Pramod K. Varshney

Distinguished Professor

Electrical Engineering and Computer Science

3-173 CST



  • Ph. D. (Illinois) 1976

Areas of Expertise:

  • Distributed sensor networks and data fusion
  • Statistical inference
  • Wireless communications
  • Signal processing
  • Machine learning
  • Human-machine teaming

My research addresses fundamental questions in statistics-based signal processing, data/information fusion, sensor data processing, data analytics, machine learning and AI. My research has been generously funded for over four decades by Department of Defense, NSF, ARPA-E, EPA and many companies. Starting in the early 1980s, I have pioneered the area of data/information fusion and inference in sensor networks. While a lot of my work has been inspired by Department of Defense applications, I have also applied my research results to a wide variety of non-defense applications including IoT and health-related applications. For example, I have worked on imaging for breast cancer detection, and methods for more accurate Alzheimer disease detection. My current research includes detection and tracking, secure inference in distributed sensing systems, human-machine teaming for inference, and information fusion.

Honors and Awards:

  • ASEE Dow Outstanding Young Faculty Award, 1981
  • IEEE Fellow 1997
  • Third Millennium Medal IEEE 2000
  • President International Society of Information Fusion 2001.
  • Judith A. Resnik Award IEEE 2012
  • Doctor of Engineering honoris causa, Drexel University, 2014
  • Distinguished Alumni Award, ECE Department, Univ. of Illinois, 2015
  • Yaakov Bar-Shalom Award for a Lifetime of Excellence in Information Fusion, 2018
  • Claude Shannon-Harry Nyquist Technical Achievement Award, IEEE Signal Proc. Society, 2021
  • Pioneer Award, IEEE Aerospace and Electronic Society, 2021
  • Chancellor’s Citation for Lifetime Achievement, Syracuse University, 2023

Selected Publications:


  • P.K. Varshney, Distributed Detection and Data Fusion, Springer-Verlag, 1997.
  • G.L. Foresti, C. S. Regazzoni, and P. K. Varshney (eds.), Multisensor Surveillance Systems: The Fusion Perspective, Kluwer Academic Press, 2003.
  • K. Varshney and M. K. Arora (eds.), Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data, Springer Verlag, 2004.
  • A. Vempaty, B. Kailkhura and P. K. Varshney, Secure Networked Inference with Unreliable Data Sources,  Springer 2018

