Scholar
Wenhao Gao
Google Scholar ID: s4eywrUAAAAJ
Chemical Engineering, MIT
Citations & Impact
Citations
3,850
H-index
15
i10-index
16
Publications
20
Co-authors
56
list available
Publications
Resume (English only)
Academic Achievements
- Publications:
- - Generative Artificial Intelligence for Navigating Synthesizable Chemical Space PNAS
- - Projecting Molecules into Synthesizable Chemical Spaces ICML 2024
- - Substrate Scope Contrastive Learning: Repurposing Human Bias to Learn Atomic Representations JACS
- - Closing the Execution Gap in Generative AI for Chemicals and Materials: Freeways or Safeguards An MIT Exploration of Generative AI
- - Scientific Discovery in the Age of Artificial Intelligence Nature
- Awards:
- - Google PhD Fellowship
- - Takeda Fellowship
- - CAS Future Leaders 2025
- - D. E. Shaw Research Fellow
- - Forbes 30 Under 30 Asia Honoree in Healthcare and Science
Research Experience
- 2020 - 2025 MIT Ph.D. Student in Chemical Engineering
- 2025 - 2026 Stanford University Postdoctoral Scholar in Chemistry and Computer Science
- June-August 2020 Los Alamos National Lab Machine Learning Scientist Intern in the Computer, Computational, and Statistical Sciences Division
Education
- 2014 - 2018 Peking University B.Sc. in Chemistry and Molecular Engineering
- 2018 - 2020 Johns Hopkins University M.S.E. in Chemical and Biomolecular Engineering
- 2020 - 2025 MIT Ph.D. in Chemical Engineering Advisor: Connor W. Coley
- 2025 - 2026 Stanford University Postdoctoral Scholar in Chemistry and Computer Science Advisors: Grant Rotskoff and Stefano Ermon
Background
- Research Interests: The intersection of chemistry and AI, particularly how AI can transform molecular discovery. His research focuses on building systematic methodologies for scalable, effective, and efficient molecular discovery, with applications in drug design and sustainable materials. The main approach is to integrate chemical and physical priors with modern computational techniques to enhance the modeling and design of molecules and materials with targeted functionalities, with a recent emphasis on AI and machine learning. He is also interested in applying these methods to real-world problems, including therapeutic discovery and sustainable chemistry.
Miscellany
- He will be joining the Department of Chemical and Biomolecular Engineering at the University of Pennsylvania as an Assistant Professor in January 2027 and will begin recruiting Ph.D. students from the December 2025 application cycle.
