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I am on the job market for tenure-track Assistant Professor, Research Scientist, or Research Staff.

I am a postdoctoral researcher in the Department of Applied Mathematics & Statistics. I am working with Mauro Maggioni on a research project which learns, in a non-parametric fashion, the governing structures of science/engineering based ODE/PDE driven dynamical systems from observation data.

Before my postdoc appointment at Hopkins, I was a doctoral student in the Applied Mathematics & Statistics, and Scientific Computing (AMSC) program at the University of Maryland. My thesis adviser was Eitan Tadmor (Wikipedia Page).

Research Interests

The main focus of my research is Scientific Machine Learning, which blends Scientific Computing and Machine Learning together. In particular, I design, develop and analyze algorithms to facilitate the need of making valid, useful and swift scientific discoveries from observation data. Oftentimes, I have to deal with data having enormous size, hence the algorithms have to be scalable and efficient. In order to design these algorithms with the desired properties, I use theories and techniques from machine learning, numerical ODE/PDE, scientific computing, approximation theory, inverse problems, probabilty and statistics.

Right now, I am considering the following problems:

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