Selected Recent Papers

  • Li C., Wang Z., Wang X., and Varshney, P.K, “COMIC: An unsupervised change detection method for heterogeneous remote sensing images based on copula mixtures and Cycle-Consistent Adversarial Networks”, Elsevier Information Fusion, 2023
  • Dwivedi AK, Chaudhari S, Varshney N and Varshney, P. K., “Performance Analysis of LEO Satellite-Based IoT Networks in the Presence of Interference”, IEEE Internet of Things Journal, 2023
  • Li, C., Li, G., Wang, X. and Varshney, P.K., “A Copula-Based Method for Change Detection with Multi-sensor Optical Remote Sensing Images”, IEEE Trans. on Geoscience and Remote Sensing, September, 2023
  • Joseph, G., Zhong, C., Gursoy, M.C., Velipasalar, S. and Varshney, P.K., “Scalable and decentralized algorithms for anomaly detection via learning-based controlled sensing”, IEEE Trans. on Signal and Information Processing over Networks., Early Access, 2023
  • Zhang, G., Yi, W., Varshney, P.K., and Kong, L., “Direct Target Localization With Quantized Measurements in Noncoherent Distributed MIMO Radar Systems”, IEEE Trans. on Geoscience and Remote Sensing, pp. , Apr, 2023
  • Quan, C., Sriranga, N., Yang, H., Han, Y.S., Geng, B., and Varshney, P.K., “Efficient Ordered-Transmission Based Distributed Detection under Data Falsification Attacks”, IEEE Signal Process Letters, pp. 145 – 149, Feb, 2023
  • Hakansson, V.W., Venkategowda, N.K.D., Werner, S., and Varshney, P.K., “Optimal Scheduling of Multiple Spatiotemporally Dependent Observations for Remote Estimation Using Age of Information”, IEEE Internet of Things Journal, pp. 20308 – 20321, Oct, 2022
  • Sun, J., Yi, W., Varshney, P.K., and Kong, L., “Resource Scheduling for Multi-Target Tracking in Multi-Radar Systems With Imperfect Detection”, IEEE Trans. Signal Process, pp. 3878 – 3893, Jul, 2022
  • Lu, R., Chen, B., Sun, J., Chen, W., Wang, P., Chen, Y., Liu, H., and Varshney, P. K., “Heterogeneity-Aware Recurrent Neural Network for Hyperspectral and Multispectral Image Fusion”, IEEE Journal of Selected Topics in Signal Processing, pp. 649 – 665, Jun, 2022
  • Li, Q., Kailkhura, B., Goldhahn, R., Ray, P., and Varshney, P. K., “Robust Decentralized Learning Using ADMM With Unreliable Agents”, IEEE Trans. Signal Process, pp. 2743 – 2757, June, 2022
  • Trezza, A., Bucci, D. J., and Varshney, P. K., “Multi-Sensor Joint Adaptive Birth Sampler for Labeled Random Finite Set Tracking”, IEEE Trans. Signal Process, pp. 1010 – 1025, Feb, 2022
  • Yuan, Y., Yi, W., and Varshney, P. K., “Exponential Mixture Density based Approximation to Posterior Cramér-Rao Lower Bound for Distributed Target Tracking”, IEEE Trans. Signal Process, pp. 862 – 877, Feb, 2022
  • Chen, Q., Geng, B., Han, Y., and Varshney, P. K., “Enhanced Audit Bit Based Distributed Bayesian Detection in the Presence of Strategic Attacks”, IEEE Trans. on Signal and Information Process. over Networks, pp. 49 – 62, Jan, 2022
  • Bulusu, S., Khanduri, P., Kafle, S., Sharma, P., and Varshney, P. K., “Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations”, IEEE Trans. on Signal and Information Process. over Networks ., pp. 754 – 766, Nov, 2021
  • Cheng, X., Khanduri, P., Chen, B., and Varshney, P. K., “Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network”, IEEE Trans. Signal Process, pp. 5448 – 5462, Sept, 2021
  • Geng, B., Cheng, X., Brahma, S., Kellen, D., and Varshney, P. K., “Collaborative Human Decision Making with Heterogeneous Agents”, IEEE Trans. on Computational Social Systems., pp. 469 – 479, Jul, 2021
  • Li, C., Li, G., and Varshney, P. K., “Communication-Efficient Federated Learning Based on Compressed Sensing”, IEEE Internet of Things Journal., pp. 15531 – 15541, Apr, 2021
  • Geng, B., Li, Q., and Varshney, P. K., “Utility Theory Based Optimal Resource Consumption For Inference In IoT Systems”, IEEE Internet of Things Journal., pp. 12279 – 12288, Mar, 2021
  • Ciuonzo, D., Rossi, P.S., and Varshney, P. K., “Distributed Detection in Wireless Sensor Networks Under Multiplicative Fading via Generalized Score Tests”, IEEE Internet of Things Journal., pp. 9059 – 9071, Feb, 2021
  • Joseph, G., Nettasinghe , B., Krishnamurthy, V., and Varshney, P. K., “Controllability of Network Opinion in Erdos-Renyi Graphs Using Sparse Control Inputs”, SIAM Journal on Control and Optimization., pp. 2321-2345, Jan, 2021
  • Joseph, G. and Varshney, P. K., “Measurement Bounds for Compressed Sensing in Sensor Networks With Missing Data”, IEEE Trans. Signal Process., pp. 905-916, Jan, 2021