AI in chemistry and beyond : Highlights in the field (ChE-605)

The Machine Learning Seminars are organized by Prof. Clémence Corminboeuf, Prof. Berend Smit and Prof. Philipp Schwaller, the seminars usually take place on Tuesdays at 15:15. Unless indicated otherwise, the lecture takes place on Zoom.

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PAST SEMINARS

"AI in chemistry and beyond" seminar "AI4Science at Microsoft Research" by Rianne van den Berg

20-12-202220-12-2022

With: Rianne van den Berg is a Principal Researcher at MSR. 
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"AI in chemistry and beyond: Highlights in the field" seminar "Deep learning for photochemical reaction discovery and targeted molecular design" by Julia Westermayr

06-12-202206-12-2022

With: Julia Westermayr is an Assistant Professor at the University of Leipzig.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Geemi Wellawatte: "Model Agnostic Counterfactual Explanations for Molecular Property Predictions"

22-11-202222-11-2022

With: Geemi Wellawatte is a PhD student at the University of Rochester, NY, with Prof. Andrew White. She completed her BSc. in Computational Chemistry in 2017 at the University of Colombo Sri Lanka. Her research work focuses on developing computational models to solve chemistry problems, particularly in coarse-grained modeling, deep learning in chemistry, and explainable AI.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Rocío Mercado "Exploring new frontiers in drug discovery using deep generative models"

08-11-202208-11-2022

With: Rocío Mercado is currently a post-doc at MIT working with Professor Connor Coley.  Previously, she completed an industrial post-doc at AstraZeneca in the Molecular AI team where she worked on graph molecular generative models for small molecule drug design. Before that, she completed a PhD in Chemistry with Professor Berend Smit at UC Berkeley and EPFL in molecular simulation. Rocío will be starting an assistant professorship at Chalmers University of Technology in the Data Science and AI division working on data-driven molecular design.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Anirudh Nambiar "Bayesian Reaction Optimization on a Robotic Flow Synthesis Platform"

25-10-202225-10-2022

With: Anirudh Nambiar is a Senior Engineer in the Synthetics Process Development Department at Amgen in Cambridge, Massachusetts. He completed his PhD in Chemical Engineering at MIT working with Klavs Jensen where he developed robotic flow synthesis platforms equipped with decision-making algorithms to optimise reaction outcomes.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Gabe Gomes "Machine-Guided Catalyst Optimization"

27-09-202227-09-2022

With: Gabe is an assistant professor at the departments of Chemistry and Chemical Engineering at Carnegie Mellon University, in Pittsburgh, USA. Gabe was born and raised in the countryside of the state of Rio de Janeiro, Brazil, where he received his B.Sc. He earned his Ph.D. in Fall 2018 from Florida State University, where he was awarded the LASER Fellowship in 2014 and the 2016-2017 IBM Ph.D Scholarship. At FSU, Gabe’s research was centered on the relationship between molecular structure and reactivity, focusing on the development and applications of stereoelectronic effects. For his work at FSU, in 2018, Gabe received several awards for his work in computational chemistry, including his selection for the CAS SciFinder Future Leaders Program. In 2019, Gabe joined the University of Toronto as a Postdoctoral Research Fellow in the Matter Lab, led by Professor Alán Aspuru-Guzik. In 2020, Gabe was awarded the prestigious NSERC Banting Postdoctoral Fellowship with the project “Designing Catalysts with Artificial Intelligence,” and has been featured on the “Next Great Impossible” series by Merck/Milipore-Sigma. Gabe joined the Journal of Chemical Information and Modeling as an Early Career Board member in 2021.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Xiaowei Jia (University of Pittsburgh)

14-12-202114-12-2021

With: Xiaowei Jia is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. He obtained my Ph.D. degree at the University of Minnesota, under the supervision of Prof. Vipin Kumar. Prior to that, he got his B.S. and M.S. from the University of Science and Technology of China (USTC) and State University of New York at Buffalo.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Bharath Ramsundar: "Language based Pre-training for Drug Discovery"

