source: YC batch S2025 founder at Modelence. Role: Co-Founder & CTO. An engineer and engineering manager with 18 years of experience. Was the founding engineer and Director of Engineering at CodeSignal.

c00: Public author profile is associated with Folkwang University of the Arts. 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 "cosmic ray, physics, air shower, nuclear physics '.

c02: 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 "physics, computer science, artificial intelligence, statistical physics '.

c03: 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 '.

c04:
[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..

c05: Public author profile is associated with Utah Cancer Specialists. 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 "medicine, biology '.

c06: 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: Public author profile is associated with Jilin Province Science and Technology Department. 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 "chemistry, biology, biochemistry, engineering '.

c10: 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 '.

c11: 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 '.

c12: Public author profile is associated with Bielefeld University. Recent work in quantitative social science and economics includes 'Retrospective Economic Evaluation of Group Testing in the COVID-19 Pandemic'. Surveillance of diseases in a pandemic is an important part of public health policy... OpenAlex concept tags include "computer science, mathematical optimization, mathematics, algorithm '.

c13: 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, machine learning, artificial intelligence, mathematics '.

c15: Public author profile is associated with Guangdong Food and Drug Vocational College. 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 "elevator, engineering, operating system, epistemology '.

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... OpenAlex concept tags include "mathematics, computer science, artificial intelligence, machine learning '.

c17: Public author profile is associated with Friedrich-Alexander-Universität Erlangen-Nürnberg. Recent work in quantitative social science and economics includes 'Retrospective Economic Evaluation of Group Testing in the COVID-19 Pandemic'. Surveillance of diseases in a pandemic is an important part of public health policy... OpenAlex concept tags include "medicine, computer science, mathematics, biology '.

c18: Public author profile is associated with The University of Texas at Austin. 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 "computer science, mathematics, applied mathematics, mathematical analysis '.

c19: Public author profile is associated with Indian Institute of Science Education and Research Kolkata. 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 "computer science, materials science, artificial intelligence, physics '.

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: YC batch W2026 founder at Captain. Role: Co-Founder and CTO. CTO @ Captain | Published AI NLP Researcher | Built OCR engines @ Boar's Head | Scaled high-performance RAG pipelines for the past 4 years | Built a Cross Region L2 Datacenter

c00: Public author profile is associated with Oak Ridge National Laboratory. 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 "computer science, mathematical optimization, physics, mathematics '.

c01: Public author profile is associated with Munster Technological University. Recent work in ai and machine learning includes 'Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration'. Multimodal deep learning for cancer prognosis is commonly assumed to benefit from synergistic cross-modal interactions, yet this assumption has not been directly tested in survival prediction settings... OpenAlex concept tags include "psychology, computer science, artificial intelligence, machine learning '.

c02:
[person] (@[person]). base in Brooklyn, NY; works with Jamsocket.

Sandboxes @modal-labs (formerly: founder @jamsocket)

Representative projects and topics: A distributed system for running WebSocket services at scale.; A realtime CRDT-based document store, backed by S3.; Synchronizable structs for Rust.; A client for sending notifications to your own phone or desktop.; Visualize Bluesky conversations as a tree.; Simple Diff Function implemented in Python, PHP, CoffeeScript, and JavaScript.

c03:
[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.

c04: Public author profile is associated with Santobono Children's Hospital. 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, mathematics, environmental science, statistics '.

c05:
[person] (@[person]). base in London, United Kingdom; works with @pydantic.

The Pydantic Stack: Pydantic Validation, Pydantic AI and Pydantic Logfire

Representative projects and topics: Data validation using Python type hints; AI Agent Framework, the Pydantic way; A minimal, secure Python interpreter written in Rust for use by AI; AI observability platform for production LLM and agent systems.; Simple, modern and fast file watching and code reload for Python, written in Rust; Dev tools for python.

c06: Public author profile is associated with Antea Group (France). 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 "medicine, biology, genetics, immunology '.

c07: Public author profile is associated with Guangdong University of Technology. Recent work in ai and machine learning includes 'Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration'. Multimodal deep learning for cancer prognosis is commonly assumed to benefit from synergistic cross-modal interactions, yet this assumption has not been directly tested in survival prediction settings... OpenAlex concept tags include "computer science, materials science, physics, engineering '.

c08: 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 '.

c10:
[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

c13:
[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.

c14: Public author profile is associated with Max Planck Institute for Dynamics of Complex Technical Systems. 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, mathematical optimization, artificial intelligence '.

c15: 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 '.

c16: 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 '.

c17:
[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.

c18:
[person] (@[person]). base in Austin, TX; works with NVIDIA.

