JK Lakshmipat University

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Ankur Sharma
Institute of Engineering and Technology

Ankur Sharma

Ankur Sharma

Assistant Professor
Institute of Engineering and Technology

Area/ Specialisation

 Computer Vision and Image Processing Bayesian Statistics Theoretical Foundations of Computation



Member of JKLU faculty since

10th Nov 2022

Profile Links


  • MS (Computer Science) from University of North Carolina at  Chapel Hill, USA.
  • MA (Statistics) from Yale University, USA.
  • B.Tech.(Electrical Engineering) from IIT Kanpur.


Mr. Ankur Sharma is Assistant Professor in the Department of Computer Science and Engineering at Institute of Engineering and Technology, JKLU. He holds Master’s degrees in Computer Science and Statistics from UNC Chapel Hill and Yale University USA, and a B.Tech. in Electrical Engineering from IIT Kanpur. He has pursued research in various areas of Statistics and Computer Science at UNC and Yale.


Mr. Sharma is passionate about teaching. He has taught multiple courses at Yale and UNC as an instructor and a teaching assistant.

Teaching Interests
  • Algorithms and Theoretical Computer Science
  • Discrete Mathematics
  • Probability and its applications
  • Applied Statistics
  • Machine Learning, Computer Vision, Image and Signal Processing
  • C, C++ programming
  • Operating Systems
Research Interests
  • Computer Vision and Image Processing
  • Bayesian Statistics
  • Theoretical Foundations of Computation
Honours, Awards, and Affiliations
  • Leonard J. Savage Award for the best written work in the Yale Statistics department.
  • Perfect Score 1600/1600 in GRE (Sept 2007), and 337/340 in GRE (Sept 2014).
  • Sridhar Memorial Prize at IIT Kanpur.
  • JN Kapur Prize for Mathematical Excellence at IIT Kanpur.
  • Gold Medal in the Indian National Physics Olympiad 2003.
  • First rank in the Regional Mathematical Olympiad (Uttar Pradesh) in 2002.
  • Kishore Vaigyanik Protsahan Yojana (KVPY) fellowship awarded by the Govt of India.
Selected Publications

Stephen Pizer, …, Ankur Sharma, … et al. “Object Shape Representation via Skeletal Models (s-reps) and Statistical Analysis,” in Riemannian Geometric Statistics in Medical Image Analysis, no. (Xavier Pennec, Stefan Sommer, and Tom Fletcher, eds.), pp. 233-272, 2019.

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