AI in chemistry and beyond: Trends in the field (ChE-607)

With: Brett Savoie is the inaugural Coyle Mission Collegiate Professor of Engineering in the Department of Chemical and Biomolecular Engineering at the University of Notre Dame. Brett graduated with degrees in chemistry and physics from Texas A&M University in 2008, obtained his Ph.D. in theoretical chemistry from Northwestern University in 2014, and from 2014-2017 was a postdoc with Thomas Miller at Caltech. In 2017, Brett joined the faculty of the Davidson School of Chemical Engineering at Purdue University, where he established an independent research group to develop physics-based and machine learning methods to characterize and discover new organic materials. In 2022, Brett was promoted to the Charles Davidson Associate Professor of Chemical Engineering at Purdue University. In July 2024, Brett joined the faculty at Notre Dame to advance computational materials research and lead the university’s Scientific AI (SAI) initiative. Brett is the recipient of the ACS PRF, NSF CAREER, Dreyfus Machine Learning in the Chemical Sciences, and ONR YIP awards.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Kim Jelfs completed her PhD in Computational Chemistry at University College London, working on the development and application of modelling to understand zeolite crystal growth and was awarded the Ramsay Medal for the best completing PhD student. She then went on research visits at the Universitat de Barcelona, the University of Liverpool, and finally Imperial as a research fellow, where she is now a Professor since 2022. Kim was awarded a 2018 Royal Society of Chemistry Harrison-Meldola Memorial Prize, a 2019 Philip Leverhulme Prize in Chemistry and was named the 2022 UK Blavatnik Awards Laureate in Chemistry. Kim holds an ERC Starting Grant and is an Associate Editor for Chemical Communications.        
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Prof. Emma Schymanski is chemist known for her work identifying unknown organic compounds, particularly pollutants. She graduated with a B.Sc. in Chemistry and a B.E. in Environmental Engineering from the University of Western Australia in 2003. She completed her PhD at the Helmholtz Centre for Enironmental Research in Leipzig, Germany in 2011, and a postdoc position at the Swiss Federal Institute of Aquatic Science and Technology. She is now head of the Environmental Cheminformatics Group as a Full Professor at the University of Luxembourg.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYINRdz09
Category: Conferences – Seminars

