Machine Learning in Structural Biology

Regina Barzilay is a Delta Electronics Professor in MIT’s Department of Electrical Engineering and Computer Science and a faculty lead for the MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic). She is also a principal investigator at the Computer Science and Artificial Intelligence Laboratory. Barzilay’s research interests are in natural language processing, and applications of deep learning to chemistry and oncology. Her research focuses on developing deep learning models that can transfer annotations across domains and languages, that can learn from a few annotated examples by utilizing supplementary data sources, and that can take advantage of human-provided rationales to constrain model structure. Barzilay has received an NSF Career Award, MIT Technology Review’s TR-35 Award, and Microsoft Faculty Fellowship. She has also received fellowships from the MacArthur Foundation, Association for Computational Linguistics and Association for the Advancement of Artificial Intelligence. She received a PhD in computer science from Columbia University, and was a postdoc at Cornell University.

Michael Bronstein joined the Department of Computing as Professor in 2018. He has served as a professor at USI Lugano, Switzerland since 2010 and held visiting positions at Stanford, Harvard, MIT, TUM, and Tel Aviv University. Michael received his PhD with distinction from the Technion (Israel Institute of Technology) in 2007. His main expertise is in theoretical and computational geometric methods for machine learning and data science, and his research encompasses a broad spectrum of applications ranging from computer vision and pattern recognition to geometry processing, computer graphics, and biomedicine. Michael has authored over 200 papers, a book, and holds over 35 granted patents. He was awarded five ERC grants, two Google Faculty Research awards, two Amazon ML Research awards, Facebook Computational Social Science award, Dalle Molle prize, Royal Society Wolfson Merit award, and Royal Academy of Engineering Silver Medal. He is a PI and ML Lead in Project CETI, a TED Audacious Prize winning collaboration aimed at understanding the communication of sperm whales. During 2017-2018 he was a fellow at the Radcliffe Institute for Advanced Study at Harvard University and since 2017, he is a Rudolf Diesel fellow at TU Munich. He was invited as a Young Scientist to the World Economic Forum, an honour bestowed on forty world’s leading scientists under the age of forty. Michael is a Member of Academia Europaea, Fellow of IEEE, IAPR, ELLIS, and BCS, alumnus of the Technion Excellence Program and the Academy of Achievement, and ACM Distinguished Speaker. In addition to academic work, Michael's industrial experience includes technological leadership in multiple startup companies, including Novafora, Videocites, Invision (acquired by Intel in 2012), and Fabula AI (acquired by Twitter in 2019). Following the acquisition of Fabula, he joined Twitter as Head of Graph Learning Research. He previously served as Principal Engineer at Intel Perceptual Computing (2012-2019) and was one of the key developers of the Intel RealSense 3D camera technology. He is also an angel investor and supporter of multiple early-stage startups.

Cecilia Clementi is an Italian-American scientist who specialises in the simulation of biomolecules. She is a Professor of Computational Biophysics at the Free University of Berlin. She was previously a Professor of Chemistry at the Rice University and co-director of the National Science Foundation Molecular Sciences Software Institute. From 2017 to 2019 she held an Einstein Foundation fellowship.

Lucy is a research scientist at Google Research who works closely with colleagues from GAS and Brain to better understand the relationship between the sequence and function of biological macromolecules. Her broader research interests involve understanding how Google's strengths in experimental design and machine learning can be applied to the discovery and production of proteins for use in a diverse range of applications.

A Professor of Biology and Biological Engineering at the Massachusetts Institute of Technology (MIT), Keating’s research involves working to understand how protein sequences and structures encode interaction specificity. Her lab uses computational and experimental methods to measure protein interactions in high throughput, predict new interactions, and design proteins and peptides with novel interaction properties.

Derek Lowe is a medicinal chemist working on preclinical drug discovery in the pharmaceutical industry. Lowe has published a blog about this field, "In the Pipeline", since 2002 and is a columnist for the Royal Society of Chemistry's Chemistry World.