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. |
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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 |