## THANK YOU FOR

REGISTERING

### ZOOM LINK

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PLENARY SESSION 1

*Please note all times below are PDT (U.S. Pacific Daylight Time)*

8:30 AM

**Pramod Khargonekar Vice Chancellor for Research, UCI**

Introductions

8:45 AM

Keynote Address

**Stanley Osher **

*Innovations in Mean-Field Game Theory for Scalable Computation and Diverse Applications*

9:30 AM

**Kipton Barros**

*Automated discovery of a robust interatomic potential for aluminum*

10:00 AM

**Kieron Burke**

*Machine learning for electronic structure calculations and a new approach to warm dense matter simulations*

10:30 AM

Lighting Talks (Video Presentation)

** [ 15 Minute Break ] **

11:15 AM

Poster Session

## Poster Session by Topic and Breakout Room

### Breakout Room 1

**Extreme Physics, ****Fundamental Physics/Astronomy and Astrophysics**

**Irina Espejo -**Excursion - Active Learning and Gaussian Processes for black box inference**Jessica Howard -**Foundations of a Fast, Data-Driven, Machine-Learned Simulator**Evan Jones -**Tests of Catastrophic Outlier Prediction in Empirical Photometric Redshift Estimation with a Support Vector Machine**Bernadette Bosco -**Machine Learning in Astronomy: Galaxies ML**Anne-Katherine Burns -**A Machine Learning Solution to Computationally Intensive Problems in Big Bang Nucleosynthesis (BBN)

### Breakout Room 2

**Methods, Hardware/Software/Algorithms/ Mathematics**

**Eric Montoya -**Spin torque oscillators for spintronic neuromorphic computing**Tess Smidt -**e3nn: A modular PyTorch framework for 3D Euclidean neural networks**Truong Nguyen -**An Expectation-Maximization accelerator for unsupervised learning of adaptive Gaussian Mixture models**Jiayi****Li -**Tropical Geometry for Understanding Expressivity of Neural Networks**Yonatan****Dukler -**Optimization Theory for ReLU Neural Networks Trained with Normalization Layers

### Breakout Room 3

**Biophysics**

**Cameron Movassaghi -**Machine Learning Applications for Multiplexed Neurotransmitter Detection**Zixiao Zong -**Topological Models of Amyloid Fibril Formation, and Identification of Fibril Topologies from Fibrillization Kinetics**Elizabeth -**Diessner**:**Mapping the Mutational Landscape of the SARS-CoV-2 Main Protease: Molecular Modeling and Comparative Analysis**Eric Medwedeff -**Towards Scalable Simulation of Dynamical Graph Grammar Biological Models, a Natural Arena for ML Model Reduction**Cory Scott -**Efficient Learning of Cytoskeletal Dynamics with Multiscale Machine Learning and Optimized Projection Operators

### Breakout Room 4

**Many-body Physics**

**Mathieu Bauchy -**End-to-End Differentiability and TPU Computing to Accelerate Materials’ Inverse Design**Yu Song -**Deciphering the viscosity of nuclear waste immobilization glasses by deep learning**Azmain Abrawr Hossain -**Extracting Exciton Binding Energy using Regression Techniques**David Rosenberger -**Evaluating diffusion and the thermodynamic factor for binary ionic mixtures

### Breakout Room 5

**Weather and Climate; Science Image Analysis and Bio-image Analysis**

**Matthew Laffin -**Physics-Constrained Neural Networks for Large-Scale Inference of Subglacial Topography under Greenland and Antarctica**Griffin Mooers -**Generative Modeling of Atmospheric Convection**Nadia Ahmed -**Remote Sensing for Severe Weather Detection**Silvia Miramontes -**Accelerating Cell Counting with Quantitative Microscopy Based on U-Net

** [ 15 Minute Break ] **

PLENARY SESSION 2

12:30 PM

**Brian Spears **

*Cognitive Simulation: Combining simulation and experiment with artificial intelligence*

1:00 PM

**Stephan Mandt**

*Machine Learning and Physics: Bridging the Gap*

** [ 15 Minute Break ] **

1:45 PM

**Gowri Srinivasan**

*Combining Graph Theory and Machine Learning to Characterize Fractured Systems*

2:15 PM

**Eric Mjolsness**

*AI approaches to graph dynamics for multiscale computational science*