Qijia Jiang [Chee-ja Jee-ang]

I am an Assistant Professor in the Statistics and Applied Mathematics departments at UC Davis (Fall 2024 - ).

I got my PhD in Electrical Engineering from Stanford under Emmanuel Candès in 2021, followed by postdoc at UT Austin and Berkeley. I spent my undergrad at Rice University, studying Electrical Engineering, Statistics and Applied Mathematics, fascinated by quantitative approaches to understand the natural world generally. After all these years, I think this is still what drives me, despite the excursion into several abstract places somewhere along the way.

Research

• Current Interests:
  • Theoretical connections between: optimization, MCMC sampling, dynamical system, interacting particle system (Mirror Langevin, Hamiltonian Monte Carlo)
  • Blending machine learning with traditional numerical algorithms for: PDE, sampling, optimal transport, control (Schrödinger Bridge, autodiff Spectral PDE solver)
  • AI for Science: data-driven approaches to computational problems arising in Physics + Chemistry (with an eye towards molecular dynamics & atomistic simulation)
  These themes, of course, overlap, and span the theory - application spectrum, as they should.
• As Google Scholar may suggest, I have also been curious about various topics in optimization, signal processing and statistics in the past.
• Some Slides related to past and current research

Teaching

• @UC Davis (as instructor): Introduction to Probability Theory
• @Stanford (as TA): High-dimensional Statistics, Convex Optimization, Machine Learning
• I had fun serving as a technical mentor for the Data Science for Social Good program at Stanford

Contact

• Email: qjang AT ucdavis DOT edu
• Office: Mathematical Sciences Building # 1129

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