See you at SUDS 2024!
- Thursday, August 22nd
- 8:00-8:30 Badging and Coffee
- 8:30-9:15 Keynote: Dr. Jennifer Ngadiuba
- 9:15-10:00 Keynote: Dr. Anima Anandkumar
- 10:00-10:30 Panel Discussion
- 10:30-10:45 Coffee Break
- 10:45-12:00 Thursday Poster Session
- 12:00-1:30 Lunch
- 1:30-3:00 Oral 3
- 1:30-2:30 Townhall: The State of SUDS
- 3:00-3:30 Coffee Break
- 3:30-5:30 Oral 4
- Poster Map
Thursday, August 22nd
- Schedule-at-a-glance is available for a graphical view of the program.
8:00-8:30 Badging and Coffee
Chen Breezeway
8:30-9:15 Keynote: Dr. Jennifer Ngadiuba
Chen 100, overflow Chen 130
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Dr. Jennifer Ngadiuba is Associate Scientist with Wilson Fellowship at the Fermi National Accelerator Laboratory, the leading facility for particle physics research in the United States. She is specialised in the application of AI to particle physics towards more intelligent detector systems, data reduction and data analysis strategies. This ensures the efficient extraction of the most fundamental physics information from the multitude of data collected at the Large Hadron Collider (LHC), the world’s highest-energy particle physics experiment located at the CERN laboratory (Switzerland-France). |
9:15-10:00 Keynote: Dr. Anima Anandkumar
Chen 100, overflow Chen 130
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Dr. Anima Anandkumar is the Bren Professor of Computing and Mathematical Sciences at the California Institute of Technology, and co-founder of the AI4Science initiative at Caltech. Her research interests are in the areas of large-scale machine learning, non-convex optimization and high-dimensional statistics. In particular, she has been spearheading the development and analysis of tensor algorithms for machine learning. |
10:00-10:30 Panel Discussion
Chen 100, overflow Chen 130
10:30-10:45 Coffee Break
Chen Breezeway
10:45-12:00 Thursday Poster Session
Chen Breezeway
| ID | Tags | Description |
|---|---|---|
| 3-C3 | Forecasting Permafrost Carbon Dynamics in Alaska with Earth Observation Data and Artificial Intelligence Bradley A Gay (Jet Propulsion Laboratory)*; Neal Pastick (United States Geological Survey); Jennifer Watts (Woodwell Climate Research Center); Amanda Armstrong (National Aeronautics and Space Administration); Kimberley Miner (Jet Propulsion Laboratory); Charles Miller (Jet Propulsion Laboratory) |
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| 6-B5 | Getting Fit: Principled Model Selection and Validation in Space Weather Daniel Brandt (Michigan Tech Research Institute)*; Erick Vega (Michigan Tech Research Institute) |
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| 7-C5 | Solar Wind Structures from the Gaussianity of Magnetic Magnitude Zesen Huang (UCLA)* |
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| 29-A2 | Random forest regression on multi-platform in-situ ocean observations: Investigating high-frequency nutrient dynamics in the Southern Ocean Sangmin Song (University of Washington)* |
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| 30-B3 | JPL SUDS Air Quality Project: Sub-grid scale drivers of pollution revealed from model-based inference and machine learning Yuliya Marchetti (JPL)*; Kazuyuki Miyazaki (JPL); James Montgomery (JPL); You Lu (Jet Propulsion Laboratory); Kevin Bowman (JPL) |
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| 31-A5 | Machine Learning and Risk Analysis of Geomagnetically Induced Currents from Coronal Mass Ejections and Space Weather Sean Jung (University of Washington)* |
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| 34-B4 | Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical Systems Doris Voina (University of Washington)*; Nathan Kutz (University of Washington); Steven L. Brunton (University of Washington) |
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| 62-A4 | Vertical AI-driven Scientific Discovery Yexiang Xue (Purdue University)* |
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| 63-D1 | Remotely sensed plant stress observations improve fine-scale wildfire prediction models Madeleine Pascolini-Campbell (JPL)* |