With: Ian is a PhD Candidate in the joint Carnegie Mellon University – University of Pittsburgh Computational Biology PhD Program where he is advised by David Koes. His research is focused on developing deep generative models for applications in structure-based design.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Dr. Bilodeau is currently an assistant professor in Chemical Engineering at the University of Virginia. She received her B.S. and M.S. from Northwestern University and her Ph.D. from Rensselaer Polytechnic Institute, both in Chemical and Biological Engineering. During her Ph.D., she received the Lawrence Livermore Advanced Simulations and Computation Graduate Fellowship, through which she carried out research at Lawrence Livermore National Laboratory. She completed a postdoc at MIT working with Klavs Jensen and Regina Barzilay. Her research explores the intersection between artificial intelligence and molecular simulations with the goal of designing new molecules and materials.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Marvin is a PhD student jointly at IBM Research and the University of Zürich. His research focusses on multimodal language models applied to analytical chemistry. Before joining IBM he completed a Masters in Chemistry at Imperial College London.
Place and room: CH G1 495
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With:   Dr. Zhiling Zheng is a Postdoctoral Associate at the Massachusetts Institute of Technology and a member of the Bakar Institute of Digital Materials for the Planet (BIDMaP). He completed his Bachelor’s degree in Chemistry and Chemical Biology at Cornell University in 2019, where he worked under the guidance of Prof. Kyle M. Lancaster. He then earned his Ph.D. in Chemistry from the University of California, Berkeley in 2023, supervised by Prof. Omar M. Yaghi. In the early phase of his Ph.D., Dr. Zheng was trained as an experimental chemist, focusing on the design and synthesis of Metal-Organic Frameworks (MOFs) for atmospheric water harvesting and CO2 capture. Later, his research scope expanded to the use of large language models (LLMs) and machine learning (ML) in accelerating the discovery of reticular materials and drug molecules. Dr. Zheng is recognized as a Merrill Presidential Scholar and has received the Kavli ENSI Graduate Student Fellowship for his contributions to AI and Chemistry.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Originally from Ukraine, Ganna (Anya) Gryn’ova received her BS and MSc in chemistry summa cum laude from Oles Honchar Dnipro National University. In 2014 she received a PhD in computational chemistry from Australian National University. Her doctoral thesis gathered a number of awards, including the IUPAC-Solvay International Award for Young Chemists for one of the five most outstanding PhD theses in the general area of the chemical sciences worldwide. Dr. Gryn’ova continued her research career at École Polytechnique Fédérale de Lausanne as a postdoctoral researcher working on in silico modeling of organic semiconductors. In 2016 she won the Marie Skłodowska-Curie Actions individual fellowship and focussed on the non-conventional architectures of single-molecule junctions. In 2019, Dr. Gryn’ova started her independent scientific career leading the junior research group “Computational Carbon Chemistry” (CCC) at the Heidelberg Institute for Theoretical Studies (HITS gGmbH) and Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University, Germany. The CCC group uses state-of-the-art computational chemistry and data science to explore and exploit diverse functional organic materials for applications in organocatalysis and environmental remediation. In 2021, Anya received the prestigious ERC Starting Grant for her project “PATTERNCHEM: Shape and Topology as Descriptors of Chemical and Physical Properties in Functional Organic Materials”; she is also a principal investigator in the Collaborative Research Centre SFB1249 “N-Heteropolycycles as Functional Materials” and the SIMPLAIX strategic research initiative on bridging scales from molecules to molecular materials by multiscale simulation and machine learning.
Place and room: BCH 2218
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Kobi Felton is a chemical engineer interested in solving problems at the intersection of chemical engineering, chemistry and software. He holds a Bachelor of Science in Chemical Engineering from North Carolina State University and a MPhil Research and PhD in Chemical Engineering from the University of Cambridge, where he was a recipient of the Marshall Scholarship and the Cambridge-Marshall PhD Scholarship. His current projects include: Optimization of distillation control systems, Self-optimization of reactions using bayesian algorithms, Design of experiments for time-series datasets, and Designing descriptors for chemical reactions.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Frank Noé has a background in Electrical Engineering, Computer Science and Physics and did his PhD at University of Heidelberg in 2006. He became group leader at FU Berlin in 2007 and professor in 2013. Since 2022 he is Partner Research Manager in Microsoft Research AI4Science, also located in Berlin. Frank has received two European Research Commission (ERC) grants and the early career award in Theoretical Chemistry of the American Chemical Society (ACS). He is member of the Berlin-Brandenburg academy of sciences, a fellow in the European Laboratory for Learning and Intelligent Systems (ELLIS) and an ISI highly cited researcher. Frank’s research is highly interdisciplinary and focuses on developing Machine Learning methods to address fundamental questions in the natural Sciences.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Daniel received his BSc in computer science at the Bern University of Applied Sciences in 2013 and his MSc in Bioinformatics and Computational Biology at the University of Bern in 2016. In 2020 he received his PhD in Chemistry and Molecular Sciences for his thesis “Scalable Methods for the Exploration and Visualization of Large Chemical Spaces” from the University of Bern under the supervision of  Prof. Jean-Louis Reymond. His main research interest is efficient machine learning and data visualisation applied to natural sciences, focusing on the intersection of chemistry and biology. After a two-year stay as a permanent research staff member at  IBM Research in the Team of Teodoro Laino working on machine learning for biocatalysis, he started as a postdoctoral researcher in the group of  Prof. Pierre Vandergheynst at EPFL.
Place and room: MA A1 10
Category: Conferences – Seminars

