Tufts
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Usman A. Khan (bio)

Associate Professor, Electrical and Computer Engineering
Adjunct Professor, Computer Science
Tufts University


Office: 135 Halligan,
161 College Ave.,
Medford, MA 02155
Phone: (617) 627-5299
Email: khan AT ece DOT tufts DOT edu


Education

Postdoc, University of Pennsylvania, 2009-2010
Ph.D., Carnegie Mellon University, 2009 (graduation photo with Prof. José Moura)
M.S., University of Wisconsin-Madison, 2004
B.S., University of Engineering and Technology, Lahore-Pakistan, 2002

Research

My research interests lie in the areas of data and network science, systems and control, and optimization theory and algorithms with applications in autonomous multi-agent systems, Internet of Mobile Things (IoMTs), fleets of driverless vehicles, and smart-and-connected cities.

Highlights

  • Lead Guest Editor, Proceedings of the IEEE Special Issue on Optimization for Data-driven Learning and Control, vol. 118, no. 11, Nov. 2020
  • Technical Area Chair, Track C: Networks, Asilomar Conference on Signals, Systems, and Computers, Monterey, CA, Nov. 2020

  • Associate Editor, IEEE Open Journal of Signal Processing, 2019-present
  • Associate Editor, IEEE Transactions on Signal and Information Processing over Networks, 2019-present
  • Associate Editor, IEEE Letters to Control System Society, 2018-present

  • Guest Associate Editor, IEEE Letters to Control System Society Special Issue on Learning and Control, vol. 4, no. 3, Jul. 2020
  • Editor, IEEE Transactions on Smart Grid, 2014-2017

  • Guest Professor, ACCESS Linnaeus Centre, KTH Sweden, Spring 2015
  • NSF CAREER award, Jan. 2014
    My photo

Preprints

  • Feb. 2021: An improved convergence analysis for decentralized online stochastic non-convex optimization, to appear in IEEE Transactions on Signal Processsing. Arxiv; IEEE Xplore
  • Oct. 2020: Variance-reduced decentralized stochastic optimization with accelerated convergence, published in IEEE Transactions on Signal Processsing. Arxiv; IEEE Xplore
  • Aug. 2020: A general framework for decentralized optimization with first-order methods, published in the Proceedings of the IEEE. Arxiv; IEEE Xplore
  • Feb. 2020: Decentralized stochastic optimization and machine learning, published in IEEE Signal Processing Magazine. Arxiv; IEEE Xplore

  • Feb. 2021: A hybrid variance-reduced method for decentralized stochastic non-convex optimization. Arxiv
  • Nov. 2020: A fast randomized incremental gradient method for decentralized non-convex optimization. Arxiv
  • Aug. 2020: A near-optimal stochastic gradient method for decentralized non-convex finite-sum optimization. Arxiv
  • Aug. 2020: Push-SAGA: A decentralized stochastic algorithm with variance reduction over directed graphs. Arxiv

News

    JSTSP

Misc.




Electrical and Computer Engineering
School of Engineering
Tufts University