Viveck received his Ph.D. from the University of California, Irvine in 2006. Between 2011 and 2014, he was a postdoctoral researcher, jointly with the Electrical and Computer Engineering Department at Boston University and the Research Laboratory of Electronics (RLE) at the Massachusetts Institute of Technology (MIT).
His research group focuses on the theoretical and mathematical foundations of several applications, most commonly using tools from information theory. His research interests include secure and privacy-preserving machine learning, cloud
storage and database services, and wireless networks. In addition to theoretical explorations, Viveck’s group conducts systems prototyping and implementations for several research projects.
He has been recognized with numerous awards, including the 2009 IEEE Information Theory Society Best Paper Award, the 2014 IEEE International Symposium on Network Computing and Applications (NCA) Best Paper Award, an NSF Career Award in 2016, and a 2019 Google Faculty Award. He is currently an associate editor for IEEE Transactions on Communications.
- Ph.D., Electrical and Computer Engineering, University of California, Irvine, 2012
- M.Tech, Electrical, Electronics, and Communications Engineering, Indian Institute of Technology, Madras, 2006
- B.Tech, Electrical Engineering, Indian Institute of Technology, Madras, 2006
Cadambe’s research focuses on information theory and its applications to communication networks. His work addresses fundamental limits of wireless networks, interference management, and network coding. He investigates new theoretical frameworks to enhance data transmission efficiency and reliability. The research actively involves the design and analysis of signaling strategies to optimize network capacity and performance in complex communication systems. Graduate and undergraduate student participation is integral to his research efforts.
Cadambe’s teaching is centered on foundational and advanced electrical and computer engineering courses at both undergraduate and graduate levels. His instruction emphasizes communication theory, signal processing, and network information theory. He integrates theoretical concepts with problem-solving techniques, fostering analytical skills in his students. Professor Cadambe’s teaching approach encourages active engagement and supports students’ development in both fundamental principles and research methodologies.
- 2009 Information Theory Society Best Paper Award
- 2014 NSF CRII Award
- 2016 NSF Career Award
- Google Faculty Award
- Member, IEEE
- S Vithana, VR Cadambe, FP Calmon, H Jeong, Correlated privacy mechanisms for differentially private distributed mean estimation, 2025 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 590–614, 2025
- H Hu, VR Cadambe, Differentially Private Secure Multiplication with Erasures and Adversaries, arXiv preprint arXiv:2504.21178, 2025
- S Vithana, VR Cadambe, FP Calmon, H Jeong, Differentially Private Distributed Mean Estimation with Constrained User Correlations, 2025 IEEE International Symposium on Information Theory (ISIT), 1–6, 2025
- S Acharya, PV Kumar, VR Cadambe, Chromatic Codes for Latency Optimal Geo-Distributed Storage, 2025 IEEE International Symposium on Information Theory (ISIT), 1–6, 2025
- S Acharya, PV Kumar, VR Cadambe, Latency-Optimal File Assignment in Geo-Distributed Storage with Preferential Demands, arXiv preprint arXiv:2507.12830, 2025