I am a Research Scientist (Career) at the Lawrence Berkeley National Laboratory. I also lead the Robust Deep Learning Group at the International Computer Science Institute (ICSI), an affiliated institute of UC Berkeley. Prior to this role, I was an Assistant Professor (Tenure-Track) for Data-driven Modeling and Artificial Intelligence in the Department of Mechanical Engineering and Materials Science at the University of Pittsburgh, from September 2021 to December 2022. Before joining Pitt, I was a postdoctoral researcher in the Department of Statistics at UC Berkeley, where I worked with Michael Mahoney. I was also part of the RISELab in the Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley. Before that, I was a postdoc in the Department of Applied Mathematics at the University of Washington (UW), working with Nathan Kutz and Steven Brunton. I earned my PhD in Statistics at the University of St Andrews in December 2017. My MSc. in Applied Statistics is also from the University of St Andrews.

I am broadly interested in the intersection of deep learning, dynamical systems, and robustness—how can we build robust and intelligent dynamical systems that are computationally efficient and expressive? I am also interested in leveraging tools from randomized numerical linear algebra to build modern algorithms for data-intensive applications such as fluid flows and climate science. Projects in my group span the space between the development of robust and dynamical systems-inspired neural network architectures, efficient training strategies for extracting knowledge from limited data, and data-driven modeling of scientific data.