2nd Student-Focused SciML Symposium @ GT 2024
Virtual Symposium
19th & 21st Nov, 2024
About Sci-ML Symposium
The second student-focused scientific machine learning (SciML) symposium at Georgia Tech is dedicated to the development and applications of SciML methodologies led by current students in a wide array of applications. The primary goal of this symposium is to showcase student talents and contributions through the invited and contributed talks. Although this symposium is student-focused, everyone is welcome to attend irrespective of their student status. This event originated from the graduate Special Topics Course on SciML at Georgia Tech. In compliance with FERPA, only the group names (rather than the author names) will be provided in the schedule for the projects that were conducted by the students of the course.
Code of Conduct:
The organizational staff of the SciML Symposium is committed to providing a positive symposium experience for all attendees, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion, or national and ethnic origin. We encourage respectful and considerate interactions between attendees and do not tolerate harassment of symposium participants in any form. Symposium participants violating these standards may be sanctioned or expelled from the symposium at the discretion of the symposium organizers.
Zoom - Google Calendar Invites
Dates and Venue
19th Nov, 2024 - Session 1
Click to Join in Zoom!
8:00-8:15AM |
2B1G: Optimize Hydraulic Conductivity Estimation using Fourier Neural Operator |
8:15-8:30AM |
CompOpt: Physics-Informed Fourier Neural Operators for Photonic Device Simulation and Optimization |
8:30-8:45AM |
The Natural Disasters: Predicting Ground Temperatures and the Active Layer Thickness for Permafrost |
8:45-9:00AM |
Bio Team: Modeling the FitzHugh-Nagumo System with Scientific Machine Learning |
9:00-9:15AM |
Magdalini Koukouraki - ESPCI (Invited Talk): Experimental Investigation of Water Wave Scattering by a Vertical Plate |
21st Nov, 2024 - Session 2
Click to Join in Zoom!
8:00-8:15AM |
Physics GP: Towards discovery of minimal structure of Physics-Informed Neural Networks |
8:15-8:30AM |
AIRO: Aeroacoustic Noise Predictions Using Physics-Informed Neural Networks |
8:30-8:45AM |
Physics Team 3: Scientific Machine Learning for Cardiac Electrophysiology Simulations |
8:45-9:00AM |
Team 8: EP-PINN Reduced FHN modeling in Detailed Cardiac Potentials |
9:00-9:15AM |
Eric Qu - UC Berkeley (Invited Talk): The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains |
Guest Speakers
Organizers