See you at SUDS 2024!

Wednesday, August 21st

8:00-8:30 Badging and Coffee

Chen Breezeway

8:30-9:30 Opening Keynote

Chen 100, overflow Chen 130

9:45-10:45 Oral 1

Chen 100, overflow Chen 130

ID    Time Tags Description
71 9:45 - 10:15 AM Sampling Strategies and Insights for Fine-tuning Earth Observation Foundation Models for Diverse Downstream Tasks
Anna Jungbluth (European Space Agency)*; Laura Martínez-Ferrer (University of Valencia); Matthew J Allen (University of Cambridge); Joseph A. Gallego-Mejia (Drexel University); Francisco Dorr (Independent); Freddie Kalaitzis (University of Oxford); Raul Ramos-Pollan (Universidad de Antioquia)
27-D1 10:15 - 10:30 AM Data Scientists and Physical Scientists Working Together to Create a Novel and Comprehensive Map of Martian Frost
Serina Diniega (Jet Propulsion Laboratory)*; Mark Wronkiewicz (Jet Propulsion Laboratory); Gary Doran (Jet Propulsion Laboratory); You Lu (Jet Propulsion Laboratory); Umaa Rebbapragada (JPL); Jacob Widmer (University of California, Los Angeles)
19-D4 10:30 - 10:45 AM Knowledge Mgmt. Next Generation Communication and Information Exchange in the Hybrid Workplace: Why we need knowledge-based solutions now
Barbara J Thompson (NASA Goddard Space Flight Center)*; Raphael Attie (GSFC/George Mason U.); Ryan McGranaghan (Jet Propulsion Laboratory)

10:45-11:00 Coffee Break

11:00-12:00 Wednesday Poster Session

Chen Breezeway

ID    Tags Description
13-A2 Demonstrating Onboard Inference for Earth Science Applications with Spectral Algorithms and Deep Learning
Itai Zilberstein (Jet Propulsion Laboratory, California Institute of Technology)*; Steve Chien (Jet Propulsion Laboratory, California Institute of Technology); Alberto Candela (Jet Propulsion Laboratory, California Institute of Technology); David Rijlaarsdam (Ubotica Technologies); Leonie Buckley (Ubotica Technologies); Tom Hendrix (Ubotica Technologies); Aubrey Dunne (Ubotica Technologies)
14-B2 Global Land Change and Disturbance Mapping from Sentinel-1 OPERA RTC
Harris Hardiman-Mostow (UCLA); Charlie Z Marshak (JPL)*; Alexander Handwerger (JPL); Talib Oliver-Cabrera (JPL); Richard West (JPL); Jungkyo Jung (JPL)
23-A3 Storm Classification and Dynamic Targeting for a SMart ICE Cloud Sensing (SMICES) Satellite
Jason Swope (Jet Propulsion Laboratory, California Institute of Technology)*; Steve Chien (Jet Propulsion Laboratory, California Institute of Technology); Xavier Bosch-Lluis (Jet Propulsion Laboratory, California Institute of Technology); Emily R Dunkel (Jet Propulsion Laboratory, California Institute of Technology); Qing Yue (Jet Propulsion Laboratory, California Institute of Technology); Mehmet Ogut (Jet Propulsion Laboratory, California Institute of Technology); Isaac Ramos (Jet Propulsion Laboratory, California Institute of Technology); Pekka Kangaslahti (Jet Propulsion Laboratory, California Institute of Technology); William Deal (Northrop Grumman); Caitlyn Cooke (Northrop Grumman)
28-D2 Driving SUDS Impact Through Quality Data Releases
Mark Wronkiewicz (Jet Propulsion Laboratory)*; HAI MINH NGUYEN (JPL); Erika Podest (JPL)
37-D3 Machine Learning Classifiers for Martian Frost Detection in Satellite Observations
You Lu (Jet Propulsion Laboratory)*; Mark Wronkiewicz (Jet Propulsion Laboratory); Gary Doran (Jet Propulsion Laboratory); Umaa Rebbapragada (JPL); Serina Diniega (Jet Propulsion Laboratory); Jake Widmer (Jet Propulsion Laboratory)
39-A6 Event Detection to Understand Dynamic Systems: A Statistical Paradigm of Inquiry
Daniel E da Silva (NASA/GSFC, UMBC)*; Li-Jen Chen (NASA); Barbara J Thompson (NASA Goddard Space Flight Center)
47-B3 Predicting the Impact of Storms on Utility Customers Using Weather Analytics
David J Corliss (Grafham Analytics)*
51-A4 Bayesian Neural Network for Surface Reflectance Modeling to Improve Imaging Spectrometer Atmospheric Correction
Alberto Candela (Jet Propulsion Laboratory, California Institute of Technology)*; David Thompson (Jet Propulsion Laboratory, California Institute of Technology); Philip Brodrick (Jet Propulsion Laboratory, California Institute of Technology)
53-B4 Remote Sensing-based In-season Crop Mapping: Connecting Machine Learning Algorithms to Phenological Uncertainty
August Posch (Northeastern University - SDS Lab)*; Jitendra Kumar (Oak Ridge National Laboratory); Forrest Hoffman (Oak Ridge National Laboratory); Auroop Ganguly (Northeastern University)
54-C4 Machine-Learning Cosmology from Cosmic Voids
Bonny Y. Wang (Carnegie Mellon University)*; Alice Pisani (Princeton University); Francisco Villaescusa-Navarro (Princeton University); Benjamin D Wandelt (Institut d’Astrophysique de Paris)
59-C5 Using Evolutionary Algorithms to Design Antennas with Greater Sensitivity to Ultrahigh Energy Neutrinos
Bryan Reynolds (Ohio State University)*; Julie Rolla (NASA Jet Propulsion Laboratory); Alex Machtay (Ohio State University); Amy Connolly (Ohio State University); Jacob Weiler (Ohio State University); Dylan Wells (Ohio State University)
78-A5 Reconstructing the Sun in 3D using Neural Radiance Fields
Anna Jungbluth (European Space Agency)*; Robert Jarolim (University of Graz); Benoit Tremblay (High Altitude Observatory); Andrés Muñoz-Jaramillo (Southwest Research Institute); Kyriaki-Margarita Bintsi (Imperial College London ); Miraflor P Santos (MIT); Angelos Vourlidas (Johns Hopkins University, Applied Physics Laboratory); James Mason (Johns Hopkins University, Applied Physics Laboratory); Sairam Sundaresan (Intel Labs); Cooper Downs (Predictive Science Inc.); Ronald Caplan (Predictive Science Inc.)
86-B6 A Data-Driven Subgrid Model for Multi-Scale Black Hole Feedback
Haiyang Wang (Caltech)*