Representative projects and topics: Multi-agent project starter for Claude Code. Fill in PROJECT.md, run /bootstrap, start building.; Experiment in AI Agent tools via creation of an email assistant.; cuTile is a programming model for writing parallel kernels for NVIDIA GPUs; NVIDIA curated collection of educational resources related to general purpose GPU programming.; Python for HPC Tutorial Notebooks; The NumFOCUS DISCOVER Cookbook (Diverse & Inclusive Spaces and Conferences: Overall Vision and Essential Resources). A guide for organizing more diverse and inclusive events and conferences, produced by the NumFOCUS Diversity & Inclusion in Scientific Computing (DISC) Program, with support from the Moore Foundation..

Hi there 👋

🔭 I’m currently working on CUDA Python @ NVIDIA
👯 I’m looking to collaborate on DISCOVER Cookbook, gpu dsls
😄 Pronouns: he / him

📊 GitHub Stats:

c19:
[person] (@[person]). base in Bengaluru; works with @pydantic.

Software Engineer @pydantic

Representative projects and topics: Agent Framework / shim to use Pydantic with LLMs; AI observability platform for production LLM and agent systems.; Uncomplicated Observability for Python and beyond! 🪵🔥; JavaScript and TypeScript SDK for Logfire.

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: YC batch W2023 founder at Trigger.dev. Role: CTO. Co-founded CodeSchool.com. Works on JSON Hero, a popular developer tool.

c00:
[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.

c01: 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, surgery, crystal structure, geomorphology '.

c02:
[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.

c03:
[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.

c04:
[person] (@[person]). base in ABQ.

Lead developer on @sympy. Doing math and Python.

Representative projects and topics: A Python REPL the way I like it; The git workflow for contributing to open source repositories.; A collection of a bunch of my .files; Tool to automatically replace 'import *' in Python files with explicit imports; A computer algebra system written in pure Python.; Symbolic representation of matrix multiplication decompositions from Google DeepMind's AlphaEvolve paper.

c05: Public author profile is associated with The University of Texas at Austin. Recent work in computational biology includes 'Poisoning the Genome: Targeted Backdoor Attacks on DNA Foundation Models'. Genomic foundation models trained on DNA sequences have demonstrated remarkable capabilities across diverse biological tasks, from variant effect prediction to genome design... OpenAlex concept tags include "genome, artificial intelligence, sliding window protocol, data mining '.

c06:
[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

c07:
[person] (@[person]). works with @bentoml.

emacs otaku

Representative projects and topics: Hua (㕦) is a hy-like lisp language to lua compiler.; [zsy.ds4] is is a simple max patch to handle Dualshock 4 inputs (over bluetooth); retro forth in lua; lightweight script for nanopi oled hat; toy dsp library in python; The Modular Platform (includes MAX & Mojo).

c08:
[person] (@[person]). base in Bangalore, India; works with @google.

Software Engineer @google

Representative projects and topics: Yahoo! Cloud Serving Benchmark; Implementation of the paper - IPACT: A Dynamic Protocol for an Ethernet PON (EPON) by Glen Kramer and Biswanath Mukherjee; Run program in a sandbox-like environment; Use C# instead of YAML to define your Azure DevOps pipelines; A library to create QueryExpression the fluent way; CSharpier is an opinionated code formatter for c#..

c09: 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 '.

c10:
[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.

c11:
[person] (@[person]). base in London, United Kingdom; works with @pydantic.

The Pydantic Stack: Pydantic Validation, Pydantic AI and Pydantic Logfire

Representative projects and topics: Data validation using Python type hints; AI Agent Framework, the Pydantic way; A minimal, secure Python interpreter written in Rust for use by AI; AI observability platform for production LLM and agent systems.; Simple, modern and fast file watching and code reload for Python, written in Rust; Dev tools for python.

c12: Public author profile is associated with Microsoft Research (United Kingdom). 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, artificial intelligence, machine learning, mathematics '.

c13: Public author profile is associated with Imperial Valley College. 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 "computational biology, computer science, biology, chemistry '.

c14: 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 '.

c15:
[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..

c16: 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 '.

c17: Public author profile is associated with Exscien (United States). 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, graph, artificial intelligence, machine learning '.

c18:
[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":"

c19:
[person] (@[person]). works with Prefect.

Platform Engineer @PrefectHQ

Representative projects and topics: Configs for my development environment.; Resume in Markdown, styled with CSS, output to HTML and PDF.

