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Rutgers Theory Symposium
September 4 @ 9:00 am - 5:00 pm
Morning session: ML/Data-based methods and software
9:20 – Opening remarks
9:30 – Bhaskar Rana (Pavanello group)
Learning the Electronic Structure of Excited States via the 1-RDM
9:50 – Rishi Rao (Zhu Group)
Machine Learning of Self-energies for Accelerated DMFT Calculations
10:10 – Aniket Mandal (Pavanello group)
QEpy: Quantum ESPRESSO in Python
10:30 – break
11:00 – Meiyan Wang (Zhu Group)
From Semiconductors to Superconductors: A Data-Driven Pipeline for Exploring Complex Energy Landscapes
11:20 – Jessica Martinez Bernal (Pavanello group)
Machine Learning the 2-RDM
11:40 – Ezekiel Oyeniyi (Pavanello group, zoom)
Pseudopotentials for Orbital Free DFT
12:00 – lunch break
Afternoon Session: Physics-based methods
2:30 – Jack Taylor (Maitra Group)
Ground-to-excited state conical intersections in LR-TDDFT: Implications for nonadiabatic molecular dynamics
2:50 – Anya Baranova (Maitra Group)
Excited-State Densities from Linear-Response TDDFT
3:10 – Dhyey Ray (Maitra Group)
The Application of Response-Reformulated TDDFT to Strong-Field Dynamics in Systems with Double Excitations
3:30 – break
4:00 – Valeria Rios Vargas (Pavanello group)
Orbital-Free TDDFT for Plasmonic Nanoparticles
4:20 – Evaristo Villaseco (Maitra group)
Electronic Coherences in Molecules: The Nuclear Quantum Momentum as Hidden Agent
4:40 – Open discussion