Parthe Pandit

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Parthe Pandit

Ph.D. Candidate

Affiliation: University of California, Los Angeles, Department of Electrical and Computer Engineering, Department of Statistics.

Home page: https://parthe.github.io

Contact Information

 

Research Interests

  • Statistical Learning and Inference

Biography:

Parthe is a Ph.D. candidate at the University of California, Los Angeles (UCLA) in the Department of Electrical Computer Engineering. He is also working towards an MS degree in Statistics at UCLA. His research focusses on providing rigorous theoretical guarantees for computational and statistical aspects of Machine Learning and Deep Learning algorithms. He applies tools from large-scale optimization, statistical physics, and high dimensional statistics. 

He completed his B.Tech and M.Tech in Electrical Engineering from IIT Bombay, with a minor in Computer Science. Apart from Machine Learning, he has also published articles on problems in mechanism design, network economics, coding theory, graph theory, and music information retrieval. He is a recipient of the Jack K. Wolf best student paper award, the Guru Krupa Foundation fellowship, the J. N. Tata scholarship, and the K. C. Mahindra scholarship.

He has been a research intern with two teams at Amazon, working on problems in Natural Language Processing and Deep Generative modeling.

Author Of:

P. Pandit , M. Sahraee-Ardakan , "Asymptotics of MAP Inference in Deep Networks", Proceedings of the 2019 IEEE International Symposium on Information Theory, Paris, France, Jul. 2019