering), psychology '.

c15: Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "computer science, artificial intelligence, computer vision, computer graphics (images) '.

c16: YC batch S2023 founder at Automorphic. Role: Founder. Building AI agents that can remember and self-improve at Automorphic.

c17: YC batch S2023 founder at Parea. Role: Founder. Published first paper in the highest-ranked number theory journal at age 17. M.Sc. from NYU as a Fulbright scholar. Researched applications of deep learning to medical imaging at Covera Health. Built semantic search systems and automatic code generation software at Jina AI.

c18: YC batch S2020 founder at Humanloop. Role: Founder. Ex-MonolithAI and Google. ML PhD @ UCL and MSc in Physics @ Cambridge.

c19:
[person] (@[person]). base in San Francisco, CA.

Founder/CEO of BentoML, previously @databricks, ML/AI Platforms & Systems, Product Design

Representative projects and topics: The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!; Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.; Applying Genetic Algorithm to Travelling Salesman Problem; Unified Model Serving Framework; Benchmark and optimize LLM inference across frameworks with ease; Everything you need to know about LLM inference.

Hi there 👋

🔭 I’m currently working on 🍱 BentoML - 🙋 We're hiring!
🤖 Ask me about building ML/AI applications
📷 Photography: Eyes of San Francisco

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Recent work in ai and machine learning includes 'Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought?'. Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems... OpenAlex concept tags include "reinforcement learning, computer science, artificial intelligence, machine learning '.

c00: Public author profile is associated with Nanjing Agricultural University. Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "biology, computer science, gene, computational biology '.

c01: YC batch S2020 founder at Humanloop. Role: Founder. Machine Learning and Engineering at Cambridge and MIT.

c02: Public author profile is associated with Universitätsklinikum Aachen. Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "biology, computer science, genetics, gene '.

c03:
[person] (@[person]). base in New York; works with Dagster Labs.

Founder of Dagster Labs. Ex-Facebook Engineer. GraphQL co-creator.

Representative projects and topics: Python framework for building scalable GraphQL servers; 📚 Parameterize, execute, and analyze notebooks; The best way to create REST APIs - Generate RESTful APIs from your GraphQL Server; An orchestration platform for the development, production, and observation of data assets..

c04: Public author profile is associated with Kunming University of Science and Technology. Recent work in computational biology includes 'A Hierarchical Sheaf Spectral Embedding Framework for Single-Cell RNA-seq Analysis'. Single-cell RNA-seq data analysis typically requires representations that capture heterogeneous local structure across multiple scales while remaining stable and interpretable... OpenAlex concept tags include "chemistry, medicine, physics, biology '.

c05: Public author profile is associated with Technische Universität Berlin. Recent work in computational biology includes 'Recent advances in modeling and simulation of biological phenomena in crowded and cellular environments'. While experiments and computer simulations to study biological phenomena are usually performed in diluted in vitro conditions, such phenomena happen inside the cellular cytoplasm, an environment densely packed with diverse macromolecules... OpenAlex concept tags include "chemistry, ligand (biochemistry), biophysics, dynamics (music) '.

c06: Public author profile is associated with East China University of Science and Technology. Recent work in computational biology includes 'Modeling the mutational dynamics of very short tandem repeats'. Short tandem repeats (STRs) are low-entropy regions in the genome, consisting of a short (1-6 bp) unit that is consecutively repeated multiple times... OpenAlex concept tags include "medicine, chemistry, biology, apoptosis '.

c07: Public author profile is associated with University of Twente. Recent work in computer vision includes 'SurgNavAR: An Augmented Reality Surgical Navigation Framework for Optical See-Through Head Mounted Displays'. Augmented reality (AR) devices with head mounted displays (HMDs) facilitate the direct superimposition of 3D preoperative imaging data onto the patient during surgery... OpenAlex concept tags include "augmented reality, sensory cue, psychology, gait '.

c08: Public author profile is associated with Southwest Forestry University. Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "medicine, biology, environmental science, environmental health '.

c09:
[person] (@[person])

Full-Time Open-Sourcerer. Focused on Swift & JavaScript. Makes macOS apps, CLI tools, npm packages.

Representative projects and topics: A collection of essential TypeScript types; 🌳 Tiny & elegant JavaScript HTTP client based on the Fetch API; 😎 Awesome lists about all kinds of interesting topics; 🤖 Awesome list for ChatGPT — an artificial intelligence chatbot developed by OpenAI; ⌨ Add user-customizable global keyboard shortcuts (hotkeys) to your macOS app in minutes; 💾 Swifty and modern UserDefaults.

i love code** **and unicorns

check out my latest app: Supercharge

and my latest blog post

c10: Public author profile is associated with Weizmann Institute of Science. Recent work in computational biology includes 'Modeling the mutational dynamics of very short tandem repeats'. Short tandem repeats (STRs) are low-entropy regions in the genome, consisting of a short (1-6 bp) unit that is consecutively repeated multiple times... OpenAlex concept tags include "biology, stem cell, computational biology, genetics '.

c11:
[person] (@[person]). base in Cambridge, MA.

