01 /AI4SCIENCE
HACKATHON 2027

YaleSciHack

January 29–February 1, 2027 · New Haven, USA

Apply to participate Discuss a partnership In preparation
Academic sponsors
  • Yale Ventures
Industry sponsors
Explore SciHack
02 /Definition

What is SciHack?

Yale SciHack is an AI for Science hackathon. Students, researchers, and developers use AI to investigate scientific questions or build research tools.

150
Participant tickets
$25,000
Expected total prize pool
4days
Planned schedule · Monday optional
03 /

Directions

Research themes

  1. AI in the physical world

    Explore how AI senses and interacts with physical systems.

  2. Modeling and simulation

    Use models to understand and explore scientific systems.

  3. Scientific knowledge

    Use AI to organize, connect, and interpret scientific knowledge.

  4. Research data

    Improve how scientific data is collected, organized, and used.

  5. Efficient AI and computing

    Make scientific computing and AI more efficient.

Submission tracks

Academic research

Use AI to investigate a scientific question and produce a result others can test.

Research tools

Build a tool, dataset, or workflow that makes research easier.

Submissions and review

Describe data sources, methods, experiments or evaluation, limitations and next steps. Detailed requirements and evaluation criteria will be published with the challenges.

Choose a question

Work on a researcher-proposed challenge or pose your own scientific question within a track.

What to submit

Submissions may include working papers, solutions, proofs, models, simulations or research tools.

Validate results

Support conclusions through benchmarks, baseline comparisons, proof checks or expert review, as appropriate to the question.

04 /FACULTY · Academic Guests

Featured speakers

Ruzica PiskacYale Engineering
Opening Speaker · Formal Methods

Ruzica Piskac

Zhan Tianyou Professor of Computer Science
Chair, Department of Computer Science
Yale University

Yale profile (opens in a new tab)
Research details

PyDex co-author
soid co-author

Develops formal methods for dependable software and AI, with work on automated reasoning, verification and program synthesis.

01 / PROGRAM REPAIR

PyDex

Co-authored a system that uses a large language model to repair syntax and logic errors in introductory Python assignments. Published at OOPSLA 2024.

Original paper (opens in a new tab)
02 / AUTOMATED REASONING

soid

Co-authored a tool that uses automated reasoning to investigate how autonomous agents acted and how their decisions could change under different conditions. CAV 2024.

Original paper (opens in a new tab)
Lu LuPhoto: Wu Tsai Institute, Yale University
Keynote · Scientific Machine Learning

Lu Lu

Assistant Professor
Department of Statistics and Data Science
Yale University

Yale profile (opens in a new tab)
Research details

Co-creator of DeepONet
Developer of DeepXDE

His research focuses on scientific machine learning (SciML) and AI4Science, connecting deep learning, physical laws and scientific computing.

01 / OPERATOR LEARNING

DeepONet

Co-introduced deep operator networks that learn mappings between functions. Published in Nature Machine Intelligence (2021).

Original paper (opens in a new tab)
02 / SCIENTIFIC MACHINE LEARNING

DeepXDE

Develops and maintains an open-source scientific machine learning library for physics-informed learning and solving differential equations.

Project team (opens in a new tab)
05 /

Track Judges

Lucila Ohno-Machado

Lucila Ohno-Machado

Biomedical Informatics
Research details

Deputy Dean for Biomedical Informatics
Chair, Department of Biomedical Informatics and Data Science
Yale School of Medicine

Research on machine-learning prediction models and privacy-preserving federated methods that let hospitals analyze clinical data together without moving it.

Yale profile (opens in a new tab)

Yale School of Medicine

Hua Xu

Hua Xu

Clinical NLP
Research details

Professor of Biomedical Informatics and Data Science
Associate Dean for Biomedical Informatics
Yale School of Medicine

Studies clinical natural language processing, large language models and AI agents for clinical care and biomedical research.

Yale profile (opens in a new tab)

Yale School of Medicine

Luciano V. Del Priore

Luciano V. Del Priore

Ophthalmology
Research details

Robert R. Young Professor of Ophthalmology and Visual Science
Chair of Ophthalmology
Yale School of Medicine

Studies retinal degeneration, cell-based therapies and statistical models of disease progression.

Yale profile (opens in a new tab)

Yale School of Medicine

Jose Gomez Villalobos

Jose Gomez Villalobos

Pulmonary Medicine
Research details

Associate Professor of Medicine
Director of Precision Pulmonary Medicine (P2MED)
Yale School of Medicine

Combines computational biology, genomics and statistical methods to study asthma and other lung diseases.

Yale profile (opens in a new tab)

Yale School of Medicine

Owen Miller

Owen Miller

Nanophotonics
Research details

Associate Professor of Applied Physics
Yale University

Research combining large-scale computational optimization (inverse design) with theory to design nanoscale photonic devices and find the fundamental limits of their performance.

Yale profile (opens in a new tab)

Yale Engineering

Yu He

Yu He

Quantum Materials
Research details

Assistant Professor of Applied Physics
Yale University

Uses photoemission spectroscopy and X-ray scattering to investigate correlated electrons and functional quantum materials.

Yale profile (opens in a new tab)

Yale Engineering

06 /SCHEDULE · Schedule

Four days
from questions to results.

Friday–Sunday are the core days, with final submissions on Sunday. Monday is optional. This is a draft schedule; final arrangements will be announced.

  1. 01

    Define questions
    form teams

    Opening, talks, challenge announcements and team formation. Define your research question.

  2. 02

    Research
    build prototypes

    Research, experiments and prototype development.

  3. 03

    Submit
    begin review

    Finalize results and presentation materials, then submit your work. Review begins.

  4. 04

    Present projects
    exchange ideas

    Results, project presentations, open workshops and discussions.Optional

07 /

Take part in SciHack

Apply as an individual or as a team.

Apply to participate Apply without signing in. Join the organizing team See the open roles and how to apply.
08 /

Partner with SciHack

Research institutions, companies and communities are welcome to contribute challenges, technical support, campus outreach and event organization.

Discuss a partnership

Research collaboration

Contribute scientific questions, research materials, methodological guidance or expert review.

Technical resources

Support models, APIs, computing resources, research software and development tools.

Community and operations

Connect university and technical communities. Help with recruitment, outreach and on-site organization.

Sponsorship

Support prizes, participant services and event delivery.