Email : sakhanna[at]ece.iitr.ac.in
Phone: +91-1332-28-4956
Room No. : S 215
My Google Scholar
My Website
Compressive Sensing, Inference and learning with sparse/deep generative models, Signal processing for communication and imaging, FMCW Radar Signal Processing
| From | To | Designation | Organisation |
|---|---|---|---|
| July 2007 | April 2016 | Design Engineer | Texas Instruments India Pvt. Ltd. |
| July 2018 | August 2020 | Postdoctoral Research Fellow | National University of Singapore |
| Sept 2020 | Now | Assistant Professor | Indian Institute of Technology Roorkee |
| Degree | Subject | University | Year Studied |
|---|---|---|---|
| B. Tech | Electrical Engineering | Indian Institute of Technology Kanpur | 2007 |
| Ph.D. | Electrical Communication Engineering | Indian Institute of Science | 2018 |
| Scheme | Sponsoring Agency | Other Faculties | Year Sponsored |
|---|---|---|---|
| Core Research Grant for project titled “Compressed Sensing-Based Ultra-High Resolution Automotive FMCW Radars” | SERB | 2024-27 |
Membership Details
IEEE, Member
| Topic | Scholar Name | Status of PhD | Registration Year |
|---|---|---|---|
| Compressed Sensing of R-Separable Data | Neha Singh | Ongoing | 2021 |
| To be decided | Prishail Mishra | Ongoing | Dec 2022 |
| To be decided | Namrata Saha | Ongoing | 2023 |
| Title | Place | Date Delivered |
|---|---|---|
| Joint tutorial talk with Prof. Chandra R. Murthy on “The surprising effectiveness of hierarchical Bayesian methods for sparse signal recovery” in Workshop on Stochastic Optimization in Networks and Related Topics | Indian Institute of Technology Bombay | 2018 |
| Sparsity-aware techniques for cross-interference cancellation in automotive FMCW Radars | Short Term Course on Advances in Communication and Signal Processing Techniques (ACST-2023) in NIT Kurukshetra | 2023 |
Journal Publications:
(J5) S. Khanna and C. R. Murthy, “On the Support Recovery of Jointly Sparse Gaussian Sources via Sparse Bayesian Learning,” in IEEE Transactions on Information Theory, vol. 68, no. 11, pp. 7361-7378, Nov. 2022.
(J4) S. Khanna and C. R. Murthy, “Sparse Recovery From Multiple Measurement Vectors Using Exponentiated Gradient Updates,” in IEEE Signal Processing Letters, vol. 25, no. 10, pp. 1485-1489, Oct. 2018.
(J3) S. Khanna and C. R. Murthy, “On the Restricted Isometry of Column-wise Khatri-Rao Product”, IEEE Transactions on Signal Processing, vol. 66, no. 5, pp. 1170-1183, Dec. 2017.
(J2) S. Khanna and C. R. Murthy, “Communication Efficient Decentralized Sparse Bayesian Learning of Joint Sparse Signals”, IEEE Transactions on Signal and Information Processing over Networks, vol. 3, no. 3, pp. 617–630, Nov. 2016.
(J1) S. Khanna and C. R. Murthy, “Decentralized Joint-Sparse Signal Recovery: A Sparse Bayesian Learning Approach”, IEEE Transactions on Signal and Information Processing over Networks, vol. 3, no. 1, pp. 29–45, Sept. 2016.
Book Chapters:
(B1) G. Joseph, S. Khanna, C. R. Murthy, R. Prasad, S. Thoota, Sparsity-aware Bayesian inference and its applications, in Handbook of Statistics, vol. 47, pp. 161-207, 2022
Conference Proceedings:
(C8) D. Goel and S. Khanna, “Semi-NMF Regularization-Based Autoencoder Training for Hyperspectral Unmixing”, 30th National Conference on Communications (NCC), Madras, India, 2024 (accepted).
(C7) N. Singh and S. Khanna, “Desketching of R-Separable Matrices From Compressive Linear Measurements,” 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP), Rome, Italy, 2023.
(C6) M. Singhal and S. Khanna, “Proximal Subgradient Descent Method for Cancelling Cross-Interference in FMCW Radars,” 2023 IEEE Statistical Signal Processing Workshop (SSP), Hanoi, Vietnam, 2023, pp. 225-229.
(C5) S. Khanna and V. Y. F. Tan, “Economy Statistical Recurrent Units for Inferring Nonlinear Granger Causality”, International Conference on Learning Representations (ICLR), 2020, Addis Ababa.
(C4) S. Khanna and C. R. Murthy, “Renyi Divergence Based Covariance Matching Pursuit of Joint Sparse Support”, IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2017, Sapporo, pp. 1-5.
(C3) S. Khanna and C. R. Murthy, “Decentralized Bayesian learning of jointly sparse signals”, IEEE GLOBECOM Conference, Austin, TX, 2014, pp. 3103-3108.
(C2) J. Tangudu, K. Ramasubramanian, K. Subburaj, S. Khanna and S. Chomal, “Techniques to enhance GNSS signal acquisition and tracking sensitivity”, International Conference on Indoor Positioning and Indoor Navigation, Montbeliard-Belfort, 2013, pp. 1-10.
(C1) H. Snoussi and S. Khanna and D. Hewson and J. Duchene, “Number of Sources Uncertainty in Blind Source Separation”, 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, 2007, pp. 6515-6518.
(July 2022 – Present)
1. A. K. Chowdhary and D. Sikdar, A Passive Radiative Cooler System, App. No: 202231043104 (filed on July 27, 2022)
2. T. Bhowmik, A. K. Chowdhary, and D. Sikdar, Frequency-scalable Polarization-insensitive Dual-mode Electro-Optic modulators, App. No: 202231066529 (filed on November 19, 2022)