2024 DOE CSGF Annual Program Review Presentations

Sunday, July 14 - Thursday, July 18
Hilton Washington DC National Mall The Wharf

Monday, July 15
Welcome
Ceren Susut Associate Director of Science for Advanced Scientific Computing Research, U.S. Department of Energy Office of Science DOE Office of Science Welcome
Thuc Hoang Director, Office of Advanced Simulation & Computing and Institutional R&D Programs, U.S. Department of Energy National Nuclear Security Administration DOE NNSA Welcome
Howes Scholar Award Presentations
Judith Hill Computational Scientist, Lawrence Livermore National Laboratory; DOE CSGF Alumna Introduction of the 2024 Frederick Howes Scholars
Kyle Bushick Postdoctoral Research Scientist, Lawrence Livermore National Laboratory; DOE CSGF Alumnus Building Tools for Digital Laboratories
Quentarius Moore MTS Software Development Engineer, Advanced Micro Devices; DOE CSGF Alumnus Enabling Excellence: Optimizing GPU Applications, AI Workloads, and Supporting the HPC Community
Session I
Mary LaPorte University of California, David Learning from Kernels: HPC in Plant Breeding
Marc Davis Massachusetts Institute of Technology Quantum Gate Synthesis for Clifford+T Circuits
Laura Nichols Vanderbilt University Defect Activation Through Hydrogen Release in Semiconductors
Session II
Danilo Perez Jr New York University Hierarchical Kalman Filter Reveals Multi-Timescale Neural Dynamics in the Orbitofrontal Cortex
Margot Fitz Axen University of Texas at Austin The Impact of Cosmic Rays on Molecular Cloud Collapse and Star Formation
Albert Musaelian Harvard University Scaling Equivariant Machine Learning for Atomic-Scale Simulations (No Release)
Tuesday, July 16
Keynote
Daniel Reed Presidential Professor in Computer Science, University of Utah Reinventing High-Performance Computing
Session III
Ethan Epperly California Institute of Technology Randomly Pivoted Cholesky: Faster Matrix Approximation for Scientific Machine Learning
Ariel Kellison Cornell University Numerical Fuzz: A Type System for Rounding Error Analysis
Justin Porter Rice University Prediction and Modeling of Nonlinear Vibration in Bolted Connections
Session IV
Santiago Vargas University of California, Los Angeles Ab Initio Enhancement of Machine Learning for Complex Chemistries
Alexandra Baumgart California Institute of Technology Reduced Order Chemistry Modeling for Detonations
Graham Pash University of Texas at Austin Towards Predictive Digital Twins With Applications to Precision Oncology
Session V
Nishad Maskara Harvard University Towards Useful Quantum Simulation With Reconfigurable Rydberg Atom Arrays
David Rogers Stanford University Model-Driven Verification of Enhanced Weathering for Carbon Dioxide Removal
Wednesday, July 17
Keynote
Mark Taylor E3SM Chief Computational Scientist, Sandia National Laboratories Cloud Resolving Atmospheric Modeling on Exascale Computers
Session VI
Luis Rangel DaCosta University of California, Berkeley Simulation and Machine Learning for Atomic-Scale Characterization of Nanomaterials With Transmission Electron Microscopy
Ian DesJardin University of Maryland, College Park Multifluid Simulation of Ion Acoustic Solitons Arising From a Charged Source and Comparison to the Forced Korteweg–de Vries Model
Margaret Trautner California Institute of Technology Operator Learning for PDEs: Function Space Theory Meets Machine Learning
Grant Johnson Princeton University Discontinuous Galerkin Algorithm for Particle Kinetics on Smooth Surfaces
Session VII
Anthony Degleris Stanford University Optimal Power Grid Expansion Planning Using Differentiable Electricity Models
Rachel Robey University of Colorado Boulder Approaches to Multi-Scale Challenges in Measurements and Modeling of Geophysical Flows
Kiran Eiden University of California, Berkeley Computational Modeling of Astrophysical Explosions With Central Engines (Release Pending)
Nikita Kozak Stanford University Leveraging Steerable Equivariant Graph Neural Networks for Data-Driven Flow Modeling (Release Pending)
Pre-Recorded
Talk submissions from outgoing fellows unable to attend the 2024 meeting in person.
Emily de Jong California Institute of Technology Modeling Droplet Collisions for the Climate Scale
Rebekah Loving California Institute of Technology Scalable and Accurate Long-Read Sequencing Transcriptome Quantification with Ir-Kallisto
Ellis Torrance University of North Carolina at Greensboro Evolution of Homologous Recombination Rates Across Bacteria