Engineering @langchain-ai

Representative projects and topics: The agent engineering platform; Build resilient language agents as graphs.; Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks.; 🦜🔗 Docs for LangChain projects; Webhook trigger option for LangSmith's Fleet; ID vinyl records with Computer Vision & fetch metadata for radio DJs.

c12: Public author profile is associated with Weizmann Institute of Science. Recent work in computational biology includes 'Modeling the mutational dynamics of very short tandem repeats'. Short tandem repeats (STRs) are low-entropy regions in the genome, consisting of a short (1-6 bp) unit that is consecutively repeated multiple times... OpenAlex concept tags include "biology, gene, genetics, computational biology '.

c13: Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "quantum dot, physics, optoelectronics, materials science '.

c14:
[person] (@[person]). base in Half Moon Bay, California; works with Datasette.

Representative projects and topics: An open source multi-tool for exploring and publishing data; Python CLI utility and library for manipulating SQLite databases; Access large language models from the command-line; A command-line utility for taking automated screenshots of websites; Concatenate a directory full of files into a single prompt for use with LLMs; A tool for creating credentials for accessing S3 buckets.

c15: Public author profile is associated with Center for NanoScience. Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "materials science, inverse, physics, optics '.

c16:
[person] (@[person]). works with Dagster Labs.

@dagster-io, @illinois

Representative projects and topics: An orchestration platform for the development, production, and observation of data assets.; july; An encrypted messenger application for Android devices; Sling is a CLI tool that extracts data from a source storage/database and loads it in a target storage/database.; Get started with dbt in less than 1 minute from `git clone` to `dbt docs serve` for free!; The Python Package Index.

c17:
[person] (@[person]). base in Amsterdam; works with @pydantic.

[contact removed]

Representative projects and topics: Data validation using Python type hints; A flake8 plugin to check Pydantic related code.; Automatically add type hints for Django powered applications.; An extensible and sane implementation of JsonLogic; A Python library for tree data structures with an intuitive, yet powerful API.; PyPy is a very fast and compliant implementation of the Python language..

c18: YC batch W2024 founder at Sonauto. Role: Founder. Previously a software engineering intern at Vocode (YC W23) and an intern on the Machine Learning Team at Ada.

c19:
[person] (@[person]). base in Berkeley.

🏍 🛣 🌎 I miss _why.

Representative projects and topics: Give your JS App some Backbone with Models, Views, Collections, and Events; JavaScript's utility _ belt; Unfancy JavaScript; Literate Programming can be Quick and Dirty.; Code as Art, Art as Code. Processing and Ruby are meant for each other.; A TextMate Bundle for CoffeeScript.

{"message":"Moved Permanently","url":"

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Public author profile is associated with Simon Fraser University. Recent work in quantitative social science and economics includes 'GPU-accelerated Bayesian inference for block-cave mine monitoring via muon tomography'. We describe a Bayesian framework for an inverse problem arising from monitoring block caving operations via muon tomography... OpenAlex concept tags include "mathematics, computer science, philosophy, mathematical analysis '.

c00: Recent work in computational biology includes 'Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design'. Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale... OpenAlex concept tags include "antibody, molecular biology, virology, binding site '.

c01: Recent work in computational biology includes 'Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction'. We investigate the parameter space of transformer models trained on protein sequence data using a statistical mechanics framework, sampling the loss landscape at varying temperatures by Langevin dynamics to characterize the low-loss manifold and understand the mechanisms underlying the superior performance of transformers in protein structure prediction... OpenAlex concept tags include "computational biology, computer science, biology '.

c02: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "computer science, artificial intelligence, machine learning, task (project management) '.

c03: Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "medicine, biology, internal medicine, pathology '.

c04:
[person] (@[person]). base in Liège (Belgium); works with Georode.

Earth scientist, software developer, musician

Representative projects and topics: N-D labeled arrays and datasets in Python; Interactive audio in Jupyter; Xarray extension and framework for computer model simulations; A fast, versatile and user-friendly landscape evolution model; Publish Xarray Datasets via a REST API.; Manipulation and analysis of geometric objects on the sphere..

c05: Recent work in ai and machine learning includes 'Think Anywhere in Code Generation'. Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer... OpenAlex concept tags include "biology, chemistry, environmental science, oceanography '.

c06:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c07: Recent work in computer vision includes 'Benchmarking PhD-Level Coding in 3D Geometric Computer Vision'. AI-assisted coding has rapidly reshaped software practice and research workflows, yet today's models still struggle to produce correct code for complex 3D geometric vision... OpenAlex concept tags include "computer science, artificial intelligence, computer vision, machine learning '.

c08: Recent work in computational biology includes 'Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction'. We investigate the parameter space of transformer models trained on protein sequence data using a statistical mechanics framework, sampling the loss landscape at varying temperatures by Langevin dynamics to characterize the low-loss manifold and understand the mechanisms underlying the superior performance of transformers in protein structure prediction... OpenAlex concept tags include "medicine, chemistry, internal medicine, biochemistry '.

c09:
[person] (@[person]). base in San Francisco, CA.

