Mengchen Wang

PhD Student @ Stanford CS. B.E. @ Tsinghua IIIS (Yao Class)

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(+1) 6505615108

wmc@stanford.edu

Hi I am Mengchen, a first-year PhD Computer Science Ph.D. student at Stanford University specializing in AI4Science. I received my Bachelor of Engineering from Tsinghua University’s Institute for Interdisciplinary Information Science (Yao Class). My overarching goal is to identify complex biological bottlenecks and engineer the precise machine learning architectures required to solve them.

Currently, my research centers on spatial transcriptomics, where I model the continuous-time dynamics of embryogenesis and transcription regulation using advanced representation learning, optimal transport, and transformer-based multi-modal foundation models.

Beyond biology, I have a strong algorithmic foundation in developing explainable AI pipelines and integrating foundation models with reinforcement learning for embodied agents and nanorobotic swarms. Whether analyzing spatial-temporal gene expression or optimizing complex control systems, I focus on translating high-dimensional, multi-modal data into actionable scientific insights.

News

Dec 21, 2025 Check our 3D embryo website Here! We provide an easy way to interact with out analysis results. Our paper will be coming out soon :rocket:.

Selected Publications

  1. microrobot.jpg
    Artificial intelligence-assisted multimode microrobot swarm behaviors
    Xuanjie Xia, Miao Ni, Mengchen Wang, and 3 more authors
    ACS nano, 2025
  2. hydrogel.jpg
    Spatiotemporally actuated hydrogel by magnetic swarm nanorobotics
    Bin Wang, Dong Liu, Yuting Liao, and 6 more authors
    ACS nano, 2022
  3. nanochains.jpg
    Photothermally modulated magnetic nanochains as swarm nanorobotics for microreaction control
    Yuting Liao, Dong Liu, Bin Wang, and 5 more authors
    ACS Applied Nano Materials, 2022
  4. CoRL
    Reinforcement Learning with Foundation Priors: Let Embodied Agent Efficiently Learn on Its Own
    Weirui Ye, Yunsheng Zhang, Haoyang Weng, and 6 more authors
    In 8th Annual Conference on Robot Learning, 2024
  5. arXiv
    Foundation reinforcement learning: towards embodied generalist agents with foundation prior assistance
    Weirui Ye, Yunsheng Zhang, Mengchen Wang, and 4 more authors
    arXiv preprint arXiv:2310.02635, 2023