Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators. - Jenna A. Bilbrey; Kristina M. Herman; Henry Sprueill; Sotiris S. Xantheas; Payel Das; Manuel Lopez Roldan; Mike Kraus; Hatem Helal; Sutanay Choudhury (CoRR, 2022)

Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Design. - Henry Sprueill; Carl Edwards; Mariefel V. Olarte; Udishnu Sanyal; Heng Ji; Sutanay Choudhury (EMNLP (Findings), 2023)

CHEMREASONER: Heuristic Search over a Large Language Model's Knowledge Space using Quantum-Chemical Feedback. - Henry W. Sprueill; Carl Edwards; Khushbu Agarwal; Mariefel V. Olarte; Udishnu Sanyal; Conrad Johnston; Hongbin Liu; Heng Ji; Sutanay Choudhury (ICML, 2024)

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units. - Hatem Helal; Jesun Firoz; Jenna A. Bilbrey; Henry Sprueill; Kristina M. Herman; Mario Michael Krell; Tom Murray; Manuel Lopez Roldan; Mike Kraus; Ang Li 006; Payel Das; Sotiris S. Xantheas; et al. (J. Chem. Inf. Model., 2024)

Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE. - Jesun Firoz; Franco Pellegrini; Mario Geiger; Darren Hsu; Jenna A. Bilbrey; Han-Yi Chou; Maximilian Stadler; Markus Hoehnerbach; Tingyu Wang; Dejun Lin; Emine Küçükbenli; Henry W. Sprueill; et al. (CoRR, 2025)