Dr Kumar Vijay Mishra of University of Maryland

Abstract:

The millimeter-wave (mm-Wave) massive MIMO communications/radar employ hybrid analog-digital beamforming architectures to reduce the cost-power-size-hardware overheads. Lately, there is also a gradual push to move from the millimeter-wave (mmWave) to Terahertz (THz) frequencies for short-range communications and radar applications to exploit very wide THz bandwidths. At THz, ultra massive MIMO is an enabling technology to exploit even wider bandwidth while employing thousands of antennas. The design of the hybrid beamforming techniques requires the solution to difficult nonconvex optimization problems that involve a common performance metric as a cost function and several constraints related to the employed communication regime and the adopted architecture of the hybrid system(s). There is no standard methodology for solving such problems and usually, the derivation of an efficient solution is a very challenging task. Since optimization-based approaches suffer from high computational complexity and their performance strongly relies on the perfect channel condition, we introduce deep learning (DL) techniques that provide robust performance while designing a hybrid beamformer. In this lecture, the audience will learn about applying DL to various aspects of hybrid beamforming including channel estimation, antenna selection, wideband beamforming, and spatial modulation. In addition, we will examine these concepts in the context of joint radar-communications architectures.

Biography:

Biography:

Kumar Vijay Mishra (S’08-M’15-SM’18) obtained a Ph.D. in electrical engineering and M.S. in mathematics from The University of Iowa in 2015, and M.S. in electrical engineering from Colorado State University in 2012, while working on NASA’s Global Precipitation Mission Ground Validation (GPM-GV) weather radars. He received his B. Tech. summa cum laude (Gold Medal, Honors) in electronics and communication engineering from the National Institute of Technology, Hamirpur (NITH), India in 2003. He is a Senior Fellow at the United States DEVCOM Army Research Laboratory; Research Scientist at the Institute for Systems Research, The University of Maryland, College Park under the ARL-ArtIAMAS program; Technical Adviser to Singapore-based automotive radar start-up Hertz well and Boston-based imaging radar startup Aura Intelligent Systems; and honorary Research Fellow at SnT - Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg. Previously, he had research appointments at the Electronics and Radar Development Establishment (LRDE), Defence Research and Development Organisation (DRDO) Bengaluru; IIHR – Hydro science & Engineering, Iowa City, IA; Mitsubishi Electric Research Labs, Cambridge, MA; Qualcomm, San Jose; and Technion - Israel Institute of Technology.

Dr. Mishra has served as the Distinguished Lecturer (DL) of various societies: IEEE Communications Society (2023-2024), IEEE Aerospace and Electronic Systems Society (AESS) (2023-2024, 2025-2026), IEEE Vehicular Technology Society (2023-2025, 2025-2027), IEEE Geoscience and Remote Sensing Society (2024-2025). He has been a Virtual DL of IEEE Future Networks Initiative (2022) and Traveling Lecturer of Optica (2025-). He is the recipient of the IEEE Signal Processing Society Pierre-Simon Laplace Early Career Technical Achievement Award (2024), Special Mention for the IEEE AESS M. Barry Carlton Award (2023), IET Premium Best Paper Prize (2021), IEEE T-AES Outstanding Editor (2021, 2023, 2024), U. S. National Academies Harry Diamond Distinguished Fellowship (2018-2021), American Geophysical Union Editors' Citation for Excellence (2019), Royal Meteorological Society Quarterly Journal Editor's Prize (2017), Viterbi Postdoctoral Fellowship (2015, 2016), Lady Davis Postdoctoral Fellowship (2017), DRDO LRDE Scientist of the Year Award (2006), NITH Director’s Gold Medal (2003), and NITH Best Student Award (2003). He has received Best Paper Awards at IEEE MLSP 2019 and IEEE ACES Symposium 2019. Dr. Mishra is Chair (2023-2026) of the International Union of Radio Science (URSI) Commission C, Chair (2025-) of IEEE AESS Technical Working Group on Integrated Sensing and Communications (ISAC-TWG), and Vice-Chair (2021-present) of the IEEE Synthetic Aperture Standards Committee, which is the first SPS standards committee. He has been Chair (2023-2025) of the IEEE SPS Synthetic Apertures Technical Working Group. He has been an elected member of three technical committees of IEEE SPS: SPCOM, SAM, and ASPS, and IEEE AESS Radar Systems Panel. He is Editor-in-Chief of River Rapids Series in Radar Systems, Signal Processing, Antennas and Electromagnetics (2025-). He has been Senior Area Editor of IEEE Transactions on Signal Processing (2024-), Associate Editor of IEEE Transactions on Aerospace and Electronic Systems (2020-) and IEEE Transactions on Antennas and Propagation (2023-). He has been a lead/guest editor of several special issues in journals such as IEEE Signal Processing Magazine, IEEE Journal of Selected Topics in Signal Processing, IEEE Journal on Selected Areas in Communications, and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. He is the lead co-editor of several books on signal processing and radar: Signal Processing for Joint Radar-Communications (Wiley-IEEE Press, 2024), Next-Generation Cognitive Radar Systems (IET Press Electromagnetics and Radar Series, 2023), Advances in Weather Radar Volumes 1, 2 & 3 (IET Press Electromagnetics and Radar Series, 2023), and Handbook of Statistics 55: Multidimensional Signal Processing (Elsevier). His research interests include radar systems, signal processing, remote sensing, and electromagnetics.

Email:

Address:University of Maryland, , College Park, United States, 20742