Founder/CEO of BentoML, previously @databricks, ML/AI Platforms & Systems, Product Design

Representative projects and topics: The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!; Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.; Applying Genetic Algorithm to Travelling Salesman Problem; Unified Model Serving Framework; Benchmark and optimize LLM inference across frameworks with ease; Everything you need to know about LLM inference.

Hi there 👋

🔭 I’m currently working on 🍱 BentoML - 🙋 We're hiring!
🤖 Ask me about building ML/AI applications
📷 Photography: Eyes of San Francisco

c10:
[person] (@[person]). base in Half Moon Bay, California; works with Datasette.

Representative projects and topics: An open source multi-tool for exploring and publishing data; Python CLI utility and library for manipulating SQLite databases; Access large language models from the command-line; A command-line utility for taking automated screenshots of websites; Concatenate a directory full of files into a single prompt for use with LLMs; A tool for creating credentials for accessing S3 buckets.

c11: Recent work in quantitative social science and economics includes 'Longest weakly increasing subsequences of discrete random walks on the integers with heavy tailed distribution of increments'. We investigate the behavior of the length of the longest weakly increasing subsequences (weak LIS) of $n$-step random walks with nonzero integer increments $k = \pm 1, \pm 2, \dots$ given by a zero-mean, symmetric heavy tailed mass distribution proportional to $|k|^{-1-α}$ for several values of the real parameter $α> 0$ together with that of the simple random walk ($k=\pm 1$), to which the $n$-step heavy tailed random walks tends when $α> (1+o(1))\log_{2}{n}$... OpenAlex concept tags include "poisson distribution, statistics, statistical physics, random variable '.

c12: Recent work in ai and machine learning includes 'Think Anywhere in Code Generation'. Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer... OpenAlex concept tags include "artificial intelligence, generative model, algorithm, algebra over a field '.

c13: YC batch S2023 founder at Parea. Role: Founder. Published first paper in the highest-ranked number theory journal at age 17. M.Sc. from NYU as a Fulbright scholar. Researched applications of deep learning to medical imaging at Covera Health. Built semantic search systems and automatic code generation software at Jina AI.

c14: Recent work in computational materials and physics includes 'Learning the Exact Flux: Neural Riemann Solvers with Hard Constraints'. Godunov-type methods, which obtain numerical fluxes through local Riemann problems at cell interfaces, are among the most fundamental and widely used numerical methods in computational fluid dynamics... OpenAlex concept tags include "storm, computer science, meteorology, shallow water equations '.

c15:
[person] (@[person]). base in Bristol, UK; works with University of Bristol.

Climate, glaciers, and programming.

Representative projects and topics: Open Global Glacier Model; Add geolocalised subsetting, masking, and plotting operations to xarray; N-D labeled arrays and datasets in Python; Lectures notes of the scientific programming course at the University of Innsbruck; Educational material about glaciers, powered by OGGM and MyBinder; Class activities and notebooks for the MSc "Quantifying Climate Risks" class taught at Uni Bristol.

c16: Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "quantum dot, physics, optoelectronics, materials science '.

c17:
[person] (@[person]). base in San Francisco; works with @langchain-ai.

Building agent frameworks @langchain-ai. Head of the @webdriverio project. Open source & open standards advocate.

Representative projects and topics: Next-gen browser and mobile automation test framework for Node.js; A curated list of delightful Selenium resources.; Boilerplate project to run WebdriverIO tests with Cucumber; a lightweight rgb/rgba to hex parser; A Node.js based package and CLI library for launching Selenium with WebDrivers support (Chrome, Firefox, IE, Edge); Boilerplate project to run WebdriverIO tests with Appium to test native applications on iOS and Android.

Open Source & Open Standards Advocate.

🔭 I’m currently working at **LangChain** building Agent Frameworks

🤝 I’m automating things with **WebdriverIO

📝 I regulary write articles in **my blog

🧠 I'm learning Video Editing with Final Cut Pro

💬 Ask me about **WebdriverIO / Test Automation / VSCode Extension Development / Node.js / TypeScript

⚡ Fun fact **I grew up on the country side in Germany next to 🐮 and 🐔

Skills

c18:
[person] (@[person]). works with @langchain-ai.

