Conference Program

Tentative Conference Program

Tours of the National Energy Research Scientific Computing Center (NERSC), home of the Perlmutter supercomputer, and the Advanced Light Source, will also be offered throughout the conference.  Details and sign-up links will be sent to those who indicate interest at registration.

Abstracts, schedule, and full author lists will be available closer to the event.

Plenary Speakers

Monday, 9:30am: Rob Falgout (LLNL)
Tuesday, 9:00am: Suzanne Sindi (UC Merced)

Panelists

Monday, 3:30pm: Panel #1 - The Role of AI/ML and LLMs in Science

1. Tammy Kolda (MathSci.ai)
2. Michael Mahoney (UCB / LBL)
3. Shima Alizadeh (Amazon)
4. Habib Najm (Sandia)

Tuesday, 3:30pm: Panel #2 - Challenges in Mentoring Early-Career Professionals

1. Suzanne Sindi (UC Merced)
2. Harun Bayraktar (NVIDIA)
3. Rob Falgout (LLNL)
4. Ann Almgren (LBL)

Conference Thematic Session Speakers (Preliminary; Dates/Times TBA)

HPC and Simulation of Complex Dynamical Systems

1. Gavin Pandya (UC Davis): Multiscale vortex methods for compressible flow

2. Steven B. Roberts (LLNL): High Order Time Integrators for More Efficient Cloud Microphysics Simulations

3. Radoslav Vuchkov (SNL): Low-Rank Tucker Tensor Methods for Stochastic Dynamic Optimization

4. Dinesh Kumar (LBL): Hierarchical Reconstruction Method and HPC for Realtime Synchrotron Tomography
5. Laura Monroe (LANL): Mathematically designed networks for post-exascale systems

Uncertainty Quantification and Data-Driven Modeling

1. David Trebotich (LBL): gpAMR: UQ-Driven Adaptive Mesh Refinement

2. Pieterjan Robbe (SNL): Multifidelity Bayesian Optimization for Steady-State Predictions using Gyrokinetic Simulations of Plasma Turbulence

3. Michael Kielstra (UCB): Gradient-based, determinant-free, fully Bayesian Gaussian process regression

4. Jasper Lee (UC Davis): Optimal Sub-Gaussian Mean Estimation in R

5. Zineb Sordo (LBL): Review of generative models for scientific data

Machine Learning for Scientific Computing Part 1

1. Changho Kim (UC Merced): Statistics-Informed Neural Network as a Surrogate Modeling Tool

2. Christophe Bonneville (SNL): Towards Long Term Extrapolation of Phase-Field Simulations with Convolution-Only Deep Neural Networks

3. Jennifer Paige (UC Davis): Machine learning for optimal tuning of the Simple Cloud-Resolving Earth Atmosphere Model (SCREAM)

4. Maksym Zubkov (U British Columbia): The Geometry of Rational Neural Networks

5. Aaron Mishkin (Stanford): Optimal Sets and Solution Paths of ReLU Networks

Linear Algebra and Numerical Methods

1. Alec Dektor (LBL): Subspace projection methods for tensor eigenvalue problems

2. Henry Boateng (SFSU): Multicomplex Numerical Differentiation via Matrix Functions

3. Jennifer Zvonek (LLNL): Efficient Visualization of Implicit Neural Networks Via Weight Matrix Analysis

4. Mark Fornace (LBL): Column subset selection and Markov chain reduction using nuclear scores

5. Wayne Mitchell (LLNL): Semi-Structured Algebraic Multigrid in hypre

Computational Methods for Partial Differential Equations

1. Anuj Kumar (UCB): Almost anomalous dissipation in advection-diffusion of a divergence-free passive vector

2. Evan Gawlik (Santa Clara): Finite element discretizations of differential operators from Riemannian geometry

3. Justin Dong (LLNL): Well-posedness of ocean-atmosphere turbulent flux algorithms in Earth system models

4. Thai Nhan (Menlo College): Rank-Structured Direct Solvers and Preconditioners for Efficiently Solving Singularly Perturbed Differential Equations

