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Naveen Kumar Dasanadoddi Venkategowda

Associate Professor

Naveen's current research focus is on wireless communications, internet-of-things (IoT), privacy and security in IoT, distributed learning and optimization.

Naveen K. D. Venkategowda is an Associate Professor (Universitetslektor) at the Department of Science and Technology and a part of the Communication Electronics group since Jan. 2021. From Oct. 2017 to Feb. 2021, he was postdoctoral researcher at the Department of Electronic Systems, Norwegian University of Science and Technology, Trondheim, Norway. He was a Research Professor at the School of Electrical Engineering, Korea University, South Korea from Aug. 2016 to Sep. 2017. Naveen received Ph.D. in electrical engineering from Indian Institute of Technology Kanpur, India, in 2016 and B.E. in electronics and communication engineering from Bangalore University, India, in 2008. He was a recipient of the TCS Research Fellowship (2011-15) from TCS for graduate studies in computing sciences, the ERCIM Alain Bensoussan Fellowship in 2017, and Runner up - Best Paper Award in Fusion 2020.

 

Google Scholar link: https://scholar.google.com/citations?user=t4PBVt0AAAAJ&hl=en

Recent Publications:

  • A. Moradi, N. K. D. Venkategowda, and S. Werner, “Total variation based distributed Kalman filtering  for resiliency against Byzantines,” IEEE Sensors, 2023.
  • M. Jafri, S. Srivastava, N. K. D. Venkategowda, A. K. Jagannatham, and L. Hanzo, “Cooperative hybrid transmit beamforming in cell-free mmWave MIMO networks,” IEEE Transactions on Vehicular Technology, 2023.
  • K. P. Rajput, P. Maity, S. Srivastava, V. Sharma, N. K. D. Venkategowda, A. K. Jagannatham, and L. Hanzo, “Robust linear hybrid beamforming designs relying on imperfect csi in mmWave MIMO IoT networks,” IEEE Internet of Things Journal, 2023.
  • A. Moradi, N. K. D. Venkategowda, S. P. Talebi, and S. Werner, “Privacy-preserving distributed Kalman filtering,” IEEE Transactions on Signal Processing, 2022

  • V. Hakansson, N. K. D. Venkategowda, S.Werner, and P. Varshney, “Optimal scheduling of multiple spatiotemporally dependent observations for remote estimation using age-of-information,” IEEE Internet of Things Journal, 2022.
  • C. Gratt‚on, N. K. D. Venkategowda, R. Arablouei, and S. Werner, “Privacy-preserved distributed learning with zeroth-order optimization,” IEEE Transactions on Information Forensics and Security, 2022.
  • M. F. Ahmed, K. P. Rajput, N. K. D. Venkategowda, K. V. Mishra, and A. K. Jagannatham, “Joint transmit and reflective beamformer design for secure estimation in IRS-aided WSNs,” IEEE Signal Processing Lett‚ers, 2022.
  • V. Håkansson, N. K. D. Venkategowda, S. Werner, and P. Varshney, “Optimal transmission-constrained scheduling of spatio-temporally dependent observations using age-of-information,” IEEE Sensors, vol. 22, no. 15, pp. 15 596–15 606, 2022.
  • R. Mirzaeifard, N. K. D. Venkategowda, and S. Werner, “Robust phase retrieval with non-convex penalties,” in 2022 56th Asilomar Conference on Signals, Systems and Computers, Nov. 2022, pp. 1–5
  • R. Mirzaeifard, N. K. D. Venkategowda, V. C. Gogineni, and S.Werner, “ADMM for sparse-penalized quantile regression with non-convex penalties,” in 29th European Signal Processing Conference (EUSIPCO), Aug. 2022.
  • R. Mirzaeifard, V. C. Gogineni, N. K. D. Venkategowda, and S. Werner, “Dynamic graph topology learning with non-convex penalties,” in 29th European Signal Processing Conference (EUSIPCO), Aug. 2022.
  • V. C. Gogineni, A. Moradi, N. K. D. Venkategowda, and S. Werner, “Communication-e€fficient and privacy-aware distributed LMS algorithm,” in 25th International Conference on Information Fusion (FUSION), Jul. 2022
  • A. Moradi, S. P. Talebi, N. K. D. Venkategowda, and S. Werner, “Securing the distributed Kalman filter against curious agents,” in 24th International Conference on Information Fusion (FUSION), Nov. 2021.
  • K. P. Rajput, M. F. Ahmed, N. K. D. Venkategowda, A. K. Jagannatham, G. Sharma, and L. Hanzo, “Robust decentralized and distributed estimation of a correlated parameter vector in MIMO-OFDM wireless sensor networks,” IEEE Transactions on Communications, 2021.
  • K. P. Rajput, Y. Verma, N. K. D. Venkategowda, A. K. Jagannatham, and P. K. Varshney, “Robust linear transceiver designs for vector parameter estimation in MIMO wireless sensor networks under CSI uncertainty,” IEEE Transactions on Vehicular Technology, 2021.
  • V. Håkansson, N. K. D. Venkategowda, and S. Werner, “Optimal transmission threshold and channel allocation strategies for heterogeneous sensor data,” in 2021 55th Asilomar Conference on Signals, Systems and Computers, Nov. 2021.
  • A. Moradi, S. P. Talebi, N. K. D. Venkategowda, and S. Werner, “Distributed Kalman filtering with privacy against honest-but-curious adversaries,” in 2021 55th Asilomar Conference on Signals, Systems and Computers, Nov. 2021.
  • B. D. Barros, N. K. D. Venkategowda, and S. Werner, “Quickest detection of stochastic false data injection attacks with unknown parameters,” in IEEE Statistical Signal Processing Workshop (SSP), Jul. 2021.
  • C. Gratton, N. K. D. Venkategowda, R. Arablouei, and S. Werner, “Distributed learning with non-smooth objective functions,” in Proc. 27th European Signal Processing Conference (EUSIPCO), Jan. 2021.

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