Parallel associative reductions in halide. - Patricia Suriana; Andrew Adams; Shoaib Kamil 001 (CGO, 2017)

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code. - Riyadh Baghdadi; Jessica Ray; Malek Ben Romdhane; Emanuele Del Sozzo; Abdurrahman Akkas; Yunming Zhang; Patricia Suriana; Shoaib Kamil 001; Saman P. Amarasinghe (CGO, 2019)

End-to-End Learning on 3D Protein Structure for Interface Prediction. - Raphael J. L. Townshend; Rishi Bedi; Patricia Suriana; Ron O. Dror (NeurIPS, 2019)

Protein model quality assessment using rotation-equivariant, hierarchical neural networks. - Stephan Eismann; Patricia Suriana; Bowen Jing; Raphael J. L. Townshend; Ron O. Dror (CoRR, 2020)

ATOM3D: Tasks On Molecules in Three Dimensions. - Raphael J. L. Townshend; Martin Vögele; Patricia Suriana; Alexander Derry; Alexander S. Powers; Yianni Laloudakis; Sidhika Balachandar; Brandon M. Anderson; Stephan Eismann; Risi Kondor; Russ B. Altman; Ron O. Dror (CoRR, 2020)

Learning from Protein Structure with Geometric Vector Perceptrons. - Bowen Jing; Stephan Eismann; Patricia Suriana; Raphael John Lamarre Townshend; Ron O. Dror (ICLR, 2021)

ATOM3D: Tasks on Molecules in Three Dimensions. - Raphael J. L. Townshend; Martin Vögele; Patricia Suriana; Alexander Derry; Alexander S. Powers; Yianni Laloudakis; Sidhika Balachandar; Bowen Jing; Brandon M. Anderson; Stephan Eismann; Risi Kondor; Russ B. Altman; et al. (NeurIPS Datasets and Benchmarks, 2021)

FlexVDW: A machine learning approach to account for protein flexibility in ligand docking. - Patricia Suriana; Joseph M. Paggi; Ron O. Dror (CoRR, 2023)

Enhancing Ligand Pose Sampling for Molecular Docking. - Patricia Suriana; Ron O. Dror (CoRR, 2023)

Do we need equivariant models for molecule generation? - Ewa M. Nowara; Joshua Rackers; Patricia Suriana; Pan Kessel; Max Shen 002; Andrew Martin Watkins; Michael Maser (CoRR, 2025)