Xin Jiang
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Xin Jiang Assistant Professor Department of Industrial and Systems Engineering Email: xinjiang [AT] uh [DOT] edu |
I am looking for self-motivated graduate students and postdocs who are interested in optimization, machine learning, data science, and related topics. Please feel free to contact me.
Brief Biography
I am an Assistant Professor in Industrial and Systems Engineering at University of Houston. Previously, I was a postdoctoral researcher at in Cornell ORIE, hosted by Adrian S. Lewis, and Lehigh ISE, working with Frank E. Curtis. I obtained my Ph.D. degree in Electrical and Computer Engineering at UCLA, advised by Lieven Vandenberghe.
Research Interests
I am broadly interested in the mathematical foundations of data science, with primary focuses on theory and algorithms for large-scale optimization problems from engineering and data science and machine learning for graphical data. My research interests broadly include
Convex and nonconvex optimization
Distributed (and decentralized) optimization
Artificial intelligence and scientific machine learning (especially on graphical data)
Mathematical foundations of data science
My research focuses on what I think of as “practical theory”, for example, designing algorithms that are both theoretically principled and effective for real-world problems. I'm especially drawn to ideas that are simple, intuitive, and — at least to me — elegant. Being a theoretician isn't about collecting theorems, just like being a writer isn't about stacking sentences. I work to understand core problems more deeply and explore when and why algorithms succeed or fail. As I continue to develop my research program, I'm excited to stay curious, learn from others, and contribute to the filed with rigor and creativity.