5. Patrick Sprenger (UC Merced): Modulations of periodic wavetrains in a class of dispersive hydrodynamic models

Control Theory and System Optimization

1. Harish S. Bhat (UC Merced): Optimal control of molecular systems

2. Alyson Fox (LLNL): Advancing Collaborative Autonomy for Scalable and Resilient Systems

3. Robert Bassett (NPS): Decentralized Splitting for Large Optimization Problems

4. Saibal De (SNL): Efficient Fault-Tolerant Kalman Filter for Inertial Navigation Using Linear Algebra Checksums

5. Tucker Hartland (LLNL): A scalable interior-point Gauss-Newton method for PDE-constrained optimization with bound constraints

Machine Learning for Scientific Computing Part 2

1. Tyler Chang (Siemens): Leveraging interpolation models and error bounds for verifiable scientific machine learning

2. Siyuan Xing (Cal Poly SLO): Breaking Dimensional Barriers: A New Framework for Discovering Differential Equations in Complex Systems

3. Chris DeGrendele (UCSC): Hybrid ML-Numerical Solvers for Hyperbolic-Parabolic PDEs: Overcoming Timestep Constraints

4. Hardeep Bassi (UC Merced): SRaFTE: Super-resolution and Future Time Extrapolation for time-dependent PDEs

5. Patrick Wyrod (UCSC): Joint Diffusion Models for Multiscale Chaotic Dynamics

Scientific Computing for Life Sciences

1. Shahram Emami (UC Merced): Continuous Time Markov Chain Kinetic Model of Transcription Factor Binding to DNA

2. Vincent Lovero (UC Davis): Bifurcation Structure of Traveling Wave Solutions in Electrophysiological Models of Cardiac Tissue

3. Silvia Crivelli (LBL): Energy-Efficient LLMs for Advancing Precision Medicine

4. Alana Bailey (UC Davis): Optimizing Metachronal Paddling with Reinforcement Learning at Low Reynolds Number

5. Natalie Meacham (UC Merced): An Inverse Problem to Recover Sensitivity to Treatment in Cancerous Tumors

Conference Poster Presenters (Preliminary)

Ahmad Abassi (UCB): The Weakly Nonlinear and Semi-Analytic Theories and Computation of Finite-Depth Traveling Water Waves

Alaina Stockdill (UC Davis): Incorporating Species' Thermal Performance Curves into the Dynamics of Complex Food-Webs

Alexander Aghili (UCSC): TICA-Based Free Energy Matching in Coarse-Grained Machine Learning for Molecular Dynamics

Asees Kaur (UC Merced): Improving DSA Image Segmentation with CNNs

Brandon Imstepf (UC Merced): Accelerating Solutions of Nonlinear PDEs Using Machine Learning: A Case Study with the Two-Neuron Transport Model

Bryan Zhan (Burlingame HS): Neural Network Model of Wildfire Spread using Multi-image Mapping

Christopher J. Vogl (LLNL): Recent developments for coupling MFEM with structured AMR software libraries

Dani Ushizima (LBL): Advanced AI Systems for Microcapsule Synthesis

Gbocho Masato Terasaki (UC Merced): Reconstructing Patient-Specific Dynamics in Brain Tumor Growth with Deep Sequence Models

Hyun Lee (UC Davis): Pumping and Steady Streaming of Two-Frequency Oscillation

Irabiel Romero (UC Merced): An optimization-based approach for secure, safe, and economic operations of California power grid during wildfires

Isabella Cho (Orange County School of the Arts): ResNet-GAN Implementation of an FVM Tsunami Flooding Simulation on Arbitrary Topographies

Jan Nikl (LLNL): Hybridization framework for convection-diffusion systems in MFEM

Jeffrey Donatelli (LBL): Iterative Projection Framework for Solving Generalized Phase Problems from Nonuniform Fourier Data

John Gallagher (UC Merced): Conservative Hamiltonian Monte Carlo Methods: Theory and a Computational Example

Jonathan Forstater (UC Davis): E(3)-Equivariant Fragment-based Graph Neural Networks for Biomolecules

Kai Siang Hu (UC Merced): Analysis of Thymus Blood Vascular Network and Hemodynamic Profiles

Kayleigh Adams (UC Davis): Curvature of neural manifolds reveals a tradeoff in encoding strategy

Kelli E. Gutierrez (UC Davis): Analyzing Active Forces in Microswimmers

Kwassi Joseph Dzahini (ANL): A Noise-Aware Scalable Subspace Classical Optimizer for Quantum Approximate Optimization Algorithm

Kyle Wright (UC Merced): Groundwater modeling using gravity-gradient cartography

Larry Wigington (NPS): Solving Stochastic Linear Programs on GPUs

Lauren Mossman (UC Davis): The structure and dynamics of habitat-modifying interactions in marine food webs: non-trophic interactions in bioenergetic network models

Leonard Lupin-Jimenez (UCSC): Data driven forecast and downscaling for ocean dynamics.