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| 65-B2 | Optimizing the First-Order Radiative Transfer Model Using Deep Residual Networks for NISAR Soil Moisture Retrieval Xiaodong Huang (Jet Propulsion Laboratory)*; Lorenzo Giuliano Papale (Tor Vergata University of Rome); Marco Lavalle (Jet Propulsion Laboratory ); Heresh Fattahi (Jet Propulsion Laboratory); Rowena Lohman (Cornell University) |
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| 68-B6 | Modeling Turbulent and Self-Gravitating Fluids with Fourier Neural Operators Keith Poletti (University of Texas at Austin)*; Stella Offner (University of Texas at Aust); Rachel Ward (University of Texas) |
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| 74-C2 | OCO-3 Gain Instability Patterns Revealed by CDS Pedestal Clusters Robert A Rosenberg (JPL)*; Yuliya Marchetti (JPL); Graziela Keller (JPL) |
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| 88-C1 | Novel High Resolution Image Segmentation for Small Holder Farms in the Global South Michelle Lin (McGill University)* |
12:00-1:30 Lunch
1:30-3:00 Oral 3
Chen 100, overflow Chen 130
| ID | Time | Tags | Description |
|---|---|---|---|
| 20 | 1:30-2:00 | Machine Learning for Everyone: An MBx Approach Barbara J Thompson (NASA Goddard Space Flight Center)*; Mark Carroll (NASA Goddard Space Flight Center); Daniel E da Silva (NASA/GSFC, UMBC); Robert Morganstern (NASA Goddard Space Flight Center) |
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| 58-D2 | 2:00-2:15 | Three-dimensional mesoscale eddy kinetic energy in the global ocean estimated from integrating altimetry and profiling float observations Alison Gray (University of Washington)* |
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| 41-A3 | 2:15-2:30 | Improving Rainfall-Runoff Modeling Using Attention-Based Model: A Perspective on Explainability Jinyang Li (University of California, Irvine)*; Kuo-lin Hsu (University of California, Irvine); Soroosh Sorooshian (University of California, Irvine) |
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| 64-A6 | 2:30-2:45 | Statistical Approaches to Geomagnetic Index Prediction Yang Chen (University of Michigan)* |
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| 22-C4 | 2:45-3:00 | Learning Relationships Between Disparate Representations of Objects with Transformers and Contrastive Losses Azton I Wells (Argonne National Laboratory)*; Nesar Ramachandra (Argonne National Laboratory); Salman Habib (Argonne National Laboratory); Nicholas Frontiere (Argonne National Laboratory) |
1:30-2:30 Townhall: The State of SUDS
Broad 100
3:00-3:30 Coffee Break
3:30-5:30 Oral 4
Chen 100, overflow Chen 130
| ID | Time | Tags | Description |
|---|---|---|---|
| 43-D4 | 3:30-3:45 | Learning from the Machines Nima Sedaghat (University of Washington)* |
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| - | 3:45-4:00 | Withdrawn | |
| 5-B1 | 4:00-4:15 | Predictive Insights in Hydrology with Hybrid Physics and Data Sciences for Climate Adaptation Puja Das (Northeastern University)*; August Posch (Northeastern University); Nathan Barber (Tennessee Valley Authority); Kate Duffy (BAER Institute / NASA); Thomas Vandal (NASA / Bay Area Environmental Research Institute); Michael Hicks (Tennessee Valley Authority); Debjani Singh (Oak Ridge National Laboratory); Auroop Ganguly (Northeastern) |
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| 45-D3 | 4:15-4:30 | Forecasting community water system outages Monica G Bobra (State of California Office of Data and Innovation)*; Dan Wang (California State Water Resources Control Board, Division of Drinking Water) |
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| 46 | 4:30-5:00 | Into the Storm: AI/Anomaly Detection Approaches for Geospace Superstorm Investigations Janet U Kozyra (NASA)*; Hannah R Marlowe (Amazon Web Services); Delores J Knipp (Unviersity of Colorado Boulder); Liam Kilcommons (University of Colorado Boulder); Yigit Aytac (Amazon Web Services); Ekaterina Verner (NASA) |
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| 8 | 5:00-5:30 | Machine learning in the reconstruction and interpretation of radiation belt dynamics Jacob Bortnik (UCLA)* |
Poster Map
