Please join us in welcoming Prof. Qijia Jiang to GGAM!
Prof. Jiang studied Electrical Engineering, Statistics, and Applied Math at the undergraduate level at Rice, fascinated by quantitative approaches to understanding the natural world in general.
Prof. Jiang received a PhD from Stanford in Electrical Engineering in 2021, working mostly on optimization and signal processing related problems. Since then, Prof. Jiang has come to appreciate the potential of AI/ML in accelerating traditional numerical methods across science and engineering, as well as the power of data in transforming the way computational problems in physics and chemistry can be solved.
Prof. Jiang's current research interests include:
- Connection between optimization, MCMC sampling, dynamical system, interacting particle system
- Blending machine learning with traditional numerical algorithms for: PDE, sampling, optimal transport, control
- AI4Science: data-driven approaches to computational problems arising in physics & chemistry
We are thrilled to be adding another brilliant mind to GGAM!