I'm an third-year PhD student at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) co-advised by Tommi Jaakkola and Regina Barzilay. My research focuses on developing novel ML frameworks to tackle challenging problems in structural biology and drug discovery.
I did my Bachelor at the University of Cambridge where I wrote my thesis under the supervision of Pietro Lió and Jure Leskovec. Previously, I interned at Twitter Research, D.E. Shaw and Alchera Technologies as a machine learning researcher and at IBM and STMicroelectronics as a software engineer.
I am also part of the core team and mentor at LeadTheFuture, a nonprofit organization helping talented Italian university and high school students reach their potential. I'm currently serving as Program Chair and organizer of the Machine Learning for Structural Biology (MLSB) workshop at NeurIPS and organizer of the Molecular Machine Learning (MoML) conference at MIT.
Most recent publications on Google Scholar.
‡ indicates equal contribution.
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Gabriele Corso‡, Hannes Stärk‡, Bowen Jing‡, Regina Barzilay, Tommi Jaakkola
ICLR 2023 and Best Student Paper Award at the NeurIPS 2022 Score-Based Modeling workshop.
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Benjamin Fry, Nicholas Polizzi, Regina Barzilay, Tommi Jaakkola
ICLR 2024.
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso, Yilun Xu, Valentin de Bortoli, Regina Barzilay, Tommi Jaakkola
ICLR 2024.
Torsional Diffusion for Molecular Conformer Generation
Bowen Jing‡, Gabriele Corso‡, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola
NeurIPS 2022. Oral presentation.
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso‡, Luca Cavalleri‡, Dominique Beaini, Pietro Liò, Petar Veličković
NeurIPS 2020.
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Gabriele Corso‡, Hannes Stärk‡, Bowen Jing‡, Regina Barzilay, Tommi Jaakkola
ICLR 2023 and Best Student Paper Award at the NeurIPS 2022 Score-Based Modeling workshop.
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents
Yilun Xu, Gabriele Corso, Tommi Jaakkola, Arash Vahdat, Karsten Kreis
ICML 2024.
Dirichlet Flow Matching with Applications to DNA Sequence Design
Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi Jaakkola
ICML 2024.
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Benjamin Fry, Nicholas Polizzi, Regina Barzilay, Tommi Jaakkola
ICLR 2024.
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso, Yilun Xu, Valentin de Bortoli, Regina Barzilay, Tommi Jaakkola
ICLR 2024.
Graph neural networks
Gabriele Corso, Hannes Stärk, Stefanie Jegelka, Regina Barzilay, Tommi Jaakkola
Nature Reviews Methods Primers 2024.
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models
Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stärk, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola
ICLR MLDD workshop 2023.
EigenFold: Generative Protein Structure Prediction with Diffusion Models
Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi Jaakkola
ICLR MLDD workshop 2023.
Modeling Molecular Structures with Intrinsic Diffusion Models
Gabriele Corso
MIT Master's Thesis.
Torsional Diffusion for Molecular Conformer Generation
Bowen Jing‡, Gabriele Corso‡, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola
NeurIPS 2022. Oral presentation.
Subspace Diffusion Generative Models
Bowen Jing‡, Gabriele Corso‡, Renato Berlinghieri, Tommi Jaakkola
ECCV 2022.
Graph Anisotropic Diffusion
Ahmed A. A. Elhag, Gabriele Corso, Hannes Stärk, Michael M. Bronstein
ICLR 2022 Workshop on Geometrical and Topological Representation Learning.
3D Infomax improves GNNs for Molecular Property Prediction
Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Liò
ICML 2022.
Learning Graph Search Heuristics
Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Veličković, Zhitao Ying, Jure Leskovec, Pietro Lio
LoG 2022.
Neural Distance Embeddings for Biological Sequences
Gabriele Corso, Rex Ying, Michal Pándy, Petar Veličković, Jure Leskovec, Pietro Liò
NeurIPS 2021.
Directional Graph Networks
Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò
ICML 2021. Oral presentation.
Principal Neighbourhood Aggregation for Graph Nets
Gabriele Corso‡, Luca Cavalleri‡, Dominique Beaini, Pietro Liò, Petar Veličković
NeurIPS 2020.