Shivaram Kalyanakrishnan is an Associate Professor at the Department of Computer Science and Engineering , Indian Institute of Technology Bombay , specialising in Artificial Intelligence and Machine Learning . His research spans sequential decision making , multiagent learning , multi-armed bandits , and humanoid robotics , with applications in robot soccer , computer games , and online advertising . He teaches advanced courses like CS 747: Foundations of Intelligent and Learning Agents and CS 748: Advances in Intelligent and Learning Agents , focusing on end-to-end system design and theoretical analysis. His scientific awards include the Best Student Paper Award at RoboCup International Symposium 2006 and nomination for Best Student Paper Award at AAMAS 2007 . His work on reinforcement learning and policy iteration has been published in leading venues such as IJCAI , ICML , and COLT , with recent contributions to railway scheduling and bandit algorithms. While no explicit list of advisees is provided, his research projects and publications suggest mentorship of students in collaborative efforts. Contact : shivaram@cse.iitb.ac.in .
Krishna Jagannathan is a full-time Professor in the Department of Electrical Engineering at the Indian Institute of Technology Madras (IIT Madras), India. He specializes in stochastic modeling, communication networks, information theory, and queuing theory. He obtained his B.Tech from IIT Madras in 2004, followed by S.M. and Ph.D. degrees from MIT in 2006 and 2010, respectively. After post-doctoral positions at Caltech and MIT, he joined IIT Madras in 2011. Education: B.Tech in Electrical Engineering, IIT Madras (2004) S.M. in Electrical Engineering and Computer Science, MIT (2006) Ph.D. in Electrical Engineering and Computer Science, MIT (2010) Research Interests: His research focuses on stochastic modeling and analysis of communication networks , information theory , and queuing theory . He has made significant contributions to understanding network performance, resource allocation, and risk-aware decision-making in complex systems. He leads the Networks and Stochastic Systems lab at IIT Madras, mentoring a large cohort of Ph.D. and M.S. students working on cutting-edge problems in networking, optimization, and stochastic systems. Scientific Awards: Best Paper Award at WiOpt 2013, Tsukuba, Japan Young Faculty Recognition Award for Excellence in Teaching and Research, IIT Madras (2014) Teaching & Mentorship: He has taught a wide range of courses including Probability Foundations , Stochastic Modeling and Queuing Theory , Convex Optimization , and Signals & Systems , consistently receiving high teaching evaluations. He has supervised over 15 Ph.D. and M.S. students to completion and continues to guide several active researchers.
Amit Mitra is a Professor in the Department of Mathematics & Statistics at the Indian Institute of Technology Kanpur (IIT Kanpur), India. He has held academic positions at IIT Kanpur since 2005, progressing from Assistant Professor (2005-2007) to Associate Professor (2008-2012) and Professor (2012-present). Prior to this, he served as an Assistant Professor at IIT Bombay (2002-2005) and held research roles at the Reserve Bank of India (1996-2002). His international collaborations include visiting positions at Uppsala University (Sweden) and universities in Australia and Cyprus. His educational qualifications include: Ph.D. in Statistics from IIT Kanpur (1996) M.Sc. in Statistics from IIT Kanpur (1991) B.Sc. (Honors) in Statistics from the University of Calcutta (1988) Professor Mitra's research centers on statistical signal processing with emphasis on parameter estimation for nonlinear time series models, particularly chirp signals, and data mining of financial/economic time series. His work develops robust algorithms for signal model estimation using techniques like genetic algorithms, M-estimators, and wavelet filtering, with applications in radar, sonar, finance, and image processing. He has pioneered methods for 1D/2D chirp signal analysis and volatility modeling in econometrics. His 15 most recent publications (2018-2023) reveal a sustained focus on advanced parameter estimation for chirp and sinusoidal models, with increasing attention to computational efficiency and real-world applicability. Key trends include the development of robust M-periodogram approaches, asymptotic analysis of quantile estimators, and extensions to multidimensional signal processing—particularly for image applications through nonnegative matrix factorization. His scientific awards include: Excellence in Teaching Award (2019, IIT Kanpur) Distinguished Teacher Award (2010, IIT Kanpur) M. N. Murthy Award from the Indian Statistical Institute (2002) Postdoctoral award from Swedish Foundation for Strategic Research (2000) Research award from National Board for Higher Mathematics (1992) Professor Mitra has supervised 67 students including 3 PhD candidates (1 completed), 4 M.Tech students, and 59 Masters students across Mathematics, Economics, and Statistics programs. His applied work includes consultancy projects with Politis (Cyprus) on market data modeling, Retailzoom (Cyprus) on retail analytics, and QuantLink Solutions (USA) on data mining software development for financial applications. No specific research labs or teams are mentioned in the provided text, though his patent in image processing (US Patent 9,940,868) indicates collaborative work with engineers on real-time display systems.
Ketan Rajawat is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in signal processing in communications and networks. His research and teaching focus on optimization algorithms, network measurement, localization, and network optimization within communication systems. He maintains an active research program with publications in top IEEE journals. Dr. Rajawat's research interests span optimization algorithms in communications, dynamic network measurement and cartography, network localization, and network optimization. His work bridges theoretical foundations with practical applications in wireless communications and networked systems. He has developed novel approaches for distributed estimation, matrix completion, and multidimensional scaling in network environments, contributing significantly to the field of signal processing for communication networks. His recent publications demonstrate a consistent research trajectory in distributed optimization techniques for communication networks, with a focus on wireless sensor networks, matrix completion, and asynchronous optimization methods. These works primarily appear in high-impact IEEE journals including IEEE Transactions on Wireless Communications and IEEE Transactions on Signal Processing, reflecting the quality and relevance of his research contributions to the field. Dr. Rajawat teaches courses in Convex Optimization, Networks, and Signals and Systems, providing students with both theoretical foundations and practical applications in electrical engineering. His office is located in ACES 305C at IIT Kanpur, where he conducts his research and academic activities.
Dr. Raghu Nandan Sengupta is a Professor at the Department of Management Sciences, Indian Institute of Technology Kanpur (IITK). With a Ph.D. from IIM Calcutta and a BE in Mechanical Engineering from BIT Mesra, he has held visiting positions at institutions including Princeton University, University of Warsaw, and Technische Universität Dresden. His academic leadership includes serving as Head of Department (2017-2020) and Chairman of GATE/JAM-2025. Research Focus: Sequential Estimation, Statistical Reliability Theory, Risk Analysis, Optimization Techniques in Finance, Meta Heuristic Algorithms, and Robust Optimization His publications span topics like reliability-based portfolio optimization , multiobjective decision-making , and brand sensitivity in B2B marketing . Key awards include DAAD Research Stays, EU-NAMASTE Erasmus Mundus Fellowship, and Indo-US S&T Forum Fellowship. He has advised 16 PhD students and contributed to editorial boards of journals including Sequential Analysis and Foundations of Computing and Decision Sciences . Scientific Awards: DAAD Research Stays (2017, 2015) EU-NAMASTE Erasmus Mundus Fellowship (2015) Indo-US S&T Forum Fellowship (2008) Erasmus Mundus Europe Asia Fellowship (2011) He has taught courses such as Probability and Statistics , Quantitative Methods for Decision Making , and Security Analysis & Portfolio Management at IITK, University of Warsaw, and IGIDR Mumbai. His work bridges statistical inference , financial engineering , and operations research , emphasizing practical applications in industry and academia.
