Machine Learning Seminars (ChE-651) – Spring

The Machine Learning Seminars are organized by Prof. Berend Smit, Prof. Clémence Corminboeuf and Prof. Jiri Vanicek, the seminars usually take place on Tuesdays at 15:15 CE 1. Unless indicated otherwise, the lecture takes place on Zoom.

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PAST EVENTS

"Machine learning in chemistry and beyond" (ChE-651) seminar by Cory Simon "Classifying the toxicity of pesticides to honey bees via support vector machines with random walk graph kernels"

Pesticides benefit agriculture by increasing crop yield, quality, and security. However, pesticides may inadvertently harm bees, which are valuable as pollinators. Thus, candidate pesticides in development pipelines must be…

07-06-202207-06-2022

With: Cory Simon hails from a small town in Ohio. He earned his B.S. in Chemical Engineering from the University of Akron. He then studied mathematics at the University of British Columbia in Vancouver, Canada for two years. In 2016, he earned his Ph.D. in Chemical Engineering from the University of California, Berkeley. He conducted scientific research at Virginia Tech, Okinawa Institute of Science and Technology, Lawrence Berkeley National Laboratory, École Polytechnique Fédérale de Lausanne, and Altius Institute for Biomedical Sciences and interned in industry at Bridgestone Research (chemical engineering) and Stitch Fix (data science). Since 2017, Cory is an assistant professor at Oregon State University in the School of Chemical, Biological, and Environmental Engineering. His research group employs molecular models and simulations, machine learning, and statistical mechanics to discover nanoporous materials for gas storage, separations, and sensing. Cory digs hiking/backpacking in scenic places, snowboarding, wine, and going on walks with his dog, Oslo.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Simon Batzner "Equivariant Interatomic Potentials"

24-05-202224-05-2022

With: Simon is a PhD student in Applied Mathematics at Harvard. While interested in far too many things for his own good, his research focuses on building deep learning systems for applications in computational physics and chemistry. Before joining Harvard, he worked on machine learning at MIT and on the NASA mission SOFIA. In his free time, you can find him playing soccer, hiking, and swimming. He comes to Harvard having finished his Master’s at MIT. He is originally from beautiful Illertissen, Germany. 
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Miguel Caro "Machine learning local atomic properties: accurate prediction of XPS spectra of carbon materials"

10-05-202210-05-2022

With: Miguel Caro is originally from a small town (Cartaya) in southwestern Spain. He graduated with a Physics degree from University of La Laguna, Tenerife, Spain. He then moved to Cork, Ireland, where he pursued a PhD in computational condensed-matter physics under Prof. Eoin O’Reilly at the Tyndall National Institute. His thesis work, for which he was awarded his PhD in 2013, focused on theory of III-N alloys, a material system widely used for optoelectronic applications. After the PhD, he moved to Aalto University, Finland as a postdoc in 2013. In 2017 he obtained the Academy of Finland Postdoctoral Researcher grant and since 2020 he is Academy of Finland Research Fellow. Dr. Caro’s current research interests concern the atomistic simulation of real materials, especially carbon-based materials, using a battery of simulation tools and methodologies, from density functional theory to machine learning.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Julian Zimmermann and Daniela Rupp "Machine learning based analysis of single-shot single-particle coherent diffraction imaging data"

26-04-202226-04-2022

With: Prof. Daniela Rupp is a Tenure-Track Assistant Professor at the head of the Nanostructures and Ultrafast X-ray Scienc group in the Department of Physics at ETHZ. Her group founded in 2019 develops and uses new methods to flash-image short-lived nanostructures and ultrafast changes in their electronic and structural properties via diffraction imaging, pushing towards extreme time-resolution. Before that, she was a Junior research group leader in “Ultrafast dynamics in nanoplasma” at the Max Born Institute in Berlin, Germany. She will present her research together with Dr. Julian Zimmermann, Postdoctoral researcher in her group at ETHZ.
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Maria Rodriguez Martinez "AI-driven modelling of T cell-based therapies"

05-04-202205-04-2022

With: Maria Rodriguez Martinez
Online: https://epfl.zoom.us/j/64473017589?pwd=Vmpnd1pleGhEb1hFb3kxUlNIUWJyQT09
Category: Conferences – Seminars

"Machine learning in chemistry and beyond" (ChE-651) seminar by Esther Heid "Graph-convolutional neural network: From molecules to chemical reactions"

22-03-202222-03-2022

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

"Machine learning in chemistry and beyond" (ChE-651) seminar by Risi Kondor (University of Chicago)

08-03-202208-03-2022

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

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