Trace tackler @ LangChain

Representative projects and topics: An Open-Source Asynchronous Coding Agent; 📃 A better UX for chat, writing content, and coding with LLMs.; An open-source, no-code agent building platform.; 📲 An agent for sourcing, curating, and scheduling social media posts with human-in-the-loop.; 🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface.; 📥 An inbox UX for interacting with human-in-the-loop agents..

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type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Recent work in computational biology includes 'Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design'. Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale... OpenAlex concept tags include "computer science, biology, data science, computational biology '.

c00: Public author profile is associated with Schott (Germany). Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "physics, quantum dot, photon, optoelectronics '.

c01: Public author profile is associated with Schott (Germany). Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "quantum dot, photon, optoelectronics, physics '.

c02: YC batch S2023 founder at Parea. Role: Founder. Published first paper in the highest-ranked number theory journal at age 17. M.Sc. from NYU as a Fulbright scholar. Researched applications of deep learning to medical imaging at Covera Health. Built semantic search systems and automatic code generation software at Jina AI.

c03: Public author profile is associated with University of Bari Aldo Moro. Recent work in quantitative social science and economics includes 'Violence Against Women: a pilot study on the perception of Apulian High school students'. Violence Against Women (VAW) is a widespread issue deeply rooted in social and cultural structures... OpenAlex concept tags include "biology, statistics, geography, ecology '.

c04:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c05: Public author profile is associated with Hong Kong Polytechnic University. Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "materials science, microstructure, composite material, metallurgy '.

c06: Public author profile is associated with University of Würzburg. Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "quantum dot, physics, photon, quantum '.

c07: Public author profile is associated with University of Manchester. Recent work in computational materials and physics includes 'Deep-UV bleaching of charge disorder in encapsulated graphene'. Disorder masks much of the rich physics in two-dimensional electronic systems, with charged impurities often the limiting factor... OpenAlex concept tags include "materials science, optoelectronics, physics, nanotechnology '.

c08: Public author profile is associated with Universidade de São Paulo. Recent work in quantitative social science and economics includes 'Longest weakly increasing subsequences of discrete random walks on the integers with heavy tailed distribution of increments'. We investigate the behavior of the length of the longest weakly increasing subsequences (weak LIS) of $n$-step random walks with nonzero integer increments $k = \pm 1, \pm 2, \dots$ given by a zero-mean, symmetric heavy tailed mass distribution proportional to $|k|^{-1-α}$ for several values of the real parameter $α> 0$ together with that of the simple random walk ($k=\pm 1$), to which the $n$-step heavy tailed random walks tends when $α> (1+o(1))\log_{2}{n}$... OpenAlex concept tags include "physics, mathematics, discrete mathematics, computer science '.

c10: Public author profile is associated with University of Manchester. Recent work in computational materials and physics includes 'Deep-UV bleaching of charge disorder in encapsulated graphene'. Disorder masks much of the rich physics in two-dimensional electronic systems, with charged impurities often the limiting factor... OpenAlex concept tags include "materials science, physics, optoelectronics, nanotechnology '.

c11:
[person] (@[person])

Representative projects and topics: Sampling CPU profiler for Ruby; Recipes for using Python's pandas library; spy on the DNS queries your computer is making; Source for Mess With DNS; simple markdown translator; twine.

hello!

The main repositories here are a Ruby profiler I wrote called rbspy and a cookbook for learning pandas. There are also dozens of other tiny toy projects that I made for fun once and don't maintain at all.

Some other places you can find my work on the internet:

blog:
zines:

c12: YC batch W2026 founder at CellType. Role: Co-Founder & CEO. Co-Founder & CEO of CellType (W26). Yale Professor, 11,000+ citations. Built biological foundation models with Google. Building the agentic drug company.

c13: Public author profile is associated with Erasmus MC. Recent work in computer vision includes 'SurgNavAR: An Augmented Reality Surgical Navigation Framework for Optical See-Through Head Mounted Displays'. Augmented reality (AR) devices with head mounted displays (HMDs) facilitate the direct superimposition of 3D preoperative imaging data onto the patient during surgery... OpenAlex concept tags include "neurocognitive, cognition, psychiatry, psychology '.

c14: Public author profile is associated with University of Manchester. Recent work in computational materials and physics includes 'Deep-UV bleaching of charge disorder in encapsulated graphene'. Disorder masks much of the rich physics in two-dimensional electronic systems, with charged impurities often the limiting factor... OpenAlex concept tags include "semiconductor, electron, physics, quantum hall effect '.

c15:
[person] (@[person]). works with Dagster Labs.

