Recent Talks and Lectures:
- Accelerating Molecular Discovery from a Data-driven Computational Perspective
- @ACS Generative Modeling for Chem, Bio & Material Symposium, March 2025
- @Princeton AI^2 Research Talk Series, Jan 2025
- @UCLA Modern computation: AI + Quantum (Guest Lecture), Oct 2024
- @UT Austin Henkelman Group (Chemistry), Oct 2024
- @MIT Kulik’s Group (Chemical Engineering), August 2024
- @Microsoft Research AI4Science Colloquium, June 2024
- @Stanford Theoretical Chemistry Group, June 2024
- @Gatech Applied and Comp. Mathematics Seminar, April 2024
- Accelerating Transition Dynamics Simulation with Probabilistic Machine Learning
- @ACS Inferring Kinetics, Thermodynamics, and Mechanisms from Sampling Symposium, March 2025
- @NYU Courant Generative Model/Sampling Seminar, Nov 2024
- @UCB BIDMaP Young Scholar Seminar, Nov 2024
- @SIAM New York-New Jersey-Pennsylvania Section Annual Conference, Nov 2024
- @IAIFI Summer Workshop, August 2024
- Language Model-based Design Programs for Chemical Synthesis and Design
- @ACS Machine Learning in Chemistry Symposium, March 2025
- Recent Advances of Machine Learning in Molecular Discovery: From Representation, Simulation to Inverse Design
- @Cornell Deep Learning (SYSEN 6888) guest lecture, Nov 2023
- Scientific Discovery in the era of Artificial Intelligence
- @Cornell Luo Lab (Integrative Plant Science), Sep 2023
- @Cornell CS Grad Seminar, Oct 2022
- Machine Learning for Molecular Discovery: From One Distribution to Two
- Structure-based Drug Design with Equivariant Diffusion Models
- @Cornell Yu Lab (Computational Biology), Nov 2022