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: YC batch S2023 founder at Automorphic. Role: Founder. Building the next generation of artificial narrow intelligence.

c00: Public author profile is associated with Johns Hopkins University. 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, medicine, gene, cell biology '.

c01: 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 '.

c02: 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) '.

c03: Public author profile is associated with Jinan Central Hospital. 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, medicine, internal medicine '.

c05: 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 '.

c06: 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 '.

c08: Public author profile is associated with Antea Group (France). 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 "medicine, biology, genetics, immunology '.

c11: Public author profile is associated with Imperial Valley College. 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 "computational biology, computer science, biology, chemistry '.

c12: Public author profile is associated with Tianjin University of Technology. 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 "chemistry, materials science, chemical engineering, physics '.

c13: 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 '.

c14: Public author profile is associated with Nanchang 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 "chemistry, biology, engineering, biochemistry '.

c15: Public author profile is associated with Tianjin Hospital. Recent work in computational materials and physics includes 'A Precision Emulation Approach to the GPU Acceleration of Ab Initio Electronic Structure Calculations'. This study explores the use of INT8-based emulation for accelerating traditional FP64-based HPC workloads on modern GPU architectures... OpenAlex concept tags include "computer science, geology, cloud computing, artificial intelligence '.

c16: Public author profile is associated with University of Padua. 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 "microstructure, materials science, metallurgy, chemistry '.

c17: 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 '.

c18: Public author profile is associated with Wenshan University. 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, medicine, chemistry, artificial intelligence '.

c19: 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 "modular design, computer science, artificial intelligence, psychology '.

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: 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.

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 "mathematics, computer science, artificial intelligence, machine learning '.

c01: 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 "physics, computer science, artificial intelligence, statistical physics '.

c02: Public author profile is associated with Guangdong Food and Drug Vocational College. 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 "elevator, engineering, operating system, epistemology '.

c03:
[person] (@[person])

(hello) => there

Representative projects and topics: A repo for getting started with Prefect.; Production repository for the all-new Advantage360 Professional using ZMK engine; Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms, Tasks, Search & Drive with AI - Comprehensive Google Workspace / G Suite MCP Server; Excel-like grid component built with React, with editors, keyboard navigation, copy & paste, and the like; A MCP server for the Frankfurter API for currency exchange rates..

c04:
[person] (@[person]). base in Berlin, Germany; works with FastAPI Cloud.

Creator of FastAPI, Typer, SQLModel, Asyncer, etc. 🚀 From 🇨🇴 in 🇩🇪. Open Source, Python, APIs, AI. 🤖 Building FastAPI Cloud. ⚡

Representative projects and topics: FastAPI framework, high performance, easy to learn, fast to code, ready for production; Typer, build great CLIs. Easy to code. Based on Python type hints.; Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.; SQL databases in Python, designed for simplicity, compatibility, and robustness.; Asyncer, async and await, focused on developer experience.; Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀.

I'm a software developer from Colombia. 🇨🇴

I currently live in Berlin, Germany. 🇩🇪

I created ** FastAPI **, ** Typer **, ** SQLModel **, ** Asyncer **, and a bunch of other open source tools. 🚀

I'm normally doing things around Python, APIs, AI, and friends.

Now I'm also building FastAPI Cloud . ⚡

You can find me on:

My website: [person].com
GitHub as @[person] (you are here)

c05:
[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.

c07: 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, surgery, crystal structure, geomorphology '.

c08:
[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..

c09: Public author profile is associated with Indian Institute of Technology Kharagpur. Recent work in computational biology includes 'Pan-Cancer Mapping of the Tumor Immune Landscape through Metagene Clustering and Predictive Modeling'. As immunotherapies become standard cancer treatments, it is increasingly important to identify a patient's immune profile, which encompasses the activity of immune cells within the tumor microenvironment and the presence of specific biomarkers... OpenAlex concept tags include "computer science, mathematics, physics, artificial intelligence '.

c10:
[person] (@[person]). base in Schaumburg, IL; works with @PrefectHQ.

Software Engineer @PrefectHQ

Representative projects and topics: Prefect is a workflow orchestration framework for building resilient data pipelines in Python.; An experiment in distributed memoization; MCP server for delegating tasks to Devin AI; Generate MDX API documentation from Python modules; Test project for `include_files` feature with the `prefect-aws` `@ecs` decorator; 🫏 Add a stubborn streak to your code..

c11: Public author profile is associated with Council of Agriculture. Recent work in ai and machine learning includes 'Reward-Based Online LLM Routing via NeuralUCB'. This study investigates the use of NeuralUCB for cost-aware large language model (LLM) routing... OpenAlex concept tags include "irrigation, water resource management, environmental science, engineering '.

c12: Public author profile is associated with China Europe International Business School. 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 "psychology, social psychology, computer science, political science '.

c13: 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 '.

c14: Public author profile is associated with Massachusetts Institute of Technology. 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 "rna, biology, computational biology, gene '.

c15: Public author profile is associated with Exscien (United States). 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, graph, artificial intelligence, machine learning '.

c16: Public author profile is associated with Microsoft Research (United Kingdom). 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, artificial intelligence, machine learning, mathematics '.

c17:
[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.

c18: Public author profile is associated with Johns Hopkins University. 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, medicine, gene, cell biology '.

c19: 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 '.

