In order to try to make the most of the Covid-19 quarantene time a new on-line seminar series titled Machine Learning for Science, ML4Science, has been established. The series will host seminars from speakers from all over the world, discussing current topics in machine learning applied to the physical/chemical science. These investigate how machine learning methods can help in materials science, many-body physics, measurement techniques and how they can be used to extract data from literature. The seminars are weekly and are broadcasted live on the Youtube Channel
Although most of the talk will take place at 3pm (Irish time) the time can change, depending on the speaker. Note that the seminar will be recorded and will remain available for second view on Youtube. For information, seminar announcements and updates please follow the seminar series
Here is a list of recently broadcasted seminar:
- Tuesday, April 20th, Michele Ceriotti (EPFL) Physics-inspired Machine Learning for Materials Discovery
- Tuesday, April 14th, Giuseppe Carleo (Flatiron Institute), Machine Learning Techniques for Many-Body quantum systems
- Thursday, April 9th, Alexandre Tkatchenko (University of Luxembourg), Machine Learning Quantum Chemical Space
- Friday, April 3rd, Stefano Curtarolo (Duke University), Data, Disorder and Materials
- Tuesday, March 31st, Alessandro Lunghi (Trinity College Dublin), Spin-Phonon Relaxation in Molecular Materials: From First-Principles to Machine Learning
- Friday, March 27th, Rajarshi Tiwari (Trinity College Dublin), Search for Corrosion resistance