Vineeth N Balasubramanian is a Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Hyderabad, with affiliate faculty status in the Department of Artificial Intelligence. His research focuses on the intersection of deep learning, machine learning, and computer vision, emphasizing explainability, robustness, and real-world applications. He leads Lab 1055, which investigates problems such as Explainable and robust AI/ML systems Lifelong learning in evolving environments Multimodal vision-language models Applications in agriculture, autonomous navigation, and human behavior analysis His recent work includes causal reasoning in transformers, vision-language model capabilities, and drone-based object detection. Funded by organizations like Google, Microsoft, Intel, and DST, he has received multiple awards including the World's Top 2% Scientists (2022-23), INSA/INAE Fellowships, and Best Paper recognitions. Lab 1055 collaborates with institutions like CMU, UBC, and Monash University, contributing to cutting-edge advancements in AI.
Aditya K. Jagannatham is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). With expertise in wireless communications and signal processing, he has established himself as a leading researcher in 5G/6G technologies, MIMO systems, and cognitive radio networks. His educational background includes: PhD in Electrical and Computer Engineering from UC San Diego (2007) M.S. in Electrical and Computer Engineering from UC San Diego (2004) B.Tech. in Electrical Engineering from IIT Bombay (2001) Professor Jagannatham's research primarily focuses on next-generation wireless communication systems, with special emphasis on 5G and 6G technologies. His work spans OTFS modulation, Terahertz communications, Visible Light Communication (VLC), Intelligent Reflecting Surface (IRS) technology, Massive MIMO, mmWave MIMO, Non-Orthogonal Multiple Access (NOMA), and Filter-Bank Multi-Carrier (FBMC) systems. His research integrates theoretical analysis with practical implementation challenges, addressing critical issues in modern wireless networks. His recent publications demonstrate a strong trend toward advanced signal processing techniques for next-generation wireless systems, particularly focusing on Sparse Bayesian Learning approaches for channel estimation, cooperative communication systems with energy harvesting capabilities, and millimeter wave MIMO technologies. His work bridges theoretical communication theory with practical implementation challenges in emerging wireless standards. Professor Jagannatham has received numerous prestigious awards and fellowships: Arun Kumar Endowed Chair Professorship (2019) Qualcomm Innovation Fellowship (2018) P.K. Kelkar Young Faculty Research Fellowship for excellence in research (2015-2018) IEEE Signal Processing Society travel grant to attend ICASSP 2015 Gopal Das Bhandari Memorial Distinguished Teacher Award (2012-13) Cal(IT)2 fellowship for graduate study at UC San Diego As an educator, Professor Jagannatham has received commendation letters from the Director of IIT Kanpur for excellence in teaching courses including EE624 Information and Coding Theory, EE670 Wireless Communications, and EE320 Principles of Communication Systems. His research has attracted significant funding, though specific grant details are not provided in the available information. He likely supervises graduate students working on cutting-edge wireless communication research. Professor Jagannatham is based in the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where he leads research in wireless communications. His work appears to be closely connected with the Center for Developing Intelligent Systems (CDIS) and other research centers at IIT Kanpur focused on next-generation communication technologies.
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.
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.
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 .
Om P. Damani is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He serves as Faculty In-Charge of the Sustainable Development unit of the Center for Policy Studies and is also associated with the Centre for Technology Alternatives for Rural Areas (CTARA). His work bridges computer science with social development challenges, focusing on practical applications for rural communities. Dr. Damani's research interests span Technology for Development of the bottom 80%, System Dynamics: Modeling and Simulation for Social Development, System Architecture, and Data Science. His work demonstrates how computational approaches can address complex development challenges through projects like GramDrishti (for detecting rural infrastructure in satellite images), JalTantra (for optimizing water distribution networks), and FAI (Farm Assessment Index for holistic farming practice evaluation). His publications reveal a consistent focus on applying computer science to solve real-world problems in water management, agricultural systems, and rural infrastructure. His research has been recognized with significant awards including the IIT Bombay Industrial Impact Award 2010, IIT Bombay Impactful Research Award 2019, and Best Poster Award at Agriculture Science Congress 2017. Dr. Damani has successfully translated theoretical research into practical tools that address development challenges, particularly in water resource management and agricultural systems. As an educator, he has mentored numerous PhD students including Chintan Tundia, Shreenivas Kunte, Nikhil Hooda, Sivamuthu Prakash Murugan, Dipak L. Chaudhari, Prateek Kapadia, and Manoj K. Chinnakotla. His teaching portfolio includes courses on System Dynamics: Modeling and Simulation for Development (CS 752), Program Derivation (CS 420), and ICT for Development. Dr. Damani's educational background includes a Ph.D. in Computer Sciences from the University of Texas at Austin (1994-1999), B.Tech. in Computer Science and Engineering from IIT Kanpur (1990-1994), and prior professional experience at IBM T J Watson Research Lab and Akamai Technologies.
