Sotabase

Career

· Founder & CEO, Atomic AI2021–
· Research Intern, DeepMind2019–2019
· Head TA - CS229, Stanford University2018–2018
· Intern, Google2014–2014
· PhD Fellow, Stanford University2014–2020
· PhD in Computer Science, Stanford University2014–2020
· Undergraduate Student Instructor, University of California, Berkeley2012–2012
· Undergradute Research Assistant, University of California, Berkeley2012–2014
· Root Staff Member and Director, University of California, Berkeley2011–2014
· BS in Electrical Engineering and Computer Science, University of California, Berkeley2010–2014

Publications (33)

Learning from Protein Structure with Geometric Vector Perceptrons
International Conference on Learning Representations · 2020
595
cited
Geometric deep learning of RNA structure
Science · 2021
314
cited
Molecular mechanism of GPCR-mediated arrestin activation
Nature · 2018
171
cited
ATOM3D: Tasks On Molecules in Three Dimensions
NeurIPS Datasets and Benchmarks · 2020
154
cited
Simple biochemical features underlie transcriptional activation domain diversity and dynamic, fuzzy binding to Mediator
bioRxiv · 2020
138
cited
How GPCR Phosphorylation Patterns Orchestrate Arrestin-Mediated Signaling
Cell · 2020
128
cited
End-to-End Learning on 3D Protein Structure for Interface Prediction
Neural Information Processing Systems · 2018
114
cited
Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes
Proteins: Structure, Function, and Bioinformatics · 2020
64
cited
RNA-Puzzles Round V: blind predictions of 23 RNA structures
Nature Methods · 2024
35
cited
User-Driven Geolocation of Untagged Desert Imagery Using Digital Elevation Models
2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops · 2013
32
cited
ATOM-1: A Foundation Model for RNA Structure and Function Built on Chemical Mapping Data
bioRxiv · 2023
13
cited
Protein model quality assessment using rotation-equivariant, hierarchical neural networks
arXiv.org · 2020
13
cited
Geometric Prediction: Moving Beyond Scalars
arXiv.org · 2020
9
cited
Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes
arXiv.org · 2020
8
cited
Generalizable Protein Interface Prediction with End-to-End Learning
arXiv.org · 2018
5
cited
Protein model quality assessment using rotation‐equivariant transformations on point clouds
Proteins: Structure, Function, and Bioinformatics · 2023
4
cited
Gold nanoparticles and tilt pairs to assess protein flexibility by cryo-electron microscopy.
Ultramicroscopy · 2021
3
cited
ARES-specific adaptation of E3NN
2021
1
cited
ATOM3D: Ligand Binding Affinity (LBA) Dataset
2021
1
cited
Euclidean Transformers for Macromolecular Structures: Lessons Learned
2022
1
cited
Sotabase
Raphael Townshend | Researcher Profile | Sotabase | Sotabase