Venugopal V. Veeravalli

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Education

• Ph.D. in Electrical Engineering, University of Illinois at Urbana-Champaign, October 1992
• M.S. in Electrical Engineering, (May 1987) Carnegie-Mellon University, Pittsburgh, PA
• B. Tech. (B.S.) in Electrical Engineering, (May 1985) Indian Institute of Technology, Bombay,

Biography

Prof. Veeravalli received the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1992, the M.S. degree from Carnegie-Mellon University in 1987, and the B.Tech degree from Indian Institute of Technology, Bombay (Silver Medal Honors) in 1985. He is currently the Henry Magnuski Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Illinois at Urbana-Champaign, where he also holds appointments with the Coordinated Science Laboratory (CSL), the Department of Statistics, and the Discovery Partners Institute (DPI). He was on the faculty of the School of ECE at Cornell University before he joined Illinois in 2000. He served as a program director for communications research at the U.S. National Science Foundation in Arlington, VA during 2003-2005. His research interests span the theoretical areas of statistical inference, machine learning, and information theory, with applications to data science, wireless communications, and sensor networks. He is a Fellow of the IEEE and a Fellow of the Institute of Mathematical Statistics. Among the awards he has received for research and teaching are the IEEE Browder J. Thompson Best Paper Award, the U.S. Presidential Early Career Award for Scientists and Engineers (PECASE), and the Abraham Wald Prize in Sequential Analysis (twice). He received the 2023 Fulbright-Nokia Distinguished Chair in Information and Communication Technologies.

Academic Positions

• Member (2019-present), Discovery Partners Institute
• Henry Magnuski Professor of ECE (2016-present), University of Illinois at Urbana-Champaign
• Professor (2016-present), Courtesy Appointment, Department of Statistics, University of Illinois at Urbana-Champaign
• Professor (2005-present), Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
• Professor (2005-present), Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign

Other Professional Employment

• Program Director, (2003-2005) CISE/CCF/TF, National Science Foundation.

Teaching Statement

Professor Veeravalli has taught undergraduate courses on communication systems, probability, signal and systems, and data science, and graduate courses on detection and estimation theory, information theory, communication theory, optimization, and wireless communication.

Research Statement

Veeravalli’s research interests span the theoretical areas of statistical inference, machine learning, and information theory, with applications to data science, wireless communications, sensor networks and cyberphysical systems.

Undergraduate Research Opportunities

Research Experience for Undergraduates (REU) supported by National Science Foundation (NSF) grants.

Research Interests

• Data Science
• Cyberphysical Systems
• Wireless Communication
• Sensor Networks
• Information Theory
• Detection and Estimation Theory
• Machine Learning
• Statistical Inference

Research Topics

• Cyberphysical systems and internet of things
• Cybersecurity and privacy
• Data science and analytics
• Decision science
• Machine learning
• Sensing systems
• Smart grid and energy delivery

Books Authored or Co-Authored (Original Editions)

• V.V. Veeravalli and A. ElGamal. “Interference Management in Wireless Networks.” Cambridge University Press, February 2018.
• P. Moulin and V.V. Veeravalli. “Statistical Inference for Engineers and Data Scientists.” Cambridge University, February 2019.

Chapters in Books

• V.V. Veeravalli and T. Banerjee. "Quickest Change Detection." In E-Reference Signal Processing. Elsevier, 2013. Also available at http://arxiv.org/pdf/1210.5552v1.pdf.
• V.V. Veeravalli. "Fundamentals of Detection Theory." In Mathematical Foundations for Signal Processing, Communications and Networking, T. Chen, D. Rajan, and E. Serpedin (Eds.), Cambridge University Press, 2011.
• S. Sundhar Ram, V. V. Veeravalli and A. Nedic, "Distributed and Recursive Estimation." In Sensor Networks: When Theory meets Practice, G. Ferrari, (Ed.), Springer 2010.
• V.V. Veeravalli and J.-F. Chamberland. "Detection in Sensor Networks." In Wireless Sensor Networks. Signal Processing and Communications Perspectives, A. Swami et al (Eds.), Wiley, 2007.

