Manjesh Kumar Hanawal is an Associate Professor at the Industrial Engineering and Operations Research (IEOR) center of IIT Bombay , India. His academic journey includes a Ph.D. from University of Avignon/INRIA (2013), M.Sc (Engg) from IISc Bangalore (2009), and B.E. from NIT Bhopal (2004). Pre-Ph.D. work: Scientist-B at DRDO's CAIR Postdoctoral: Boston University (2013-2015) Appointed as first Professor-In-Charge of TCA2I center Research focuses on Machine Learning algorithms for limited feedback environments, Communication Networks resource allocation, and Cybersecurity threat detection. Publications span top venues like IEEE Transactions, NeurIPS, INFOCOM, and AISTATS. Recent work trends include: Bandit algorithms for distributed learning in heterogeneous networks Contextual information integration in sequential selection Energy efficiency optimization in wireless sensor networks Net neutrality violation detection frameworks Anti-jamming countermeasures in cognitive networks Scientific recognition includes the SERB Early Career Research Award (2019-2022) for machine learning applications in wireless networks. Advisees include Ph.D. awardee Arun Verma and Best Masters Thesis Awardee Sayan Chatterjee.
Supratik Chakraborty serves as the Bajaj Group Chair Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He maintains dual affiliations with the Centre for Formal Design and Verification of Software and the Centre for Liberal Education at IIT Bombay, demonstrating his cross-disciplinary engagement. Professor Chakraborty's research spans formal methods with focus on formal verification, rigorous analysis of system models, and automated synthesis of systems from specifications. His work bridges theoretical foundations with practical applications, particularly in developing mathematically provable guarantees for increasingly complex hardware, software, and intelligent systems. Current research interests include constrained counting and sampling, scalable formal verification of software and hardware systems, automated synthesis of programs and circuits, and applications of automata, logic and finite model theory to practical verification challenges. His publication trajectory shows a significant evolution from traditional hardware and software verification toward addressing verification challenges in machine learning and AI systems. Recent work increasingly focuses on interpretability of black-box models, verification of neural networks, and synthesis techniques applicable to intelligent systems. The research demonstrates strong interdisciplinary connections between formal methods, programming languages, and artificial intelligence. IIT Bombay Excellence in Thesis (CSE) Award 2011 (for Bhargav Gulavani's thesis) IIT Bombay Excellence in Thesis (CSE) Award 2017 (for Abhisekh Sankaran's thesis) Best Paper in Algorithms and Architecture track at IEEE International Conference on Computer Design: VLSI in Computers and Processors, 1998 Professor Chakraborty has successfully supervised 11 doctoral students, with research spanning formal verification techniques, Boolean functional synthesis, constrained counting, and applications to hardware and software systems. His students have gone on to positions at major institutions including Microsoft Research, TCS Research, Georgia Tech, and BARC, reflecting the strong industry and academic impact of his mentorship. Current research directions show increasing emphasis on verification challenges posed by machine learning systems and AI. His research group at IIT Bombay, while not explicitly named in the materials, appears to focus on formal methods with strong connections to the Centre for Formal Design and Verification of Software. The group maintains active collaborations with international researchers including Moshe Y. Vardi at Rice University, and has made significant contributions to verification tools like VeriAbs that bridge theoretical advances with practical applications.
S. C. Srivastava is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur) and serves as the Director of the IIT Kanpur-La Trobe University Research Academy, highlighting his leadership in international academic collaboration. Dr. Srivastava earned his PhD in Electrical Engineering from IIT Delhi in 1987 and completed his B.Tech from Banaras Hindu University in 1976. His research spans power system dynamics & stability studies, optimal power dispatch and state estimation, security analysis and control, smart grid technologies, and renewable energy integration including DC and AC micro-grids. His publication record shows consistent research output through 2018 with significant contributions to power system state estimation, microgrid protection, and wide area control systems. His work demonstrates a clear progression toward addressing contemporary challenges in power systems, particularly renewable integration and smart grid applications. Malaviya Award for Excellence in Power Systems (2018) Prof GK Dubey Memorial IEEE UP Section Life Time Achievement Award (2016) The Life time Achievement Award for Academic Excellence (2016) Dr. Srivastava serves in influential advisory roles including Chairman of the Expert Committee on Mission Innovation in Smart Grids (DST, New Delhi) and Member of the R&D Advisory Committee of NETRA, NTPC. His leadership in the IIT Kanpur-La Trobe University Research Academy demonstrates ongoing commitment to addressing global energy challenges through international collaboration.
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.