Naren Naik is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology (IIT) Kanpur, specializing in computational tomographic reconstructions and analysis for subsurface imaging and shape/target tracking. His educational background includes: PhD from the Indian Institute of Science (IISc) Bangalore in 2000 M.E. in Electronics and Communication Engineering from IISc Bangalore in 1992 B.Sc. from Bangalore in 1988 Professor Naik's research focuses on development and analysis of reconstruction algorithms for nonlinear tomography , with particular emphasis on shape-based and dynamic tomography, tracking and battlefield surveillance, and numerical solutions to partial differential equations in electromagnetics. His work spans multiple imaging modalities including subsurface imaging with Ground Penetrating Radar (GPR), fluorescence optics, electrical impedance tomography, and photoacoustic tomography. His research bridges theoretical mathematics with practical applications in electromagnetic imaging and target tracking systems, addressing complex inverse problems in computational imaging. His publication record shows a clear progression from electromagnetic tomography to advanced Kalman filtering techniques for target tracking applications. The most recent works focus on wireless sensor networks and maneuvering target tracking, demonstrating his ability to adapt theoretical frameworks to evolving technological contexts while maintaining mathematical rigor in solving inverse problems. His professional recognition includes: Invited presentation at the special session on advances in model based inversion at the 2011 IEEE AP-S International Symposium on Antennas and Propagation Professor Naik maintains an active research program with consistent publication output in high-impact journals and conferences. His work demonstrates strong interdisciplinary collaboration, particularly with researchers in electromagnetics, signal processing, and imaging sciences. His research has significant applications in defense technology (battlefield surveillance), medical imaging, and subsurface exploration systems, contributing to both theoretical advances and practical implementations in these fields. He is based in Office 303A ACES (Advanced Centre for Electronic Systems) at the Department of Electrical Engineering, IIT Kanpur, where he leads research activities in computational imaging and tomographic reconstruction.
Pradeep Kumar is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in quantum cryptography, quantum optics, and fiber-optic communications. His research focuses on secure quantum communication systems and the application of quantum phenomena in information processing. Dr. Kumar received his PhD from IIT Madras in 2009 under the supervision of Anil Prabhakar. He completed his B.E. at M.V.J. College of Engineering, Visweswaraiah Technological University in 2002. His research interests span quantum cryptography and computation, quantum and nonlinear optics, and fiber-optics. Dr. Kumar's work primarily explores quantum key distribution systems, examining various approaches including frequency coding, decoy states, and spin wave-optical interactions. His research has significant implications for secure communications and quantum information processing. Dr. Kumar's publications demonstrate a consistent focus on quantum communication technologies, with particular emphasis on improving the reliability and security of quantum key distribution systems. His research trajectory shows progression from fundamental quantum state manipulation to practical implementations of quantum cryptography. He maintains an active research laboratory within the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where he supervises graduate students working on quantum communication technologies and optical systems.
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.