Selected Articles in Journals

• V.V. Veeravalli, G. Fellouris, and G.V. Moustakides. “Quickest Change Detection with Controlled Sensing.” IEEE Journal on Selected Areas in Information Theory, Special Issue Dedicated to the Memory of Toby Berger: Data, Physics, and Life Through the Lens of Information Theory, 2024.
• A. Magesh, V.V. Veeravalli, A. Roy, and S. Jha. “Principled Out-of-Distribution Detection via Mul- tiple Testing.” Journal of Machine Learning Research, 24(378):1-35, Nov 2023.
• A. Deshmukh, J. Liu and V.V. Veeravalli. “Robust Mean Estimation in High Dimensions: An Outlier- Fraction Agnostic and Efficient Algorithm.” IEEE Transactions on Information Theory, 69(7): 4675-4690, July 2023.
• Y. Liang, A.G. Tartakovsky and V.V. Veeravalli. “Quickest Change Detection with Non-Stationary Post-Change Observations.” IEEE Transactions on Information Theory, 69(5): 3400-3414, May 2023
• C. Wilson, Y. Bu, and V.V. Veeravalli. “Adaptive Sequential Machine Learning.” Sequential Analysis, Vol. 38, No. 4, 545-568, 2019.
• S. Zou, G. Fellouris, and V.V. Veeravalli.“Quickest Change Detection under Transient Dynamics: Theory and Asymptotic Analysis.” IEEE Transactions on Information Theory, 65(3): 1397-1412, March 2019
• Y. Bu, S. Zou, Y. Liang and V.V. Veeravalli. “Estimation of KL Divergence: Optimal Minimax Rate.” IEEE Transactions on Information Theory, 64(4): 2648 - 2674, April 2018.
• G. Rovatsos, X. Jiang, A.D. Dominguez-Garcia, and V.V. Veeravalli. "Statistical Power System Line Outage Detection Under Transient Dynamics." IEEE Transactions on Signal Processing, 65(11):2787-2797, June 2017.
• Y.C. Chen, T. Banerjee, A.D. Dominguez-Garcia, and V.V. Veeravalli. “Quickest Line Outage Detection and Identification.” IEEE Transactions on Power Systems, pp. 1 - 10, February 2015.
• V. S. Annapureddy and V.V. Veeravalli. "Gaussian Interference Networks: Sum Capacity in the Low Interference Regime and New Outer Bounds on the Capacity Region." IEEE Transactions on Information Theory, 55(7): 3032-3050, July 2009.
• S.S. Ram, A. Nedic and V.V. Veeravalli. "Incremental Stochastic Subgradient Algorithms for Convex Optimization." SIAM Journal on Optimization, 20 (2): 691-717, February 2009
• A.G. Tartakovsky and V.V. Veeravalli. "General Asymptotic Bayesian Theory of Quickest Change Detection." In SIAM: Theory of Probability and its Applications, vol. 49, no. 3, pp. 538-582, 2004.
• J.-F. Chamberland and V. V. Veeravalli, "Decentralized Detection in Sensor Networks," IEEE Transactions on Signal Processing, vol. 51, no. 2, pp. 407-416, February 2003. (IEEE Signal Processing Society 2006 Young Author Best Paper Award.)
• V. V. Veeravalli and A. Mantravadi, "The Coding-Spreading Tradeoff in CDMA Systems," IEEE JSAC: Special Issue on Multiuser Detection Techniques, vol. 20, no. 2, pp. 396-408, February 2002.
• V. V. Veeravalli, "Decentralized Quickest Change Detection," IEEE Transactions on Information Theory, 47(4): 1657-65, May 2001.
• V. Dragalin, A. G. Tartakovsky and V. V. Veeravalli, "Multihypothesis Sequential Probability Ratio Tests, Part II: Accurate Asymptotic Expansions for the Expected Sample Size," IEEE Transactions on Information Theory , 46(4): 1366-1383, July 2000.
• V. Dragalin, A. G. Tartakovsky and V. V. Veeravalli, "Multihypothesis Sequential Probability Ratio Tests, Part I: Asymptotic Optimality," IEEE Transactions on Information Theory. 45(7): 2448-2462, November 1999.
• C. W. Baum and V. V. Veeravalli, "A Sequential Procedure for Multihypothesis Testing," IEEE Transactions on Information Theory, 40(6): 1994-2007, November 1994. (The authors were awarded the 1996 IEEE Browder J. Thompson Award for this work.)

Journal Editorships

• Editor-in-Chief, IEEE Transactions on Information Theory, 2023-

Other Scholarly Activities

• Member of the Board of Governors of the IEEE Information Theory Society, 2023-present
• Technical Program Committee Co-Chair, IEEE International Symposium on Information Theory, Paris, France, 2018.
• General Co-Chair, IEEE International Symposium on Information Theory, Honolulu, Hawaii, June 2014.

Honors

• Fellow, Institute of Mathematical Statistics, 2024
• Abraham Wald Prize in Sequential Analysis, 2023
• Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, 2023
• Abraham Wald Prize in Sequential Analysis, 2016
• Fellow of the IEEE, 2006
• 1998  National Science Foundation CAREER Award
• 1998 Presidential Early Career Award for Scientists and Engineers (PECASE) by the White House to recognize outstanding research in wireless communications and for innovations in teaching. This is ``the highest honor bestowed by the U.S. government on outstanding new scientists and engineers who are in the early stages of establishing their independent research careers.''
  
• 1996 IEEE Browder J. Thompson Award, an award given to an outstanding paper by authors under the age of 30 selected from all the publications of the IEEE. The award winning paper: "A Sequential Procedure for Multihypothesis Testing."
  

Teaching Honors

• Michael Tien Excellence in Teaching Award, College of Engineering, Cornell University, 1999.

Research Honors

• Editor-in-Chief, IEEE Transactions on Information Theory, 2023-2025
• Xerox Award for Faculty Research, College of Engineering, University of Illinois, 2003.
• Beckman Associate of the Center for Advanced Study, UIUC, 2002-2003.

Recent Courses Taught

• ECE 313 (MATH 362) - Probability with Engrg Applic
• ECE 365 - Data Science and Engineering
• ECE 490 (CSE 441) - Introduction to Optimization
• ECE 500 U (ECE 500 U1, ECE 500 U2, ECE 500 U3) - ECE Colloquium
• ECE 561 - Detection & Estimation Theory
• ECE 561 - Statistical Inference ENG & DS
• ECE 562 - Advanced Digital Communication