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: 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.

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...

c01:
[person] (@[person]). base in Berlin, Germany; works with FastAPI Cloud.

Creator of FastAPI, Typer, SQLModel, Asyncer, etc. 🚀 From 🇨🇴 in 🇩🇪. Open Source, Python, APIs, AI. 🤖 Building FastAPI Cloud. ⚡

Representative projects and topics: FastAPI framework, high performance, easy to learn, fast to code, ready for production; Typer, build great CLIs. Easy to code. Based on Python type hints.; Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.; SQL databases in Python, designed for simplicity, compatibility, and robustness.; Asyncer, async and await, focused on developer experience.; Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀.

I'm a software developer from Colombia. 🇨🇴

I currently live in Berlin, Germany. 🇩🇪

I created ** FastAPI **, ** Typer **, ** SQLModel **, ** Asyncer **, and a bunch of other open source tools. 🚀

I'm normally doing things around Python, APIs, AI, and friends.

Now I'm also building FastAPI Cloud . ⚡

You can find me on:

My website: [person].com
GitHub as @[person] (you are here)

c02:
[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.

c03: Public author profile is associated with Utah Cancer Specialists. 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 "medicine, biology '.

c04: Public author profile is associated with Xiamen University. 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 "chemistry, materials science, condensed matter physics, physics '.

c05: Public author profile is associated with Alibaba Group (United States). 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 "computer science, artificial intelligence, physics, programming language '.

c06:
[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..

c07:
[person] (@[person]). base in Hamburg, Germany.

Indie product engineer who loves to build tools for developers.

Representative projects and topics: The infamous DuckDB quack extension rewritten in C and built with Zig; A Rust library to decrypt & encrypt any cheat code for CodeBreaker PS2; Serverless app to keep track of your Twitter followers and unfollowers; Enjoy Dilbert in your RSS feed reader without any ads; The fastest way to run Chef cookbooks; Shell library to test your tools like Git does.

c08: Public author profile is associated with Instituto de Recursos Naturales y Agrobiología de Sevilla. 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 "agronomy, chemistry, biology, horticulture '.

c09: Public author profile is associated with Gansu Agricultural University. 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 "medicine, chemistry, biology, internal medicine '.

c10: Public author profile is associated with Oak Ridge National Laboratory. 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 "computer science, mathematical optimization, physics, mathematics '.

c11:
[person] (@[person])

(hello) => there

Representative projects and topics: A repo for getting started with Prefect.; Production repository for the all-new Advantage360 Professional using ZMK engine; Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms, Tasks, Search & Drive with AI - Comprehensive Google Workspace / G Suite MCP Server; Excel-like grid component built with React, with editors, keyboard navigation, copy & paste, and the like; A MCP server for the Frankfurter API for currency exchange rates..

c12: Public author profile is associated with Technological University Dublin. Recent work in ai and machine learning includes 'Meteorology-Driven GPT4AP: A Multi-Task Forecasting LLM for Atmospheric Air Pollution in Data-Scarce Settings'. Accurate forecasting of air pollution is important for environmental monitoring and policy support, yet data-driven models often suffer from limited generalization in regions with sparse observations... OpenAlex concept tags include "computer science, artificial intelligence, machine learning, engineering '.

c13: 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 '.

c14: 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 '.

c15: Public author profile is associated with Imperial Valley College. 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 "computational biology, computer science, biology, chemistry '.

c16: Public author profile is associated with Folkwang University of the Arts. 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 "cosmic ray, physics, air shower, nuclear physics '.

c17: 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 '.

c18: 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 '.

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: YC batch W2023 founder at Depot. Role: Co-founder and CTO. Cofounder and CTO of Depot. US expat living in the UK.

c00: 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 '.

c01: Public author profile is associated with University of Michigan–Ann Arbor. Recent work in quantitative social science and economics includes 'The Problem of Dynamic Spatial Sampling and Geofence Surveillance'. Geofencing surveillance poses a dynamic spatial sampling problem... OpenAlex concept tags include "replication (statistics), computer science, environmental science, engineering '.

c02:
[person] (@[person]). base in Hamilton, Ontario; works with me.

