Tony Shen

prof_pic_tony.JPG

School of Computing Science

Simon Fraser University

Burnaby, BC, Canada

I am a PhD student in Computing Science at Simon Fraser University, supervised by Dr. Martin Ester. My research focuses on structure-based drug design with generative flow networks and flow matching models.

Currently, I am also a visiting researcher at Northeastern University and Broad Institute of MIT and Harvard, where I work on foundation models for bio-molecular generation and antibiotics discovery applications under the supervision of Dr. Wengong Jin.

Previously, I worked as a Machine Learning Consultant at Transcripta Bio, where I conducted experiments on generative models and large scale virtual screening. Before that, I interned at Recursion, developing the map of Biology and Google, working on AI models for search.

Research Interests

My research is centered around AI for Drug Discovery, with a specific focus on:

  • Foundation models for bio-molecular generation
  • Generative Flow Networks (GFlowNets)
  • Flow Matching and Diffusion Models
  • Structure-based drug design

news

May 01, 2025 Our paper “Compositional Flows for 3D Molecule and Synthesis Pathway Co-design” has been accepted at ICML 2025. See you in Vancouver 🇨🇦!
Mar 05, 2025 Our paper “Compositional Flows for 3D Molecule and Synthesis Pathway Co-design” has been selected as oral presentation at GEM and AI4MAT workshops at ICLR 2025!
Jan 22, 2025 Our paper “Generative Flows on Synthetic Pathway for Drug Design” has been accepted at ICLR 2025 in Singapore 🇸🇬!
Sep 03, 2024 Our paper “TacoGFN: Target Conditioned GFlowNet for Structure-based Drug Design” has been accepted at TMLR!
Oct 27, 2023 Our paper “TacoGFN: Target Conditioned GFlowNet for Drug Design” has been accepted as a spotlight at the GenBio workshop and as a poster at the AI4D3 workshop at NeurIPS 2023!

selected publications

  1. ICML
    Compositional Flows for 3D Molecule and Synthesis Pathway Co-design
    Tony Shen*, Seonghwan Seo*, Ross Irwin, and 4 more authors
    International Conference on Machine Learning (ICML), 2025
  2. ICLR
    Generative Flows on Synthetic Pathway for Drug Design
    Seonghwan Seo, Minsu Kim, Tony Shen, and 4 more authors
    International Conference on Learning Representations (ICLR), 2025
  3. TMLR
    TacoGFN: Target Conditioned GFlowNet for Structure-Based Drug Design
    Tony Shen, Seonghwan Seo, Grayson Lee, and 5 more authors
    Transactions on Machine Learning Research (TMLR), 2024