Projects

Last update is on 10 April, 2024.

This page lists the projects I am working on or interested in.

Machine Learning for Particle Physics

• Language models for particle detectors. Language models have revolutionized natural language understanding. Particle detectors are complex apparatuses whose language is made of data organized in sub-detectors and readout modules. The project aims to train a language model that understands a detector’s vocabulary and can translate its raw data to higher-level constructs like clusters, tracks, jets, etc.

• Pattern recognition in a point cloud of measurements Scientific data are often represented as 3D points, each associated with measurements (like a point cloud). Pattern recognition in a point cloud of measurements is challenging due to its combinatorial complexity. The project aims to leverage deep learning models to solve the issue.

• Deep generative models for simulation. Particle simulations are often computationally expensive. The project aims to use deep generative models to simulate particle interactions with high fidelity and low computational cost.

• Anomaly detection in a point cloud of measurements. Representing learning is proven to be a powerful self-supervised learning technique. However, how to leverage the learned representation for anomaly detection in a point cloud of measurements is still an open question.