2023 Presentations

2023 DOE CSGF Annual Program Review Presentations

Sunday, July 16 - Thursday, July 20
Hilton Washington DC National Mall The Wharf

Monday, July 17
Welcome
Dr. Marvin Adams Deputy Administrator, Office of Defense Programs, National Nuclear Security Administration, U.S. Department of Energy DOE NNSA Welcome
Keynote
Tammy Ma Lead, Inertial Fusion Energy Initiative, National Ignition Facility, Lawrence Livermore National Laboratory Creating a Star on Earth, Ignition, and a Fusion Energy Future
Session I
Anda Trifan Investigator, GSK; DOE CSGF Alumna (Outgoing Fellow Talk) AI-Enabled Multi Resolution Simulations to Uncover Mechanisms of SARS-CoV-2 Virus
Amalee Wilson Stanford University Partitioning Strategies for Distributed SMT Solving
Jack Lindsey Columbia University Factorized Visual Representations in the Primate Visual System and Deep Neural Networks
Howes Scholar Award Presentation
Jeffrey Hittinger Lawrence Livermore National Laboratory; DOE CSGF Alumnus Announcement of 2023 Frederick Howes Scholar
Dipti Jasrasaria Postdoctoral Research Scientist, Columbia University Anharmonic Lattice Dynamics of Clathrates Explained by Vibrational Dynamical Mean-Field Theory
Session II
Jamin Rader Colorado State University Optimizing Seasonal-to-Decadal Analog Forecasts With an Interpretable Neural Network
Arianna Krinos Massachusetts Institute of Technology Leveraging Large Datasets to Discover Protistan Diversity Across Scales
Michael Toriyama Northwestern University Topological Insulators as Thermoelectrics
Jason Torchinsky University of Wisconsin-Madison Angular Hp-Adaptivity for Radiative Transfer
Tuesday, July 18
Keynote
Tapio Schneider Professor of Environmental Science and Engineering, California Institute of Technology; Senior Research Scientist, NASA Jet Propulsion Laboratory Earth System Modeling 2.0: Toward Accurate and Actionable Climate Predictions with Quantified Uncertainties
Session III
Lauren Zundel University of New Mexico Analysis of the Optical Response of Periodic Arrays of Nanostructures
William Moses Massachusetts Institute of Technology; DOE CSGF Alumnus (Outgoing Fellow Talk) Enzyme: High-Performance, Cross-Language, and Parallel Automatic Differentiation
Gabriel Casabona Northwestern University Numerical Frontier in Binary Compact Object Mergers
Guy Moore University of California, Berkeley The Foundation for a Ground-Up & Robust Approach to Computational Magnetic Materials Discovery
Session IV
Claire Zarakas University of Washington Land Parameter Uncertainty Impacts the Mean Climate State
Kyle Lennon Massachusetts Institute of Technology Scientific Machine Learning for Modeling and Simulating Complex Fluids
Boyan Xu University of California, Berkeley Structure-Aware Annotation of Leucine-Rich Repeat Domains
Session V
Peter Lalor Massachusetts Institute of Technology Reconstructing the Atomic Number of Cargo X-Ray Images Using Dual Energy Radiography
Madelyn Cain Harvard University Quantum Speedup in Combinatorial Optimization With Flat Energy Landscapes
Koby Hayashi Georgia Institute of Technology Constrained Low-Rank Approximation
Kyle Bushick University of Michigan Studying Direct and Phonon-Assisted Quantum Processes in Semiconductors
Wednesday, July 19
Keynote
Devin Matthews Assistant Professor of Chemistry, Southern Methodist University; DOE CSGF Alumnus What do Ionic Liquids Have to do With Linear Algebra?
Session VI
Jacob Bringewatt University of Maryland, College Park; DOE CSGF Alumnus (Outgoing Fellow Talk) Weighting God’s Dice: Exploiting Symmetry in Randomized Measurement Protocols
Thomas Blommel University of Michigan Acceleration of Non-Equilibrium Quantum Dynamics Calculations Using Data Compression
Lindsey Byrne Northwestern University The Co-Evolution of Supermassive Black Holes and Their Host Galaxies
Christopher Balzer California Institute of Technology Unraveling Electrostatic Interactions in Dipolar Solvents
Session VII
Louis Jenkins University of Rochester Dynamic Resource Scheduling of Jupyter Notebooks at Cell-Granularity
Scott Emmons University of California, Berkeley RvS: What is Essential for Offline RL Via Supervised Learning?
Nicholas Ezzell University of Southern California A Variational Approach to Quantum Tomography
Christopher Kane University of Arizona Lattice QCD Approach to Radiative Leptonic Decays