| Presenter | Presenter's Title and Organization | Link to Presentation Page |
|---|---|---|
| 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 (Not Released) |
| 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 (Not Released) |
| Nikita Kozak | Stanford University | Leveraging Steerable Equivariant Graph Neural Networks for Data-Driven Flow Modeling (Not Released) |
|
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 |