Indian Institute of Technology Hyderabad (IITH)India
Kishalay Mitra is a Professor at the Indian Institute of Technology Hyderabad , with affiliations to the Department of Chemical Engineering , Department of Climate Change , and Department of Artificial Intelligence . He also holds visiting professorships at Washington University in St. Louis and University of Washington, Seattle . His work in the Global Optimization & Knowledge Unearthing Laboratory (GOKUL) spans interdisciplinary optimization, machine learning, and their applications in industrial-scale engineering problems. Education : Ph.D. from IIT Bombay. Research Interests : Mitra's research focuses on optimization under uncertainty , surrogate modeling , multi-objective optimization , and integrating machine learning with physics-based models . His work addresses real-world challenges in wind energy , bioenergy supply chains , chemical process control , nanoscience , and environmental modeling (e.g., PM10 spatiotemporal analysis, forest fire prediction, and carbon capture). Article Trends : His recent publications emphasize wind energy systems (layout optimization, yaw control, forecasting), materials science (precipitate growth prediction, polymerization), and industrial processes (crystallization, grinding circuits). Techniques include neural operators , Bayesian optimization , generative adversarial networks (GANs) , and explainable AI .
Dr. Prabodh Bajpai is a Professor in the Department of Sustainable Energy Engineering at the Indian Institute of Technology Kanpur. Previously, he served as an Associate Professor at the same department from July 2022 to December 2022, and before that at the Electrical Engineering Department of IIT Kharagpur from July 2014 to June 2022. He began his academic career as an Assistant Professor at IIT Kharagpur from June 2008 to July 2014. His educational background includes a Ph.D. in Electrical Engineering (Power Systems) from IIT Kanpur (2008), M.Tech in Energy Studies from IIT Delhi (2001), and B.E. in Electrical Engineering from IIT Roorkee (1997). Dr. Bajpai's research spans renewable energy integration, power system operation and control, microgrid technologies, and smart grid applications. His work focuses on practical implementation of sustainable energy solutions with emphasis on power electronics, energy storage, and grid stability. He has made significant contributions to the fields of distributed generation integration, protection schemes for renewable-rich systems, and energy management in microgrids. His recent publications show a strong focus on DC microgrids, multi-port power converters, and advanced control strategies for renewable integration. The research demonstrates increasing sophistication in power electronics applications for sustainable energy systems, with particular emphasis on practical implementations for commercial and agricultural applications. Dr. Bajpai actively mentors graduate students, currently supervising seven students across PhD and M.Tech programs. His teaching portfolio includes core courses in electrical power engineering, renewables-integrated smart power systems, and energy systems modeling and analysis at IIT Kanpur, building on his extensive teaching experience at IIT Kharagpur where he developed several new courses in renewable energy systems. His research group maintains a Hybrid AC/DC Microgrid test facility and has developed a Renewable Hybrid Energy Power Plant for stand-alone applications, demonstrating his commitment to translating theoretical research into practical implementations.
Somnath Basu is a Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay. He has been serving in academic roles since 2011, progressing from Assistant Professor to Associate Professor and then to Professor in 2022. His work is deeply rooted in process metallurgy and materials engineering, with a focus on industrial steelmaking technologies. His research interests include metal refining , thermodynamics of slag-metal reactions , phosphorus and sulfur removal , and continuous casting processes . He also explores nanofluids and their transport properties, indicating interdisciplinary engagement. His work bridges fundamental thermodynamic studies with practical industrial applications in iron and steel production. The selected publications reflect a strong trend in steelmaking process optimization , particularly in reaction kinetics , inclusion behavior , and process monitoring . His research spans both experimental investigations and thermodynamic modeling, targeting improvements in steel purity and casting efficiency. Scientific Contributions: Published in leading journals such as ISIJ International , Steel Research International , and Metallurgical and Materials Transactions B . Contributions to understanding phosphorus partitioning, nozzle clogging, and nanofluid conductivity. While no specific students or grants are listed, his long-standing academic position and publication record suggest active supervision of graduate research and involvement in funded projects related to metallurgical process innovation. His work likely supports both academic and industrial advancements in steel technology. He is affiliated with a leading research department equipped with advanced facilities for metallurgical experimentation and process simulation, though specific lab names or team structures are not mentioned in the text.
