Imperial College London

Dr. Ayush Bhandari

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Senior Lecturer



+44 (0)20 7594 6233a.bhandari Website




802Electrical EngineeringSouth Kensington Campus





For details: Personal Website.

  • 2018: PhD, Massachusetts Institute of Technology
  • 2018: Lecturer/Asst. Prof. at Imperial College London
  • 2019: August-Wilhelm Scheer Visiting Professor
                 Department of Mathematics, TU Munich.
  • 2019: UKRI Future Leaders Fellowship (FLF).
  • 2021: Forthcoming Book
                 Computational Imaging (MIT Press) | Link | PDF
    Computational Imaging Book
  • Previously. Visiting Researcher at INRIA-Rennes, NTU Singapore, CUHK Hong Kong and EPFL Switzerland among other institutes.

My research revolves around the theme of Computational Sensing or how can we co-design hardware and mathematical algorithms so that popularly held limits in data capture and imaging can be broken.

  • Interested Postdoctoral researchers and PhD students can directly email me their CVs. For applying, please check the page on How to Apply.
  • MSc students interested in working with me can check the list of proposed thesis topics and setup a meeting via email.



Bhandari A, 2022, Back in the US-SR: unlimited sampling and sparse super-resolution with Its hardware validation, Ieee Signal Processing Letters, Vol:29, ISSN:1070-9908, Pages:1047-1051

Beckmann M, Bhandari A, Krahmer F, 2022, The Modulo Radon Transform: Theory, Algorithms, and Applications, Siam Journal on Imaging Sciences, Vol:15, ISSN:1936-4954, Pages:455-490

Fernandez-Menduina S, Krahmer F, Leus G, et al., 2022, Computational Array Signal Processing via Modulo Non-Linearities, Ieee Transactions on Signal Processing, Vol:70, ISSN:1053-587X, Pages:2168-2179

Florescu D, Bhandari A, 2022, Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation, Ieee Transactions on Signal Processing, Vol:70, ISSN:1053-587X, Pages:4912-4924

Florescu D, Krahmer F, Bhandari A, 2022, The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments, Ieee Transactions on Signal Processing, Vol:70, ISSN:1053-587X, Pages:616-630

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