Overview

Teaching: min
Exercises: min

Questions

Objectives

1. Day info

• August 14, 2024, Monday
• Where: Baldy 200G

2. Presentations

2.1. 9:00 - 9:15 am Alexey Akimov: Opening and Logistics

Opening

2.2. 9:15 - 10:00 am Daniel Crawford: MolSSI presentation

MolSSI

2.3. 10:00 am - 10:40 am Zhenggang Lan (remote): Nonadiabatic Dynamics and Machine Learning

Abstract Presentation

2.4. 10:40 am - 11:20 am Maksim Kulichenko: Advancing Quantum Simulations with Machine Learning and Graph Theory

Abstract Presentation

2.5. 11:20 am - 12:00 am Rafael Gomez-Bombarelli (remote): Exploring photochemical isomerization mechanisms with excited-state ML potentials

Abstract Presentation

2.6. 1:30 pm - 2:10 pm Michele Pavanello: Towards sustainable electronic structure predictions: lessons from embedding and machine learning

Abstract Presentation Code Examples

2.7. 2:10 pm - 2:50 pm Mark Tuckerman: Synthesizing first-principles simulation, machine learning, and experimental strategies for the design and analysis of a new class of high-performance battery electrolytes exploiting the Grotthuss structural diffusion mechanism

Abstract Presentation

2.8. 2:50 pm - 3:30 pm Nitin Murthy (Johannes Hachmann group): ChemML: A Machine Learning and Informatics Program Package for the Analysis, Mining, and Modeling of Chemical and Materials Data

Abstract Presentation

2.9. 3:30 pm - 4:10 pm Mohammad Shakiba (Alexey Akimov group): Nonadiabatic molecular dynamics with machine-learned Kohn-Sham Hamiltonian mapping

Abstract Presentation

3. Videorecordings

3.1. UB Recording:

3.2. Zoom recordings:

Key Points