Indranil Chowdhury is an Assistant Professor in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur. He holds a Ph.D. from Tata Institute of Fundamental Research, Centre for Applicable Mathematics in Bengaluru (2017) and has previously served as a Postdoctoral Researcher at University of Zagreb, Croatia (2020-2022) and Norwegian University of Science and Technology, Trondheim, Norway (2018-2020). Ph.D: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2017) PG: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2012) UG: St. Xavier's College, Kolkata, India (2010) Dr. Chowdhury's research focuses on the theory and numerical analysis of partial differential equations, with particular expertise in nonlocal and fractional order problems and fully nonlinear equations. His work bridges theoretical mathematics with practical applications in areas such as mean field games, optimal control, and mathematical modeling. His research program demonstrates a consistent trajectory of advancing the mathematical understanding of complex nonlocal phenomena through rigorous analytical techniques and innovative numerical methods. His publication record reveals a strong focus on fractional calculus, nonlocal diffusion processes, and mean field games. The research shows progression from foundational work on fractional Poincaré inequalities to increasingly sophisticated studies of fully nonlinear mean field games with both local and nonlocal diffusions. His recent work (2023-2025) demonstrates continued innovation in the field, particularly in addressing strongly degenerate cases and establishing precise error bounds for numerical approximations. Dr. Chowdhury maintains an active research program with consistent publication output in high-impact journals such as Foundations of Computational Mathematics, SIAM Journal on Numerical Analysis, and Discrete and Continuous Dynamical Systems. His collaborative work with researchers across international institutions reflects the global significance of his contributions to the field of nonlocal partial differential equations.
Gururaj Mirle Vishwanath is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. His research focuses on the integration of renewable energy sources into power systems, with particular emphasis on grid stability and control mechanisms. His educational background includes a PhD from IIT Roorkee (2020), an M.Tech from NITK Surathkal (2015), and a B.Tech from Visveswariah Technological University Belgaum (2009). Dr. Vishwanath's research interests span renewable energy integration challenges, machine learning applications to power systems, power converters for electric vehicles, power electronics applications to power systems, and microgrid control including black out scenarios, islanded operation, and energy management systems. His work addresses critical challenges in modern power systems as they transition toward greater renewable penetration. His recent publications demonstrate a strong focus on microgrid control architectures, voltage regulation schemes, and integration of wind energy systems with the grid. The research spans both theoretical control algorithms and practical implementation challenges for power system stability and reliability in the presence of renewable energy sources. Dr. Vishwanath works within the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where his research contributes to advancing power system technologies for the evolving energy landscape.
Dr. Triratna Muneshwar is an Assistant Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay (IIT Bombay), where he has been serving since November 2021. His research focuses on advanced thin film deposition techniques, particularly atomic layer deposition (ALD) and atomic layer etching (ALE), for next-generation semiconductor devices. Ph.D. in Materials Engineering, University of Alberta, Canada (2014) Dual Degree (B.Tech & M.Tech) in Metallurgical Engineering and Materials Science, IIT Bombay (2009) His research interests lie at the intersection of materials science and semiconductor technology, with a strong emphasis on modeling and experimental analysis of vacuum thin film processes. He investigates atomic layer deposition of oxides, nitrides, and metals, surface reaction kinetics , dopant distribution in thin films , and parasitic reactions in high-aspect-ratio structures . His work bridges lab-scale innovation to industrial fabrication (Lab-to-Fab). Dr. Muneshwar's publications reveal a consistent focus on improving the precision, efficiency, and scalability of ALD processes. His work spans plasma-enhanced ALD , precursor chemistry , in-situ characterization , and numerical modeling of growth mechanisms. Key themes include precursor utilization optimization, nucleation control, and material characterization for logic and memory applications. Scientific recognitions include: Featured Article, Journal of Applied Physics (2016) Editors Pick, Journal of Applied Physics (2018) U.S. Patent on precursor utilization in pulsed ALD processes Dr. Muneshwar has mentored research at the postdoctoral and associate levels and continues to build a research program involving graduate students and collaborative projects. His prior experience includes a Postdoctoral Research Fellowship and Research Associate role at the University of Alberta. He is actively involved in advancing ALD/ALE technologies with industrial relevance. His research is conducted within the MEMS department at IIT Bombay, leveraging advanced fabrication and characterization facilities. He collaborates with teams working on semiconductor materials, nanofabrication, and process modeling, contributing to India's growing expertise in microelectronics and advanced materials.
Arijit Chakrabarty is a Professor at the Theoretical Statistics and Mathematics Unit of the Indian Statistical Institute, Kolkata, India. His research focuses on random matrix theory, heavy-tailed distributions, large deviations, and long-range dependence. He can be reached via email at arijit.isi@gmail.com. Research Interests: Random matrix theory, Heavy-tailed distributions, Large deviations, Long-range dependence, Spectral analysis, Stochastic processes Publications Trends: His 15 most recent articles span random matrix theory, large deviations, Gaussian processes, and free probability. Key topics include eigenvalue analysis in random graphs, excursion lengths in Gaussian processes, and clustering of extremes in memory regimes. Lecture Notes: He has produced educational materials on Measure Theoretic Probability, Martingale Theory, and Probability Theory, partially in collaboration with Arup Bose and Rajat Hazra. These notes are accessible online and reflect his teaching contributions.
