1st Student-Focused SciML Symposium @ GT 2023
Virtual Symposium
16th, 21st & 30th Nov, 2023
About Sci-ML Symposium
The inaugural 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 such as weather forecast, public health predictions, SciML models for materials science, drug discovery, financial prediction, astrophysics, and robotics, to name a few. 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
16th Nov, 2023 - Session 1
Click to Join in Zoom!
8:00-8:05AM ET |
Introductions |
8:05-8:20 AM ET |
Team Sharpe Explorers: Enhancing Option Pricing with Neural ODEs and SDEs |
8:20-8:35 AM ET |
Team Py-Iguana: Enhancing Epidemic Forecasting Through Hybrid Machine Learning and Epidemiological Models |
8:35-8:50 AM ET |
Team Polaris: Scientific Machine Learning for Generalized Drug-Target Interaction Predictions |
8:50-9:15 AM ET |
Invited Talk (Jack Richter-Powell - MIT) Staying grounded: scientific machine learning with physical inductive biases |
21st Nov, 2023 - Session 2
Click to Join in Zoom!
8:00-8:10AM ET |
Introductions |
8:10-8:35 AM ET |
Invited Talk (Handi Zhang - UPenn) Federated SciML for approximating functions and solving differential equations |
8:35-8:45 AM ET |
Team Efficient DFT: Increasing Efficiency of DFT with Surrogate Models of Graph Embeddings |
8:50-9:05 AM ET |
Team Stardust: Innovating Autonomous Robotics with Dual-Task Machine Learning for Navigation and Stability |
9:05-9:15 AM ET |
Team AutoCV: Solar Flare Peak Emission Flux Prediction |
30th Nov, 2023 - Session 3
Click to Join in Zoom!
8:00-8:10AM ET |
Introductions |
8:10-8:35 AM ET |
Invited Talk (Lorenzo Xavier Van Munoz - MIT) DeltaRCWA: a PEDS-driven solver for metamaterial scattering surrogates |
8:35-8:50AM ET |
Team Cassiopeia: A Scientific Machine Learning Framework for Neutron Star Gravitational Modeling |
8:50-9:05 AM ET |
Team CliML: Enhancing Weather Predictions with Hybrid Data and Physics-Based Models |
Guest Speakers
Organizers