Matthew Blomquist (UC Merced): Semi-Lagrangian Characteristic Reconstruction and Projection for Transport under Incompressible Velocity Fields

Michael A. Culp (ASU): Localized Elliptical Geometry to Support Sparse Coding

Minh Duc Hoang (UC Davis): Background firing rate of dopaminergic neurons modulates the dopamine response to stimuli

Niloofar Asefi (UCSC): Generative Lagrangian data assimilation for ocean dynamics at extreme

Olga Shapoval (LBL): Pseudospectral Particle-In-Cell Formulation with Arbitrary Charge and Current-Density Time Dependencies for the Modeling of Relativistic Plasmas

Pratham Lalwani (UC Merced): Compositional physics-informed neural flow

Salvador Ochoa Zavalza (UC Davis): Topological and Genomic Data Analysis Reveal FUT10 and UNC5D as Tumor Drivers in Breast Cancer

Satinderpreet Singh (UC Merced): Analyzing Reactive Fluctuating Hydrodynamics Simulations Using Structure Factors

Selma Emekci (Pioneer HS): Machine Learning Framework for Simulating Nanoscale Conductor Behavior in Complex Geometries

Shashwat Sharan (UC Merced): Vacuum dambreak of a dilute gas superfluid Bose-Einstein Condensate

Yibing Wang (UC Merced): Deep Learning Approaches for Colony Segmentation and Leafhopper Egg Quantification in Microscopy Images

Zihan Xu (UC Merced): Learning time trajectories of a stochastic dynamical system with a slowly varying parameter

Zixi Hu (LBL): A Multi-Tiered Iterative Algorithm for Reconstructing 3D Particle Structures from Non-Uniform Rotational Averages of Their Power Spectrum

Axel Huebl (LBL): Embedding AI/ML Surrogates in HPC GPU Simulations - From Python to C++ and Back

Fernando Mora (SJSU): Turbulence Investigations with Fluctuating Hydrodynamics

Jairo Martinez (SJSU): Non-Newtonian Hemodynamics of Capillary Networks

Kyle Lee Nguyen (SJSU): TRANSPORT PHYSICS IN FUSION ENERGY SIMULATIONS

Poorva Shukla (UCSB): Localization and Landscape Functions in Graph Laplacians

Prachi Gupta (LBL): KBase research assistant and annotation agent

Rachel Newton (Michigan): Optimality of POD for Data-Driven LQR with Low-Rank Structures

Samarth Sandeep (Iff Tech / UC Davis): Multi-Omics Could Be QMA-Hard

Tianyong Yao (Michigan): Spatial Pattern Formation in Eco-Evolutionary Games with Environment-Driven Motion

Fares Alazemi (Kuwait University): New Kolmogorov Bounds in the Clt for Random Ratios and Applications

Dibyakanti Kumar (U Manchester): Langevin Monte-Carlo Provably Trains Depth Two Neural Nets at Any Size and Data

Xingguang JIN (Chinese University of Hong Kong): Robust Multiscale Methods for Helmholtz equations in high contrast heterogeneous media

Dr. Ubaida Fatima (NED UET): Fuzzy Reading of Complexity: Addressing Uncertainties in Social Network Analysis with Graph Neural Networks

Ali Algefary (Qassim University): Common Riccati stability and time-delay systems

Humaira Hameed (U Strathclyde): On the word-representability of $K_m$-$K_n$ graphs

Gersena Banushi (UCB): A semi-analytical model for the dynamic analysis of buried Timoshenko beams under transverse ground vibration

Ruudy Mbouza Bayonne (Stanford): Reaction-Diffusion PDE Parameters Inference for Brain Oxygen Transport with Multiple Vascular Sources

Abdullah Shah (KFUPM): Numerical Methods for Phase-Field Modeling of Two-Phase Incompressible Flows

Yiheng Du (UCB): Data-driven simulation of three-dimensional turbulence using EddyFormer