09 March – 12 March 2023
Discussion Meeting on
Machine Learning for Molecular Sciences
ML4Science 2023
at Germanus Springs, Kodaikanal
Next Meeting, ML4Science 2024 is scheduled from 25th to 28th of January 2024. More details in June/July 2023
Pictures from ML4Science 2023 here
Day 1: https://www.facebook.com/media/set/?set=a.599756318833554&type=3
Day 2: https://www.facebook.com/media/set/?set=a.600543392088180&type=3
Day 3/4: https://www.facebook.com/media/set/?set=a.601504525325400&type=3
More here: https://photos.app.goo.gl/nenQyRQVbD6qpuHGA (YOU could also upload your pictures here)
ML4Science 2023 is the first meeting in the proposed annual series after the initial pre-pandemic meeting on ML4Science at IIIT Hyderabad in November 2019. This meeting will focus on the applications of Modern Machine Learning methods in the general area of molecular sciences (Molecule/Drug/Material design, Interatomic potentials, MD simulations, etc.). The number of participants, approximately equal number of scientists and young researchers, is limited to about 70. There will be 20 talks, ~40 posters, hackathon sessions and enough time for discussions. It is desirable that the talks and posters present an ongoing work (or recently published work) with machine learning methods as one of the components. We request the speakers to avoid overview talks/Popular lectures.
ML4Science 2023 is the first meeting in the proposed annual series after the initial pre-pandemic meeting on ML4Science at IIIT Hyderabad in November 2019. This meeting will focus on the applications of Modern Machine Learning methods in the general area of molecular sciences (Molecule/Drug/Material design, Interatomic potentials, MD simulations, etc.). The number of participants, approximately equal number of scientists and young researchers, is limited to about 70. There will be 20 talks, ~40 posters, hackathon sessions and enough time for discussions. It is desirable that the talks and posters present an ongoing work (or recently published work) with machine learning methods as one of the components. We request the speakers to avoid overview talks/Popular lectures.
Organizers
TIFR Hyderabad - Madurai Kamaraj University - IIIT Hyderabad
Sponsors & Event Partners
Tyrone, RITTAL, CCNSB, IHub-Data & INAI, IIIT Hyderabad