@dagster-io, @illinois

Representative projects and topics: An orchestration platform for the development, production, and observation of data assets.; july; An encrypted messenger application for Android devices; Sling is a CLI tool that extracts data from a source storage/database and loads it in a target storage/database.; Get started with dbt in less than 1 minute from `git clone` to `dbt docs serve` for free!; The Python Package Index.

c16: YC batch S2020 founder at Humanloop. Role: Founder. Machine Learning and Engineering at Cambridge and MIT.

c17: YC batch W2026 founder at CellType. Role: Co-Founder. Co-Founder @ CellType (W26). ML @ Yale & EPFL. Co-developed Cell2Sentence at Yale and published at ICML. Previously led large-scale foundation model training at a biotech startup and built software to control CERN's Large Hadron Collider.

c18:
[person] (@[person]). base in San Francisco; works with @langchain-ai.

Building agent frameworks @langchain-ai. Head of the @webdriverio project. Open source & open standards advocate.

Representative projects and topics: Next-gen browser and mobile automation test framework for Node.js; A curated list of delightful Selenium resources.; Boilerplate project to run WebdriverIO tests with Cucumber; a lightweight rgb/rgba to hex parser; A Node.js based package and CLI library for launching Selenium with WebDrivers support (Chrome, Firefox, IE, Edge); Boilerplate project to run WebdriverIO tests with Appium to test native applications on iOS and Android.

Open Source & Open Standards Advocate.

🔭 I’m currently working at **LangChain** building Agent Frameworks

🤝 I’m automating things with **WebdriverIO

📝 I regulary write articles in **my blog

🧠 I'm learning Video Editing with Final Cut Pro

💬 Ask me about **WebdriverIO / Test Automation / VSCode Extension Development / Node.js / TypeScript

⚡ Fun fact **I grew up on the country side in Germany next to 🐮 and 🐔

Skills

c19: YC batch S2023 founder at Automorphic. Role: Founder. When not working on Automorphic, building AI to beat me at chess.

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Public author profile is associated with United States Naval Research Laboratory. Recent work in computational materials and physics includes 'NLSTEM: Non-local denoising for enhanced 4D-STEM pattern indexing'. 4D-STEM-based orientation and phase mapping has enabled rapid microstructure quantification that can be directly combined with standard TEM- and STEM-based imaging modes... OpenAlex concept tags include "materials science, composite material, metallurgy, computer science '.

c00: Recent work in ai and machine learning includes 'Aligned, Orthogonal or In-conflict: When can we safely optimize Chain-of-Thought?'. Chain-of-Thought (CoT) monitoring, in which automated systems monitor the CoT of an LLM, is a promising approach for effectively overseeing AI systems... OpenAlex concept tags include "situation awareness, software deployment, risk analysis (engineering), psychology '.

c01: Recent work in ai and machine learning includes 'Tucker Attention: A generalization of approximate attention mechanisms'. The pursuit of reducing the memory footprint of the self-attention mechanism in multi-headed self attention (MHA) spawned a rich portfolio of methods, e.g., group-query attention (GQA) and multi-head latent attention (MLA)... OpenAlex concept tags include "mathematics, computer science, applied mathematics, mathematical analysis '.

c02:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c03:
[person] (@[person]). base in Berkeley.

🏍 🛣 🌎 I miss _why.

Representative projects and topics: Give your JS App some Backbone with Models, Views, Collections, and Events; JavaScript's utility _ belt; Unfancy JavaScript; Literate Programming can be Quick and Dirty.; Code as Art, Art as Code. Processing and Ruby are meant for each other.; A TextMate Bundle for CoffeeScript.

{"message":"Moved Permanently","url":"

c04: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "computer science, artificial intelligence, machine learning, task (project management) '.

c05: Recent work in computational biology includes 'Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design'. Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale...

c06: Recent work in quantitative social science and economics includes 'Penalized GMM Framework for Inference on Functionals of Nonparametric Instrumental Variable Estimators'. This paper develops a penalized GMM (PGMM) framework for automatic debiased inference on functionals of nonparametric instrumental variable estimators... OpenAlex concept tags include "estimator, mathematics, computer science, mathematical optimization '.

c07: Recent work in ai and machine learning includes 'Do covariates explain why these groups differ? The choice of reference group can reverse conclusions in the Oaxaca-Blinder decomposition'. Scientists often want to explain why an outcome is different in two groups... OpenAlex concept tags include "psychology, public economics, outbreak, philosophy '.

c08:
[person] (@[person]). base in Minneapolis; works with University of Washington.

Open source developer, trained in phonetics and auditory neuroscience.

Representative projects and topics: MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python; A clean, three-column Sphinx theme with Bootstrap for the PyData community; PHOIBLE data and development.; Praat scripts for streamlining manual measurements in acoustic analysis; tools for phoneticians and phonologists; the scripts and files used to generate my personal website.

I am a developer of open-source scientific software, and a scientist trained in acoustic phonetics, speech perception, and auditory neuroscience.
My scientific interest broadly centers on the perception and representation of speech sounds.
I'm (probably) most known for my work on MNE-Python.

c09:
[person] (@[person]). base in California; works with @carbonplan.

