One of the original inventors of Generative Flow Networks.

Lead 20+ person drug discovery team at Mila.

Ph.D. with Yoshua Bengio.

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Alex is a postdoctoral researcher at Mila in Montreal, where he works with Yoshua Bengio on the causal discovery of cell dynamics.

Alex earned his Ph.D. from the Computer Science Department at Yale University in 2021, under the guidance of Smita Krishnaswamy where he studied optimal transport, graph signal processing, and generative modeling of cell dynamics and perturbations. His research interests span generative modeling, deep learning, and optimal transport applied to problems in biology.

Jarrid is a generative AI expert working on diffusion, flow matching, and generative flow networks.

Ph.D. in generative models with Yoshua.

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Chenghao works at the intersection of generative algorithms and molecular design. Prior to Dreamfold, Chenghao has designed and tested hundreds of molecules/polymers in the wet lab, including de novo designs generated from his own algorithms.

He did his Ph.D. at McGill University and Mila with Dima Perepichka and Yoshua Bengio. He has been awarded the prestigious Vanier scholarship.

DeepMind Professor of AI at Oxford, Former Head of Graph ML Research at Twitter, founder of multiple successful startups, author of major contributions to the field of geometric deep learning for protein design. Michael is an avid opera fan.

Joey is a Machine Learning scientist at DreamFold and a Post-Doctoral Fellow at the University of Oxford working with Michael Bronstein.

He completed his PhD at McGill/Mila under the supervision of Will Hamilton, Gauthier Gidel, and Prakash Panagaden. His research interests span Generative Modelling, and Differential Geometry for Machine Learning with a current emphasis on understanding symmetries, equivariances and invariances in data. Previously, he completed his Bachelors and Master’s degrees from the University of Toronto working on adversarial attacks against face detection and is the President and CEO of FaceShield Inc. an educational platform for digital privacy for facial data.

His work has been featured in Forbes, CBC, VentureBeat and other media outlets and is generously supported by the IVADO PhD Fellowship.

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Guillaume develops mathematical foundations for manifold learning (including generative models). His recent publications concern cutting-edge generative algorithms such as Flow Matching and Schrödinger Bridges.

Guillaume is a fourth-year PhD candidate at Mila, specializing in generative AI. He focuses his research on manifold learning, optimal transport, and dynamic models. Actively contributing to computational biology projects, particularly in the realms of protein design and single-cell analysis. Prior to his PhD, he worked on piecewise deterministic Markov processes for Monte Carlo methods.

Before DreamFold, James worked with Microsoft for nearly 5 years, most recently as an Applied Scientist in the Turing team working on LLMs and web-scale chatbots. Prior to Microsoft, James was a founding Quantitative Analyst for a Toronto-based hedge fund.

James obtained a Bachelors of Engineering in Mathematics and Engineering from Queen's University

Kilian is a machine learning research scientist. His research focuses on generative models for protein backbone generation. Before joining DreamFold, he was a postdoctoral fellow at Mila and McGill University where he worked on distribution shifts, generative modelling and optimal transport.

Kilian holds a PhD from IRISA-INRIA (France). His research focused on the interaction of optimal transport and deep learning, especially on the use of minibatch optimal transport in deep learning applications.

Pablo’s research interests are in generative modelling, Bayesian Machine learning, and Markov Chain Monte Carlo. Pablo has a PhD in cosmology from the University of Cambridge. He has led working groups at various large astronomical collaborations, and has co-authored several influential works at the intersection of machine learning and cosmology. During his free time, he mostly plays and watches football (soccer, not the American one!)

Steve is an expert in protein engineering with over 20 years of experience in the design and development of antibody, cytokine, and fusion protein drugs. After receiving a PhD in Cell Biology at Johns Hopkins University School of Medicine and postdoctoral training at UC Berkeley, he held positions at successful biotech companies including Director Cell Biology at Exelixis and was VP Research at Xencor, FivePrime Therapeutics, and Xoma. He most recently served as Chief R&D Officer at Nektar Therapeutics and is now an independent consultant to the biotechnology industry. Steve sits on the Board of Directors of Forte Biosciences, and the Biotechnology Advisory Board of the University of Delaware.