07-12-202107-12-2021

With: Bharath received a BA and BS from UC Berkeley in EECS and Mathematics and was valedictorian of his graduating class in mathematics. He did his PhD in computer science at Stanford University where he studied the application of deep-learning to problems in drug-discovery. At Stanford, Bharath created the deepchem.io open-source project to grow the deep drug discovery open source community, co-created the moleculenet.ai benchmark suite to facilitate development of molecular algorithms, and more. Bharath’s graduate education was supported by a Hertz Fellowship, the most selective graduate fellowship in the sciences. After his PhD, Bharath co-founded Computable a startup that built better tools for collaborative dataset management. Bharath is currently working actively on growing the DeepChem community and on exploring a few early projects still in stealth. Bharath is the lead author of “TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning”, a developer’s introduction to modern machine learning, with O’Reilly Media, and the lead author of “Deep Learning for the Life Sciences”
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Sereina Riniker (ETH Zurich)

23-11-202123-11-2021

With: Sereina Riniker is currently Associate Professor of Computational Chemistry at the Department of Chemistry and Applied Biosciences of ETH Zurich. 
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Alexandre Tkatchenko: On Electrons and Machine Learning Force Fields

16-11-202116-11-2021

With: Alexandre Tkatchenko is a professor at the Department of Physics and Materials Science (and head of this department since January 2020) at the University of Luxembourg, where he holds a chair in Theoretical Chemical Physics. Tkatchenko also holds a distinguished visiting professor position at Technical University of Berlin. His group develops accurate and efficient first-principles computational models to study a wide range of complex materials, aiming at qualitative understanding and quantitative prediction of their structural, cohesive, electronic, and optical properties at the atomic scale and beyond. He has delivered more than 250 invited talks, seminars and colloquia worldwide, published 180 articles in prestigious journals (h-index of 69 with more than 24,000 citations; Top 1% ISI highly cited researcher in 2018-2020), and serves on the editorial boards of Science Advances and Physical Review Letters. Tkatchenko has received a number of awards, including APS Fellow from the American Physical Society, Gerhard Ertl Young Investigator Award of the German Physical Society, Dirac Medal from the World Association of Theoretical and Computational Chemists (WATOC), van der Waals prize of ICNI-2021, and three flagship grants from the European Research Council: a Starting Grant in 2011, a Consolidator Grant in 2017, and Proof-of-Concept Grant in 2020.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar "Towards fully digital R&D in chemistry and process engineering" by Alexei Lapkin (University of Cambridge)

09-11-202109-11-2021

With: Alexei Lapkin
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Marwin Segler (Microsoft Research)

19-10-202119-10-2021

With: Dr. Marwin Segler is Senior Researcher at Microsoft Research. Before that, he was researcher at BenevolentAI and PhD student at WWU Muenster, where he worked on planning chemical synthesis with deep neural networks and symbolic AI.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Prof. Andrew White (University of Rochester): Making cool stuff with deep learning

05-10-202105-10-2021

With: Andrew White graduated from Rose-Hulman Institute of Technology in 2008 with a BS in chemical engineering. While at Rose, he spent a year studying at the Otto-von Guericke Universität and the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. Dr. White completed a PhD in chemical engineering at the University of Washington in 2013. The thesis topic was the creation of non-fouling biomimetic surfaces with computational modeling. Next, Dr. White worked with Professor Greg Voth at University of Chicago as a Post-doctoral fellow in the Institute for Biophysical Dynamics from 2013-2014. In Chicago, he developed new methods for combining simulations and experiments. Dr. White joined the University of Rochester in Chemical Engineering in 2015 and is currently an associate professor. He has joint appointments in the Chemistry Department, Biophysics, Materials Science, and Data Science programs. Dr. White received a National Science Foundation CAREER award in 2018 and an Outstanding Young Investigator Award from the National Institutes of Health in 2020. Dr. White has authored a textbook on deep learning for molecules and materials, which is freely available at https://whitead.github.io/dmol-book.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-650) seminar by Prof. Volker Deringer (University of Oxford)

21-09-202121-09-2021

With: Volker Deringer studied chemistry at RWTH Aachen University (Germany), where he obtained his diploma (2010) and doctorate (2014) under the guidance of Richard Dronskowski. In 2015, he moved to the University of Cambridge as a fellow of the Alexander von Humboldt Foundation; in 2017, he was awarded a Leverhulme Early Career Fellowship at the same institution. He joined the Inorganic Chemistry Laboratory of the University of Oxford in September 2019. In addition to his Associate Professorship in the Department, he holds a Tutorial Fellowship at St Anne’s College, Oxford.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

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