R.K. Shyamasundar is a Professor at the Indian Institute of Technology Bombay , with a focus on Real-Time and Reactive Programming, Logic Programming, Pi-Calculus, and Parallel Programs. Research spans formal verification, concurrency, and distributed systems. Key contributions include RT-CDL semantics, Esterel language extensions, and hybrid system controller synthesis. Scientific awards include JC Bose National Fellow, Fellowships at Indian Academy of Sciences and Indian National Science Academy, and Senior Membership in IEEE. His work involves collaborations with institutions like TCS Group and researchers such as Basant Rajan, N. Raja, and Deepak Kapur.
Indian Institute of Technology Hyderabad (IITH)India
Dr. V. Seshadri Sravan Kumar is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad. His research spans Power Engineering and Applied Mathematics, with a focus on Time and Frequency Domain Modeling, Electromagnetic Transients, Phasor and Frequency Estimation, and Machine Learning applications in power systems. Ph.D. and M.Sc.(Engg.) from IISc Bangalore Current research trends include Battery-Ultracapacitor Integration, Electric Vehicle Power Systems, and Non-ideal Component Modeling His group has contributed to 15 recent publications in journals like IEEE Transactions on Vehicular Technology, Renewable Energy (Elsevier), and conferences including IEEE PES General Meeting and PEDES. Key awards include the 2021 IIT Hyderabad Teaching Excellence Award and 2016 POSOCO Power System Award. Students mentored include Ph.D. candidates Sai Vinay Kishore N and alumni such as Anirudh C V S and Naresh Palla. He teaches graduate-level courses like Matrix Theory, Electrical Machine Analysis, and Modeling of Electromagnetic Transients.
Nishchal K. Verma is a Professor at the Department of Electrical Engineering, Indian Institute of Technology Kanpur. He holds a PhD from IIT Delhi (2007), an M.Tech from IIT Roorkee (2003), and a B.Tech from DEI Agra (1996). His postdoctoral research includes work at the University of Tennessee (2009) and Louisiana Tech University (2008). Specialization: Fuzzy Logic, Health Monitoring, Intelligent Informatics Current Research Interests: Intelligent Data Mining, Computer Vision, Smart Grids, Biomedical Applications His research focuses on Fuzzy Systems , Machine Learning , and Health Monitoring with applications to power systems, biomedical data, and wireless sensor networks. He has developed technologies like the Transducers and Instrumentation Virtual Laboratory and Brain Computer Interface Laboratory , emphasizing predictive modeling and fault diagnosis. Key sponsored projects include DST-funded Fuzzy Rule-Based Image Prediction and DRDO-supported Visual Surveillance Systems . His work spans 15+ years of interdisciplinary publications in journals and conferences. Scientific Awards : Devendra Shukla Young Faculty Research Fellowship (2013-16) He has served as Associate Editor for journals and Chairman of IEEE chapters, with leadership roles in academic administration at IIT Kanpur.
Joy Thomas M serves as an Assistant Professor at the Indian Institute of Science (IISc), Bangalore, with his office situated in Room 110 of the High Voltage Laboratory. His work falls under the broader electrical engineering domain at IISc, as evidenced by his course codes (E5/C22) and specialized research focus. His academic credentials include a Ph.D. and M.Sc. (Engg.) in High Voltage Engineering from IISc Bangalore, complemented by a B.Tech. in Electrical Engineering from IIT Varanasi. These qualifications form the foundation of his expertise in power systems engineering. Dr. Thomas's research portfolio demonstrates deep specialization in high-voltage phenomena and power infrastructure. Key areas include Gas Insulated Switchgear optimization, dielectric material behavior under extreme conditions, pulsed power applications, lightning protection systems, and plasma-based technologies. His work bridges theoretical electromagnetics with practical power transmission challenges, particularly in EHV/UHV systems and substation asset management. Notably, he integrates engineering pedagogy into his practice, reflecting commitment to educational methodology. Professional recognition includes IEEE Senior Membership, highlighting his standing in the electrical engineering community. Senior Member IEEE His instructional record covers advanced courses such as EHV/UHV Power Transmission Engineering (E5 213), High Voltage Engineering (E5 201), and Electromagnetic Compatibility (C 22). The absence of documented student advisement or grant details suggests either early-career status or unreported activities. Laboratory operations center on the High Voltage Laboratory facilities, enabling experimental validation of his research in controlled high-energy environments.
