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SUMMARY:What can AI do for molecular simulation?
DTSTART:20231107T151500
DTEND:20231107T161500
DTSTAMP:20260411T071824Z
UID:91878b788472d9653a4152706cd99606c3bc17f95a458828ce35752f
CATEGORIES:Conferences - Seminars
DESCRIPTION:Frank Noé has a background in Electrical Engineering\, Comput
 er 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\, al
 so located in Berlin. Frank has received two European Research Commission 
 (ERC) grants and the early career award in Theoretical Chemistry of the Am
 erican Chemical Society (ACS). He is member of the Berlin-Brandenburg acad
 emy of sciences\, a fellow in the European Laboratory for Learning and Int
 elligent Systems (ELLIS) and an ISI highly cited researcher. Frank’s re
 search is highly interdisciplinary and focuses on developing Machine Lea
 rning methods to address fundamental questions in the natural Sciences.\
 nAI\, especially deep learning methods have had enormous impact on a varie
 ty of fields in the last few years. It is increasingly clear that AI metho
 ds will also play a key role in the sciences\, e.g.\, to emulate molecular
  simulators at vastly increased speed\, or to enable computational to achi
 eve higher accuracies. In this talk I will introduce generative deep learn
 ing methods to address the sampling problem in biomolecular simulations as
  well as deep learning methods for achieving highly accurate quantum Chemi
 stry solutions.
LOCATION:https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYl
 NRdz09
STATUS:CONFIRMED
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