Zhe Bai
Lawrence Berkeley National Laboratory
Applied Mathematics and Computational Research
Biography
Zhe Bai is a computational science researcher in the Applied Mathematics and Computational Research Division of the Computing Sciences Area at Lawrence Berkeley National Laboratory. Her research interests lie in the area of data-driven modeling and model order reduction, including dynamic mode decomposition, scientific machine learning and sparse algorithms for large-scale computation and simulation. Cultivated interdisciplinary research and collaborations spanning the fields of computational science and engineering, her work focuses on AI-based modeling that couples first-principles with data-driven approaches to understand, estimate and control high-dimensional physical systems.
SRP Project Title
Sequential modeling of multi-scale dynamical systems
Topical Areas
Applied Computer Science; Applied Mathematics; Artificial Intelligence and Intelligent Systems; High Performance Computing
Abstract
This project develops advanced sequential models to analyze time-series data. The goal is to capture the complex, multi-scale, path-dependent relationships using historic event data. The model is expected to learn both short-term and long-term temporal patterns for an overall reliable forecast.
Desired Skills
Proficient in coding; experienced in optimizing neural networks; interested in transformers and/or high performance computing.
Lightning Talk Title
Sequential modeling of multi-scale dynamical systems
Keywords
Advanced sequential modeling; hierarchical learning; time series forecasting; dynamical systems.