Project Proposals by University of Alabama in 2024

The University of Alabama is a public research university in Tuscaloosa, Alabama. Established in 1820, the University of Alabama is the oldest and largest of the public universities in Alabama as well as the flagship of the University of Alabama System

Project List

• Deep Learning Inference for mass regression

• Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger System

• Event Classification With Masked Transformer Autoencoders

• Superresolution for Strong Gravitational Lensing

• Expanding Strong Gravitational Lensing Simulations

• Search for Strong Gravitational Lenses

• Learning Representation Through Self-Supervised Learning on Real Gravitational Lensing Images

• Diffusion Models for Gravitational Lensing Simulation

• Physics-Guided Machine Learning

• Discovering and exploiting abstract symmetry elements obtained from low-level data within the CMS experiment

• Masked Auto-Encoders for Efficient End-to-End Particle Reconstruction and Compression for the CMS Experiment

• Self-Supervised Learning for End-to-End Particle Reconstruction for the CMS Experiment

• End-to-End Deep Learning Regression for Measurements with the CMS Experiment

• Diffusion models for Fast and accurate simulations of the low level CMS experiment data.

• Graph Representation Learning for Fast Detector Simulation

• Graph Transformers for Fast Detector Simulation

• Deep Graph anomaly detection with contrastive learning for new physics searches

• Learning Parametrization with Implicit Neural Representations

• Learning the Latent Structure with Diffusion Models

• Non-local GNNs for Jet Classification

• Continuous learning for high-energy physics data quality monitoring

• Optimal Transport in High Energy Physics

• Implementation of Quantum Generative Adversarial Networks to Perform High Energy Physics Analysis at the LHC

• Quantum Graph Neural Networks for High Energy Physics Analysis at the LHC

• Learning quantum representations of classical high energy physics data with contrastive learning

• Equivariant quantum neural networks for High Energy Physics Analysis at the LHC

• Quantum transformer for High Energy Physics Analysis at the LHC

• Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP

• State-space models for squared amplitude calculation in high-energy physics

• Evolutionary and Transformer Models for Symbolic Regression