Software/Data Engineer @carbonplan | Core Maintainer of xarray @pydata

Representative projects and topics: N-D labeled arrays and datasets in Python; An intake plugin for parsing an Earth System Model (ESM) catalog and loading assets into xarray datasets.; Parallel computing with task scheduling; The Xarray landing page; Climate downscaling using CMIP6 data; A small utility for generating ND array pyramids using Xarray and Zarr..

Coucou 👋 🌎

As a software engineer, it has been extremely rewarding for me to work across institutional and geographical boundaries to collaborate on research tools and software. I am currently employed by @CarbonPlan, a non-profit working on open data science tools and climate policy issues surrounding carbon removal and climate solutions.

Also, I am an advocate for and contributor to open-source software. In the scientific Python data ecosystem, I help maintain Xarray, dask-jobqueue, and a few other packages.

📝 Latest Blog Posts

« Multitude de Stromae » - Des morceaux aussi forts sur des sujets si primordials 🎶
Dictionary Merge and Update Operators in Python 3.9
« Mesdames » - Parce que l’avenir appartient à celles qu’on aime trop 🎶
How to Generate Wildcard SSL Certificate using Let’s Encrypt/Certbot on CentOS
🚀 Xarray v0.17.0 is here!

More on blog.andersonbanihirwe.dev

🎥 Latest YouTube Videos

Santé 🥂 🍻

c10:
[person] (@[person]). base in San Francisco; works with @langchain-ai.

Building agent frameworks @langchain-ai. Head of the @webdriverio project. Open source & open standards advocate.

Representative projects and topics: Next-gen browser and mobile automation test framework for Node.js; A curated list of delightful Selenium resources.; Boilerplate project to run WebdriverIO tests with Cucumber; a lightweight rgb/rgba to hex parser; A Node.js based package and CLI library for launching Selenium with WebDrivers support (Chrome, Firefox, IE, Edge); Boilerplate project to run WebdriverIO tests with Appium to test native applications on iOS and Android.

Open Source & Open Standards Advocate.

🔭 I’m currently working at **LangChain** building Agent Frameworks

🤝 I’m automating things with **WebdriverIO

📝 I regulary write articles in **my blog

🧠 I'm learning Video Editing with Final Cut Pro

💬 Ask me about **WebdriverIO / Test Automation / VSCode Extension Development / Node.js / TypeScript

⚡ Fun fact **I grew up on the country side in Germany next to 🐮 and 🐔

Skills

c11:
[person] (@[person]). base in Sacramento; works with Mathematics and Statistics Department, CSU Sacramento.

Statistics Professor @ Sacramento State

Representative projects and topics: Unmaintained scripts; Utility scripts, python modules, and dotfiles to be stored in home folder; Log of research activities for PhD in statistics; Transform Serial R Code into Parallel R Code; course materials for UC Davis STA141C: Big Data & High Performance Statistical Computing; running examples on slurm cluster.

c12:
[person] (@[person]). base in Salt Lake City, Utah, USA; works with @epicweb-dev.

Improving 🌎 with quality software · Husband, 6x Dad, Latter-day Saint, Dev Educator, MVP ⚡ EpicAI.pro 🌌 EpicWeb.dev 🚀 EpicReact.dev

Representative projects and topics: My personal website; The workshop app for all workshops on EpicWeb.dev; 🐐 Simple and complete React DOM testing utilities that encourage good testing practices.; 🦤 Give me MDX/TSX strings and I'll give you back a component you can render. Supports imports!; An RSS feed generator for media (audio/video).; 🔀 Cross platform setting of environment scripts.

alt="Helping people make the world a better place through quality software"
src="
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Learn more about me

c13:
[person] (@[person]). base in Chicago; works with Canonical.

open science enthusiast ~ software developer ~ an under the sea code monkey

Representative projects and topics: The snapd and snap tools enable systems to work with .snap files.; PMR ( configs used by CheckBox developers; Creating delicious APIs for Django apps since 2010. (fork); toy app to demonstrate some tastypie behavior; The official website for the Ubuntu operating system; A tool to create Ubuntu images for embedded systems - mainly ARM/ARM64 boards like Beaglebone, RaspberryPi 2, RaspberryPI 3 or 96Boards DragonBoard410c.

c14:
[person] (@[person]). base in Liège (Belgium); works with Georode.

Earth scientist, software developer, musician

Representative projects and topics: N-D labeled arrays and datasets in Python; Interactive audio in Jupyter; Xarray extension and framework for computer model simulations; A fast, versatile and user-friendly landscape evolution model; Publish Xarray Datasets via a REST API.; Manipulation and analysis of geometric objects on the sphere..

c15:
[person] (@[person]). base in Stanford.

I like to train Deep Neural Nets on large datasets.

