0000-0002-5793-6040 About
Dr. Suraj Srivastava (MIEEE, MIET) received the Ph.D. degree in Electrical Engineering from Indian Institute of Technology Kanpur, India, and M.Tech. degree in Electronics and Communication Engineering from Indian Institute of Technology Roorkee, India. From October 2022 to November 2023, he worked as a senior lead engineer in Qualcomm India Pvt. Ltd., where he was involved in the development of 5G-IoT modems. Previously, he was also employed as a Staff-I systems design engineer with Broadcom Research India Pvt. Ltd. and as a lead engineer with Samsung Research India, where he worked on designing Layer-2 of the 3G UMTS/WCDMA/HSDPA modems. He was awarded the prestigious Qualcomm Innovation Fellowship (QIF) twice for the years 2018 and 2022, and received the Outstanding Ph.D. Thesis award and Silver Medal from IIT Kanpur. In Dec-2023 he joined the Department of Electrical Engineering, Indian Institute of Technology Jodhpur, where he is currently an Assistant Professor. His research areas include Quantum Communications and Computing, Sparse Signal Processing in 5G Wireless Systems, mmWave and Tera-Hertz Communication, Orthogonal Time-Frequency Space (OTFS), Joint Radar and Communication (RadCom), Optimization and Machine Learning, Low resolution MIMO Communications, and Intelligent Reflecting Surface (IRS) Technology. He has published 50+ research papers in reputed IEEE journals and conferences.
Employment
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Indian Institute of Technology Jodhpur Assistant Professor2023 - Present
Education
Education history is unavailable.
Projects & Funding
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Publications (83)
- Amalgamated CHIRP and OFDM for ISAC Save
- Two-Stage Hybrid Transceiver Design Relying on Low-Resolution ADCs in Partially Connected MU Terahertz (THz) MIMO Systems Save
- Terahertz Beamforming and Group Sparse Channel Estimation Relying on Low-Resolution ADCs in MU Hybrid MIMO Systems Save
- Sequential Parameter Estimation for Beam-Squint Aware THz MIMO-OFDM ISAC Systems Save
- Semi-Blind Channel Estimation and Hybrid Receiver Beamforming in the Tera-Hertz Multi-User Massive MIMO Uplink Save
- Multi-Snapshot Deep Denoising for Channel Estimation in OTFS Modulated Systems Save
- Gaussian Mixture Model Based Bayesian Learning for Sparse Channel Estimation in Orthogonal Time Frequency Space Modulated Systems Save
- Bayesian Learning Aided Doubly-Selective Simultaneous Sparse CSI Estimation in Multi-User MIMO Systems Relying on Orthogonal Time Frequency Space Modulation Save
- Beam-Squint Aware Sparse Techniques for Massive MIMO-OFDM Integrated Sensing and Communication Save
- Multiple Measurement Vector Based Bayesian Learning for Simultaneously Sparse Time/Delay-Domain Channel Estimation in ADO-OFDM Visible Light Systems Save