12:00-1:30 Lunch

1:30-2:15 Keynote: Dr. Amy McGovern

Chen 100, overflow Chen 130

Amy McGovern Dr. Amy McGovern is the director of the NSF AI Institute on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), and holds dual appointments in the School of Computer Science and the School of Meteorology at the University of Oklahoma. Her research focuses on developing and applying machine learning and data mining methods for real-world applications with a special interest in high-impact weather phenomena including tornados, hail, severe wind events, flooding, drought, and aircraft turbulence.

2:15-3:00 Keynote: Dr. Rose Yu

Chen 100, overflow Chen 130

Rose Yu Dr. Rose Yu is an Associate Professor at the UC San Diego, Department of Computer Science and Engineering. Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications to sustainability, health, and physical sciences. A particular emphasis of her research is on physics-guided AI which aims to integrate first-principles with data-driven models.

3:00-3:30 Panel Discussion

Chen 100, overflow Chen 130

3:30-4:00 Coffee Break

Chen Breezeway

4:00-5:30 Oral 2

Chen 100, overflow Chen 130

ID    Time Tags Description
11-C1 4:00-4:15 Connecting Science and Data Science for the Orbiting Carbon Observatory-2
William Keely (The University of Oklahoma)*; Steffen Mauceri (Jet Propulsion Laboratory)
49-C3 4:15-4:30 Causal Discovery for Aerosol-Cloud Interactions
Giorgia Nicolaou (UCSD)*; Duncan Watson-Parris (University of California San Diego)
56-C2 4:30-4:45 Observing System Simulation Experiments (OSSEs) as Tools for New Mission Design, Model Development, and Scientific Experimentation
Derek Posselt (Jet Propulsion Laboratory, California Institute of Technology)*
84-D5 4:45-5:00 Engaging a Community of Practice: Highlights from JPL’s SUDS Educational Working Group
Jonathan Hobbs (Jet Propulsion Laboratory, California Institute of Technology)*; Mark Wronkiewicz (Jet Propulsion Laboratory); Erika Podest (JPL)
2 5:00-5:30 Expediting Astronomical Discovery with Large Language Models: Progress, Challenges, and Future Directions
Yuan-Sen Ting (The Australian National University)*

6:30-8:30 Happy Hour @ Der Wolf

Der Wolf Pasadena, Rear Patio

Join us for food and drinks with the SUDS community!

Location:

Transportation:

Poster Map

Table of Contents