Representative projects and topics: The simplest, fastest repository for training/finetuning medium-sized GPTs.; The best ChatGPT that $100 can buy.; LLM training in simple, raw C/CUDA; Inference Llama 2 in one file of pure C; A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API; AI agents running research on single-GPU nanochat training automatically.

I like deep neural nets.

c16:
[person] (@[person]). base in Mountain View, California; works with Google.

Engineering Lead at Google working on Chrome & Web Platform

Representative projects and topics: ⚡Faster subsequent page-loads by prefetching in-viewport links during idle time; 📦 Workbox: JavaScript libraries for Progressive Web Apps; Extract & Inline Critical-path CSS in HTML pages; Material Design Components in HTML/CSS/JS; Helping you select a JavaScript framework - Todo apps for React.js, Angular, Vue and many more; Yeoman - a set of tools for automating development workflow.

🔭 I’m currently working on AI at Google (Gemini, Agents, Vertex)
👯 I’m looking to collaborate on Developer Tooling
🤔 I’m looking for help with Framework collaborations
💬 Ask me about anything

c17: Recent work in quantitative social science and economics includes 'A Unified Framework for Nonlinear Mediation Analysis of Random Objects'. Mediation analysis for complex, non-Euclidean data, such as probability distributions, compositions, images, and networks, presents significant methodological challenges due to the inherent nonlinearity and geometric constraints of such spaces... OpenAlex concept tags include "medicine, biology, cancer, internal medicine '.

c18: Recent work in computational biology includes 'Quantifying Memorization and Privacy Risks in Genomic Language Models'. Genomic language models (GLMs) have emerged as powerful tools for learning representations of DNA sequences, enabling advances in variant prediction, regulatory element identification, and cross-task transfer learning.

c19: Recent work in ai and machine learning includes 'Think Anywhere in Code Generation'. Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer... OpenAlex concept tags include "artificial intelligence, generative model, algorithm, algebra over a field '.

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补


source: Public author profile is associated with Klox Technologies (Canada). Recent work in quantitative social science and economics includes 'GPU-accelerated Bayesian inference for block-cave mine monitoring via muon tomography'. We describe a Bayesian framework for an inverse problem arising from monitoring block caving operations via muon tomography... OpenAlex concept tags include "physics, large hadron collider, particle physics, nuclear physics '.

c01: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "materials science, computer science, engineering, medicine '.

c02: Recent work in ai and machine learning includes 'Think Anywhere in Code Generation'. Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer... OpenAlex concept tags include "biology, chemistry, environmental science, oceanography '.

c03:
[person] (@[person]). base in Half Moon Bay, California; works with Datasette.

Representative projects and topics: An open source multi-tool for exploring and publishing data; Python CLI utility and library for manipulating SQLite databases; Access large language models from the command-line; A command-line utility for taking automated screenshots of websites; Concatenate a directory full of files into a single prompt for use with LLMs; A tool for creating credentials for accessing S3 buckets.

c04: Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "computer science, artificial intelligence, computer vision, computer graphics (images) '.

c05: Recent work in computer vision includes 'Video Models Reason Early: Exploiting Plan Commitment for Maze Solving'. Video diffusion models exhibit emergent reasoning capabilities like solving mazes and puzzles, yet little is understood about how they reason during generation... OpenAlex concept tags include "computer science, artificial intelligence, machine learning, task (project management) '.

c06: Recent work in computational materials and physics includes 'Molecular beam epitaxy of wafer-scale O-band InAs/InGaAs quantum dots on GaAs for quantum photonics'. We report a scalable molecular beam epitaxy strategy to achieve a low density of O-band electrically tunable InAs/InGaAs quantum dots (QDs) on GaAs(001) substrates... OpenAlex concept tags include "optics, physics, electron, engineering '.

c07: Recent work in computer vision includes 'OmniRoam: World Wandering via Long-Horizon Panoramic Video Generation'. Modeling scenes using video generation models has garnered growing research interest in recent years... OpenAlex concept tags include "medicine, biology, internal medicine, pathology '.

c08: Recent work in computational biology includes 'A Hierarchical Sheaf Spectral Embedding Framework for Single-Cell RNA-seq Analysis'. Single-cell RNA-seq data analysis typically requires representations that capture heterogeneous local structure across multiple scales while remaining stable and interpretable... OpenAlex concept tags include "betti number, physics, combinatorics, algorithm '.

c09: YC batch W2026 founder at CellType. Role: Co-Founder. Co-Founder @ CellType (W26). ML @ Yale & EPFL. Co-developed Cell2Sentence at Yale and published at ICML. Previously led large-scale foundation model training at a biotech startup and built software to control CERN's Large Hadron Collider.

c11:
[person] (@[person]). base in San Francisco, CA.

Founder/CEO of BentoML, previously @databricks, ML/AI Platforms & Systems, Product Design

Representative projects and topics: The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!; Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.; Applying Genetic Algorithm to Travelling Salesman Problem; Unified Model Serving Framework; Benchmark and optimize LLM inference across frameworks with ease; Everything you need to know about LLM inference.

