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Patricia Suriana
Researcher, Prescient Design, Genentech
Joined
April 2021
Names
Patricia Suriana
(Preferred)
,
Patricia Adriana Suriana
,
Patricia A Suriana
Emails
****@stanford.edu
(Confirmed)
,
****@gene.com
(Confirmed)
,
****@gmail.com
(Confirmed)
Personal Links
Homepage
Google Scholar
Career & Education History
Researcher
Prescient Design,
Genentech
(gene.com)
2024
–
Present
PhD student
Stanford University
(stanford.edu)
2018
–
2024
MS student
Massachusetts Institute of Technology
(mit.edu)
2015
–
2016
Undergrad student
Massachusetts Institute of Technology
(mit.edu)
2010
–
2014
Advisors, Relations & Conflicts
PhD Advisor
Ron Dror
2019
–
2024
Expertise
deep learning
,
structural biology
,
computational drug design
Present
Publications
Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
Shriram Chennakesavalu
,
Kirill Shmilovich
,
Hayley Weir
,
Colin A Grambow
,
John Bradshaw
,
Patricia Suriana
,
Chen Cheng
,
Kangway V. Chuang
GenBio 2026 Poster
Readers:
Everyone
Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
Shriram Chennakesavalu
,
Kirill Shmilovich
,
Hayley Weir
,
Colin A Grambow
,
John Bradshaw
,
Patricia Suriana
,
Chen Cheng
,
Kangway V. Chuang
ICML2026-AI4Science Poster
Readers:
Everyone
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Miruna Cretu
,
John Bradshaw
,
Patricia Suriana
,
Saeed Saremi
,
Omar Mahmood
,
Kirill Shmilovich
,
Kangway V. Chuang
,
Vishnu Sresht
,
Colin A Grambow
GEM 2026
Readers:
Everyone
Do we need equivariant models for molecule generation?
Ewa Nowara
,
Joshua A Rackers
,
Patricia Suriana
,
Pan Kessel
,
Max W Shen
,
Andrew Martin Watkins
,
Michael Maser
OpenReview Archive Direct Upload
Readers:
Everyone
Beyond Atoms: Evaluating Electron Density Representation for 3D Molecular Learning
Patricia Adriana Suriana
,
Joshua A Rackers
,
Ewa Nowara
,
Pedro O. Pinheiro
,
Vishnu Sresht
,
John M Nicoludis
AI4D3 2025 Poster
Readers:
Everyone
Beyond Atoms: Evaluating Electron Density Representation for 3D Molecular Learning
Patricia Adriana Suriana
,
Joshua A Rackers
,
Ewa Nowara
,
Pedro O. Pinheiro
,
Vishnu Sresht
,
John M Nicoludis
NeurIPS2025-AI4Science Poster
Readers:
Everyone
Do we need equivariant models for molecule generation?
Ewa Nowara
,
Joshua A Rackers
,
Patricia Adriana Suriana
,
Pan Kessel
,
Max W Shen
,
Andrew Martin Watkins
,
Michael Maser
GenBio 2025 Poster
Readers:
Everyone
FlexVDW: A machine learning approach to account for protein flexibility in ligand docking
Patricia Adriana Suriana
,
Joseph M Paggi
,
Ron O. Dror
Published: 06 Mar 2023, Last Modified: 05 May 2023
ICLR 2023 - MLDD Poster
Readers:
Everyone
Fragment-based ligand generation guided by geometric deep learning on protein-ligand structures
Alexander S Powers
,
Helen H. Yu
,
Patricia Adriana Suriana
,
Ron O. Dror
Published: 05 Apr 2022, Last Modified: 05 May 2023
MLDD Poster
Readers:
Everyone
ATOM3D: Tasks on Molecules in Three Dimensions
Raphael John Lamarre Townshend
,
Martin Vögele
,
Patricia Adriana Suriana
,
Alexander Derry
,
Alexander Powers
,
Yianni Laloudakis
,
Sidhika Balachandar
,
Bowen Jing
,
Brandon M. Anderson
,
Stephan Eismann
,
Risi Kondor
,
Russ Altman
,
Ron O. Dror
Published: 29 Jul 2021, Last Modified: 26 May 2025
NeurIPS 2021 Datasets and Benchmarks Track (Round 1)
Readers:
Everyone
Co-Authors
Alexander Derry
Alexander Powers
Alexander S Powers
Andrew Martin Watkins
Bowen Jing
Brandon M. Anderson
Chen Cheng
Colin A Grambow
Ewa Nowara
Hayley Weir
Helen H. Yu
John Bradshaw
John M Nicoludis
Joseph M Paggi
Joshua A Rackers
Kangway V. Chuang
Kirill Shmilovich
Martin Vögele
Max W Shen
Michael Maser
Miruna Cretu
Omar Mahmood
Pan Kessel
Pedro O. Pinheiro
Raphael John Lamarre Townshend
View all 34 co-authors