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 centers on what I think of as “practical theory”: designing algorithms that are both theoretically grounded and effective on real-world problems. I am especially drawn to ideas that are simple, intuitive, and — at least to me — elegant. To me, being a theoretician is not only about accumulating theorems any more than being a writer is about piling up sentences. I work to understand core problems more deeply and explore when and why algorithms succeed or fail. As I continue to shape my research program, I hope to remain curious, learn from others, and contribute to the field with both rigor and creativity.