Hi there 👋

🔭 I’m currently working on 🍱 BentoML - 🙋 We're hiring!
🤖 Ask me about building ML/AI applications
📷 Photography: Eyes of San Francisco

c12:
[person] (@[person]). works with @langchain-ai.

Trace tackler @ LangChain

Representative projects and topics: An Open-Source Asynchronous Coding Agent; 📃 A better UX for chat, writing content, and coding with LLMs.; An open-source, no-code agent building platform.; 📲 An agent for sourcing, curating, and scheduling social media posts with human-in-the-loop.; 🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface.; 📥 An inbox UX for interacting with human-in-the-loop agents..

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c14:
[person] (@[person]). base in Mountain View, California; works with Google.

Engineering Lead at Google working on Chrome & Web Platform

Representative projects and topics: ⚡Faster subsequent page-loads by prefetching in-viewport links during idle time; 📦 Workbox: JavaScript libraries for Progressive Web Apps; Extract & Inline Critical-path CSS in HTML pages; Material Design Components in HTML/CSS/JS; Helping you select a JavaScript framework - Todo apps for React.js, Angular, Vue and many more; Yeoman - a set of tools for automating development workflow.

🔭 I’m currently working on AI at Google (Gemini, Agents, Vertex)
👯 I’m looking to collaborate on Developer Tooling
🤔 I’m looking for help with Framework collaborations
💬 Ask me about anything

c15:
[person] (@[person])

Senior Data Scientist

Representative projects and topics: Python utilities to download and parse the MNIST dataset; Service to preview documentation from GitHub artifacts; Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; A high-performance library for compressed ndarrays, with a flexible computational engine; Tests to read Iceberg directly from pandas; Meson PEP 517 Python build backend.

c16: Recent work in computational biology includes 'Latent-Y: A Lab-Validated Autonomous Agent for De Novo Drug Design'. Drug discovery relies on iterative expert workflows that are slow to parallelize and difficult to scale...

c17:
[person] (@[person]). base in Santa Clara, CA; works with @BentoML.

CNCF Ambassador & KubeVela Maintainer (,,• ₃ •,,)

Representative projects and topics: A self-evolving personal AI assistant.; The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!; Declarative Workflow of KubeVela which can run as standalone.; A cloud-native Pipeline resource.; The Modern Application Platform.; Docker for Your ML/DL Models Based on OCI Artifacts.

[person]

I'm currently working on KubeVela & BentoML :sparkles:.

c18:
[person] (@[person]). base in Washington, DC; works with @PrefectHQ.

CEO at @PrefectHQ. Building FastMCP. Mostly harmless.

Representative projects and topics: 🚀 The fast, Pythonic way to build MCP servers and clients.; Prefect is a workflow orchestration framework for building resilient data pipelines in Python.; an ambient intelligence library; 📋💬 Simple code-to-context utility; Generate images with hidden text; 🌴 Simple utility for managing parallel Claude Code instances.

Hello 👋

I'm Jeremiah.

I love building tools that make developers' lives easier. You might know me from FastMCP, the standard Python framework for working with the Model Context Protocol, or Prefect, the workflow engine used by thousands of data teams worldwide.

`$ whoami`

🏢 Founder & CEO at Prefect
📍 Based in Washington, DC
🎯 Strategic advisor to Spotify, FabFitFun, and Positive Sum
📊 Former Apache Airflow PMC member
☕ Global Ambassador for Compass Coffee
🌎 Mostly Harmless

`$ ping`

💻 [person].dev

c19:
[person] (@[person]). base in Liège (Belgium); works with Georode.

Earth scientist, software developer, musician

Representative projects and topics: N-D labeled arrays and datasets in Python; Interactive audio in Jupyter; Xarray extension and framework for computer model simulations; A fast, versatile and user-friendly landscape evolution model; Publish Xarray Datasets via a REST API.; Manipulation and analysis of geometric objects on the sphere..

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c00：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

criteria: 没有具体关联 只有泛泛的领域相似 有具体共同方向或可用的互补能力 有非常明确的共同工作内容或直接互补

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c01：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c02：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c03：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c04：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c05：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c06：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c07：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c08：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c09：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c10：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c11：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c12：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c13：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c14：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c15：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c16：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c17：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c18：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

type: score

instructions: 只比较 on.source 与 ctx[0].candidates.c19：双方职业、研究、技能或资源存在多强的具体关联，值得进一步交流或协作？依据这两份材料中的实际内容，区分泛泛相似与具体共同方向、互补能力；不得编造经历、意愿或已发生的合作。同批其他候选是独立问题，不作为这个候选的证据。

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补

有具体共同方向或可用的互补能力

有非常明确的共同工作内容或直接互补