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@AI4Science-WestlakeU

AI for Scientific Simulation and Discovery Lab

Our lab's research solves the core and universal problems at the intersection of AI and science

AI for Scientific Simulation and Discovery Lab

Our research group at Westlake University (西湖大学) carries out long-term work on core and universal problems for AI + Science:

  • Core AI: Develop generative AI methods based on diffusion/flow matching and next-generation generative models; create self-evolving AI architectures. Develop generalist AI scientists and AI engineers.
  • AI for Physical Sciences: Develop novel generative AI approaches for scientific simulation, control, design, and scientific discovery in complex physical systems such as fluids and plasmas.
  • AI for Life Science: Develop AI virtual cells and decode the evolutionary mechanisms and intrinsic logic of living systems.

Group website: ai4s.lab.westlake.edu.cn
Group Leader website: tailin.org

Popular repositories Loading

  1. RealPDEBench RealPDEBench Public

    [🔥ICLR26 Oral] RealPDEBench: A Benchmark for Complex Physical Systems with Paired Real-World and Simulated Data

    Python 134 17

  2. flow_guidance flow_guidance Public

    [ICML 2025] The official implementation of the paper "On the Guidance of Flow Matching"

    Python 109 10

  3. BuildArena BuildArena Public

    [ICML 2026] BuildArena, where LLM agents design, build, and test rockets, cars, and bridges in a physics simulator given a goal-directed sentence.

    Python 107 6

  4. wdno wdno Public

    [ICLR 2025] Wavelet Diffusion Neural Operator (WDNO) uses diffusion models on wavelet space for generative PDE simulation and control.

    Python 68 2

  5. scDFM scDFM Public

    [ICLR 2026] scDFM: Distributional Flow Matching for Robust Single-Cell Perturbation Prediction

    Python 65 8

  6. research_toolbox research_toolbox Public

    A useful toolbox for research.

    59 3

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