Mahdi Soltanolkotabi

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Mahdi Soltanolkotabi

Assistant Professor

Affiliation: Departments of Electrical and Computer Engineering and Computer Science University of Southern California

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Mahdi Soltanolkotabi is an assistant professor in the Ming Hsieh Department of Electrical and Computer Engineering and Computer Science at the University of Southern California where he holds an Andrew and Erna Viterbi Early Career Chair. Prior to joining USC, he completed his PhD in electrical engineering at Stanford in 2014. He was a postdoctoral researcher in the EECS department at UC Berkeley during the 2014-2015 academic year. Mahdi's research focuses on developing the mathematical foundations of nonconvex learning and optimization. This includes design and mathematical understanding of computationally efficient algorithms for optimization, machine learning, signal processing, high dimensional statistics, computational imaging and artificial intelligence. A particular focus on the application side has been on computational imaging and artificial intelligence.

Mahdi is the recipient of the Packard Fellowship in Science and Engineering, a Sloan Research Fellowship, an NSF Career award, an Airforce Office of Research Young Investigator award (AFOSR-YIP), and a Google faculty research award.

Research Interests

  • Statistical Learning and Inference

Author Of:

E. Candes , X. Li , M. Soltanolkotabi , "Phase Retrieval via Wirtinger Flow: Theory and Algorithms", IEEE Transactions on Information Theory, Apr. 2015