With: Jules Schleinitz. Jules is currently a postdoctoral scholar at CalTech in the group of Sarah E. Reisman and a current member of the NSF Center for Computer Assisted Synthesis. His research focuses on the development of computational and machine learning tools for organic synthesis planning through mechanistic understanding. Jules graduated in 2022 from the Ecole Normale Supérieure in Paris. His PhD intitled “Machine learning and Mechanistic Analysis” was supervised by Laurence Grimaud. Alongside with his research activities, Jules spent half of his PhD teaching chemistry at Ecole Normale Supérieure (Organic chemistry: lessons, electrochemistry: tutorials and experimental sessions, experimental projects for bachelor and master students.).
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Oh-hyeon studied computational neuroscience at EPFL with Prof. Herzog, where she researched the fundamental aspects of computer vision models. She then started her career at Novartis focusing on machine learning research for drug discovery. Soon, she will start a new challenge at a med-tech company (SynpleChem) for lab automation.  
Place and room: CH G1 495
Category: Conferences – Seminars

With: Kjell Jorner is an Assistant Professor of Digital Chemistry at ETH Zurich since January 2023. His work focuses on accelerating chemical discovery with digital tools, with a special emphasis on reactivity and catalysis. His group does interdisciplinary research, drawing from the fields of computational chemistry, cheminformatics and machine learning. Before joining ETH Zurich, he was a postdoctoral researcher with Alán Aspuru-Guzik (2021-2022) and at AstraZenecaUK (2018-2020). Kjell has a PhD from Uppsala University (2018) on computational physical organic chemistry for the photochemistry of aromatic compounds.
Place and room: CH G1 495
Category: Conferences – Seminars

With: Minkai Xu is a Ph.D. student in the Computer Science Department at Stanford University. Previously, he received his M.Sc degree from Mila and B.E. from Shanghai Jiaotong University. His research lies in probabilistic models, geometric representation learning, and ML for scientific discovery. He has published several influential papers on the above topics in top machine learning conferences (e.g., ICML, NeurIPS, ICLR, AAAI, and AAMAS) including the first diffusion models for molecular structure generation, which has been widely adopted in various drug and protein design problems. His research is generously supported by Sequoia Capital Stanford Graduate Fellowship.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Hannes Stärk is a PhD student at MIT in the CS and AI Laboratory (CSAIL) co-advised by Tommi Jaakkola and Regina Barzilay.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09#success
Category: Conferences – Seminars

With: Rafael Gomez-Bombarelli is the Jeffrey Cheah Career Development Professor in MIT’s Department of Materials Science and Engineering. His work aims to fuse machine learning and atomistic simulations for designing materials and their transformations. Through collaborations at MIT and beyond, Rafael’s group develops new practical materials such as catalysts, therapeutic peptides, organic electronics or electrolytes for batteries. Rafael joined MIT in 2018 after earning BS, MS, and PhD (2011) degrees in chemistry from Universidad de Salamanca (Spain) and carrying postdoctoral work at Heriot-Watt, Harvard and at Kyulux North America. His machine learning work has received faculty awards from the Dreyfus Foundation and Google. Rafael was a co-founder of Calculario, a Harvard spinout company, and served as Chief Learning Officer of ZebiAI, a drug discovery startup.
Online: https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYlNRdz09
Category: Conferences – Seminars

With: Santiago Miret is an AI Researcher at Intel Labs where he focuses on applying AI for scientific problems with an emphasis on materials discovery and materials understanding. Through this effort, Santiago manages a wide range of academic collaborations focused on applying AI for scientific application. Among these collaboration, there have been notable engagements with the Matter Lab led by Alán Aspuru-Guzik at the University of Toronto and various AI laboratories at MILA in Montreal that have led to cross-institutional publications at various machine learning venues. Santiago was a primary organizer of the 1st AI for Accelerated Materials Discovery (AI4Mat) workshop at NeurIPS 2022, which brought together domain experts from various fields of materials science and AI to exchange research work and ideas in an interdisciplinary forum. Prior to working at Intel Labs, Santiago obtained his PhD in Materials Science and Engineering from the University of California, Berkeley.
Place and room: CH G1 495
Category: Conferences – Seminars

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

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