R K Bansal is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). He has been actively contributing to the fields of Detection Theory and Information Theory for several decades with a strong academic background including a PhD from University of Connecticut (1987). His research interests include: Universal data compression with applications Sequential detection of a change in distribution Robust detection Ergodic theory and large deviation theory applications Stochastic processes Dr. Bansal's recent publications primarily focus on data compression algorithms, particularly variations of the Lempel-Ziv algorithm, and detection theory applications. His work demonstrates a strong theoretical foundation with practical applications in information processing and analysis, showing consistent research activity from the 1980s through 2013. He has received significant recognition for his teaching excellence: Letter of commendation from Director on best teaching (2011) Outstanding tutor for Mathematical Statistics (BSO209) based on student feedback (1998-II) Consistently high teaching evaluations exceeding institute averages Dr. Bansal has advised students and maintained active research in his specialized areas, though specific names of current advisees are not mentioned in the available information. His research has been published in prestigious venues including IEEE Transactions on Information Theory. His laboratory is located in room 202 ACES (Advanced Centre for Electronic Systems) at IIT Kanpur, serving as the base for his research activities in detection theory and information theory applications.
Subhajit Dutta is an Associate Professor in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur. He has established himself as a notable researcher in specialized statistical methodologies with publications in top-tier statistical journals. Dr. Dutta completed his PhD in Statistics from the Indian Statistical Institute (ISI), Kolkata in 2013 under the supervision of Prof. Probal Chaudhuri. His academic journey includes an M.Sc. in Statistics from IIT Kanpur (2007) and a B.Sc. in Statistics from Presidency College, University of Calcutta (2005). He also pursued post-doctoral research at KAUST with Prof. Marc G. Genton. His research focuses on advanced statistical methodologies, particularly in Discriminant Analysis, Inference based on Data Depth, Characterization of Multivariate Distributions, and Classification of Sequence Data. His work bridges theoretical statistics with practical applications, developing robust methods for complex data analysis problems across various scientific domains. Dr. Dutta's publication record shows consistent progression from foundational properties of statistical depth functions to practical applications in classification and sequence analysis, demonstrating both theoretical depth and practical relevance in his scholarly contributions. As a faculty member at IIT Kanpur, one of India's premier technical institutions, Dr. Dutta contributes to both teaching and research in the Department of Mathematics and Statistics, helping to advance statistical science education and methodology development.
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.
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.
Anirban Chakraborti is a Professor at the School of Computational and Integrative Sciences, Jawaharlal Nehru University (JNU), New Delhi, India, where he has been a faculty member since 2014. He previously held academic positions at École Centrale Paris (France) as Chercheur Senior (Associate Professor) and Chargé de Recherche (Assistant Professor), and earlier roles at Banaras Hindu University, Brookhaven National Laboratory (USA), and Helsinki University of Technology (Finland). He is a leading figure in the interdisciplinary field of econophysics and complex systems. Education: Diplôme d’Habilitation à Diriger des Recherches (2013), Université Pierre et Marie Curie – Paris VI, France (Physics) Ph.D. in Physics (2003), Saha Institute of Nuclear Physics, Jadavpur University, India Post-M.Sc. in Physics (1999), Saha Institute of Nuclear Physics, Jadavpur University, India (Ranked First) M.Sc. in Physics (1998), University of Calcutta, India (Ranked First) B.Sc. in Physics (1996), Scottish Church College, University of Calcutta, India His research interests lie at the intersection of physics, economics, and data science. He is particularly known for pioneering work in econophysics , including the statistical mechanics of money, wealth distribution, agent-based market models, and network-based analysis of financial and social systems. He also works on complex systems , computational finance , statistical physics , and nanosciences , with applications in sensing and imaging. His work often involves modeling socio-economic phenomena using tools from statistical physics. His recent publications span topics such as financial fluctuations, wealth inequality, network analysis of conflicts, order book dynamics, and nanomaterial characterization. These works reflect a strong trend toward interdisciplinary research combining physics, economics, and data analytics, with a focus on real-world applications in finance, inequality, and social systems. Scientific Awards: Indian National Science Academy Young Scientist Medal (2009) He has advised Ph.D. students such as Kiran Sharma and leads the ETC (Experimental-Theoretical-Computational) Lab at JNU, which brings together physicists, computer scientists, and mathematicians. The lab has been involved in international collaborations, including projects funded by the Estonian Ministry of Education and Research and consultancies with TCS Innovation Labs and DONO Consulting. His research has been supported through grants and collaborative projects, reflecting strong industry and global academic engagement.