I create courses that make learning things like JavaScript easy and fun 🔥

Representative projects and topics: Slam Dunk JavaScript; 30 Day Vanilla JS Challenge; Starter files for learning React.js with React for Beginners; Ask me anything!; Starter Files and Solutions for Full Stack Advanced React and GraphQL; dad jokes.

[person]

Waku website

Running Locally

`pnpm install` then `pnpm run dev`.

If it's your first time, you'll need to run `pnpm run db:migrate` to generate the schema for the hot tips posts data.

c03: Public author profile is associated with Wuhan University of Technology. 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 "psychology, computer science, social psychology, business '.

c04: Public author profile is associated with Indian Institute of Science Education and Research Kolkata. 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 "computer science, materials science, artificial intelligence, physics '.

c06: Public author profile is associated with University of Padua. 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 "microstructure, materials science, metallurgy, chemistry '.

c07: 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 '.

c08: Public author profile is associated with Oak Ridge National Laboratory. 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 "computer science, mathematical optimization, physics, mathematics '.

c09:
[person] (@[person]). base in San Francisco, CA; works with CEO @ Ping.gg.

I'm just here for the vibes, man

Representative projects and topics: The best way to start a full-stack, typesafe Next.js app; How to implement Stripe without going mad; File uploads for modern web devs; A fast, local-first "search engine" for !bang users; Export Twitch markers as a LosslessCut-compatible CSV; Turn SVGs into high resolution PNGs in 2 clicks.

Current Projects

Products

T3 Chat** — The only AI chat that doesn't suck
T3 Code** — A harness for your AI harnesses
UploadThing** — File uploads for modern web devs (5k+ stars)
QuickPic** — Turn SVGs into high resolution PNGs in 2 clicks (1.2k+ stars)
Unduck** — Fast, local-first search engine for !bang users (1.1k+ stars)
Ping.gg** — Zoom for streamers, built for OBS
PicThing** — Background removal and asset management for professional creators
Shoo** — Simple auth (coming soon)
Lawn** — Open source alternative to Frame.io

LLM Benchmarks & Shenanigans

SnitchBench** — Measuring which LLMs will snitch on you
Skatebench** — Measuring how well LLMs can name skateboard tricks
Quipslop** — Quiplash for LLMs, streaming on Twitch

Everything Else

T3 Stack** — Ushered in full stack typesafety with create-t3-app (28k+ stars)
Stripe Recommendations** — How to implement Stripe without going mad (6.2k+ stars)
Claude Blocker** — Block distracting apps when you don't have agents running
Soramarker** — Add Sora watermarks to any video [TRUNCATED]

c10:
[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.

c11: Public author profile is associated with NSF National Center for Atmospheric Research. 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 "physics, geology, computer science, mathematics '.

c12: Public author profile is associated with Exscien (United States). 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, graph, artificial intelligence, machine learning '.

c13: Public author profile is associated with Folkwang University of the Arts. 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 "cosmic ray, physics, air shower, nuclear physics '.

c14: Public author profile is associated with The University of Texas at Austin. 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 "computer science, mathematics, applied mathematics, mathematical analysis '.

c15:
[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.

c16:
[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.

c17:
[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

c18:
[person] (@[person]). base in Berlin, Germany; works with FastAPI Cloud.

Creator of FastAPI, Typer, SQLModel, Asyncer, etc. 🚀 From 🇨🇴 in 🇩🇪. Open Source, Python, APIs, AI. 🤖 Building FastAPI Cloud. ⚡

Representative projects and topics: FastAPI framework, high performance, easy to learn, fast to code, ready for production; Typer, build great CLIs. Easy to code. Based on Python type hints.; Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.; SQL databases in Python, designed for simplicity, compatibility, and robustness.; Asyncer, async and await, focused on developer experience.; Run and manage FastAPI apps from the command line with FastAPI CLI. 🚀.

I'm a software developer from Colombia. 🇨🇴

I currently live in Berlin, Germany. 🇩🇪

I created ** FastAPI **, ** Typer **, ** SQLModel **, ** Asyncer **, and a bunch of other open source tools. 🚀

I'm normally doing things around Python, APIs, AI, and friends.

Now I'm also building FastAPI Cloud . ⚡

You can find me on:

My website: [person].com
GitHub as @[person] (you are here)

c19: Public author profile is associated with Twitter (United States). Recent work in quantitative social science and economics includes 'Retrospective Economic Evaluation of Group Testing in the COVID-19 Pandemic'. Surveillance of diseases in a pandemic is an important part of public health policy... OpenAlex concept tags include "computer science, intuition, mathematical optimization, mathematics '.

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