2026 Intro to HPC Bootcamp Projects

This project explores short-term load forecasting (STLF) using deep learning models to predict electricity demand in buildings, leveraging the BuildingsBench platform developed by the National Renewable Energy Laboratory. 

This project explores applying agentic workflows, guided AI prompting, and HPC to tackle the problem of molecular design and discovery for antibiotic resistance.

This project explores the intersection of AI and chemistry by using machine learning to design next-generation iron-based flow batteries.

This project will explore the application of machine learning and HPC to galaxy formation simulations.

This project explores the development of an end-to-end GPU-based simulation workflow to study neutrinos and help answer fundamental questions about the nature of matter and the evolution of the universe. 

This project will develop FireAID, a wildfire data analytics platform that leverages AI, deep learning, and high-performance computing to analyze multimodal data for improved wildfire risk assessment and management in Alaska.

The project explores how large language models can be used as a tool to identify and classify DNA function.

This project will explore training and using large language models for scientific applications. 

This project focuses on understanding and optimizing energy efficiency in High-Performance Computing (HPC) facilities, addressing the significant energy demands of modern computing systems. 

This project explores real HPC Workload data from fusion-related applications through analysis of compute and energy usage patterns to identify opportunities for optimization.