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Sharat Chandran is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay (IIT Bombay), where he has been actively engaged in teaching and research for several decades. His office is located in Room KR102 (also known as A202) in the Rekhi Building on the IIT Campus in Mumbai, India. His primary research interests span two major areas in computing: Computer Graphics and Computer Vision . He has extensively worked in these fields with his students and research staff, producing various publications, talks, and research projects over the years. His current teaching focus includes Math for Visual Computing (CS 740), a course designed for postgraduate students new to the IIT system who may have some apprehension about mathematics. Professor Chandran has supervised numerous PhD students whose work covers diverse topics including 3D modeling, efficient computing with tomographic measurements, vision for drones, cancer prognosis, hierarchical visibility, projector-camera systems, arterial pulse analysis, and optimization algorithms for motion factorization. His teaching portfolio is extensive, having offered courses such as Basic Freshman Programming, Software Systems, Parallel Programming Paradigms, Graphics I & II, Multimedia Systems, Computer Vision, Digital Image Processing, Algorithms, and Spatial Data Structures. He has held multiple administrative and service roles at departmental, institutional, and external levels. Departmental roles include PhD Faculty Advisor, Awards Committee Chair, Faculty Search Chair, and Web Team Chair. At the institutional level, he served as Founding PMRF Coordinator, Head of the Application Software Centre, and IIT Research Fellowship Initiative Coordinator. Externally, he has coordinated the DST India Digital Heritage Project and served as Program Co-Chair for conferences like Mysore Park Vision Conference and ICVGIP. Professor Chandran is actively involved in campus community activities including Sanskriti @ IITB, Taekwando @ IITB, and serves as Secretary for Kendriya Vidyalaya PTA. His office hours are from 12:30 PM to 1:00 PM on Monday, Tuesday, and Thursday, and he emphasizes using Piazza rather than email for student communications.

• Computer Graphics
• Computer Vision
• Visual Computing
• +3 more

Soumya Dutta is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur (IITK), where he leads the INSIGHT: Intelligent Scientific and Visual Computing of Big Data Research Group. He joined IIT Kanpur in October 2022 after working as a Scientist II at Los Alamos National Laboratory (LANL) from July 2019 to August 2022, and previously as a Postdoctoral Research Associate at LANL from June 2018 to July 2019. His educational background includes a Ph.D. and M.S. in Computer Science and Engineering from The Ohio State University (2011-2018), where he was part of the GRAVITY research group, and a B.Tech. in Electronics and Communication Engineering from West Bengal University of Technology, India (2005-2009). Research Interests: Dr. Dutta's research focuses on the intersection of machine learning, visual computing, big data, and high-performance computing. His primary research areas include Machine Learning for Visual Computing and Image Analysis, Big Data Visualization and Analytics, Data Science and HPC, Machine Learning for Scientific Computing, and Explainability and Interpretability of AI Models. His work addresses various big data characteristics including the 5 Vs: Volume, Velocity, Variety, Veracity, and Value. He develops techniques that make complex machine learning models more interpretable and explainable, enabling their effective adoption in real-life applications across scientific domains, social media, IoT, healthcare, and industry applications. Dr. Dutta's research group has secured multiple funded projects including: DAVi: An Intelligent Data Analytics and Visualization Framework (funded by ISRO), Intelligent Visual Computing of Extreme-scale Data for Accelerating Scientific Discovery (IIT Kanpur Initiation Grant), Enabling Interactive Big Data Analytics and Visualization at Exascale (SERB), Development of AI-Enabled National Portal for Efficient Search of Missing People (C3iHub), and Proactive and Generalized Deepfake Defense Mechanisms (C3iHub). Best Reviewer, Honorary Mention Award for IEEE Transactions on Visualization & Computer Graphics (TVCG), 2021 Best Paper Award at ISAV 2021, co-located with Supercomputing (SC) LAAP Award at Los Alamos National Laboratory, 2021 Best Paper Award at TopoInVis 2019 Best Paper Award at ISAV 2018, co-located with Supercomputing (SC) Best Poster Award in 12th Annual CSE Student Poster Exhibition, The Ohio State University, 2018 Best Poster Award in 11th Annual CSE Student Poster Exhibition, The Ohio State University, 2017 Best Paper Honorable Mention Award at IEEE Visualization Conference (IEEE VIS) 2016 Dr. Dutta actively mentors a large group of students including Ph.D., M.Tech., and B.Tech. students. His current Ph.D. students include Shanu Saklani, Sankhadeep Bhowmick, Ananya Chaturvedi, Arpita Santra, Anubhav Dixit (co-supervised), and Robin Shah. He has supervised numerous M.Tech. students with thesis topics ranging from uncertainty-aware neural networks to deepfake detection. Dr. Dutta currently teaches courses including CS360 - Introduction to Computer Graphics and CS661 - Big Data Visual Analytics. The INSIGHT research group collaborates internationally with researchers from Meta, Oak Ridge National Laboratory, and National Taiwan Normal University. The group's work focuses on building machine learning and data science-based solutions to analyze large-scale multifaceted data in a scalable way, enabling interactive and interpretable analytics of complex data from scientific simulations, social media, IoT, healthcare, and other application domains.

• Machine Learning
• Visual Computing
• Image Analysis
• +6 more

Arpit Agarwal is an Assistant Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology, Bombay. He previously held postdoctoral positions at FAIR Labs (Meta) working with Max Nickel and at the Data Science Institute at Columbia University hosted by Prof. Yash Kanoria and Prof. Tim Roughgarden. He completed his PhD from the Department of Computer & Information Science at the University of Pennsylvania under the guidance of Prof. Shivani Agarwal. His research focuses on the intersection of human behavior and machine learning systems, with particular interest in learning from implicit, strategic, and heterogeneous human feedback. His work spans multiple dimensions of human-AI interaction including understanding long-term dynamics between humans and AI systems, designing responsible AI, and studying misalignment between user preferences and system objectives. His research methodology often combines theoretical machine learning with practical applications in recommendation systems and social AI. His recent publications reveal a strong focus on bandit algorithms, preference learning, and recommendation systems, with increasing attention to responsible AI design and human-centered considerations. His work demonstrates expertise in theoretical machine learning with applications to real-world problems, particularly in understanding how humans interact with and are influenced by AI systems over time. Dr. Agarwal teaches advanced courses including CS767 Theoretical Machine Learning (Autumn 2025) and CS6103 Human-Centered AI: From Learning Models to Responsible Systems (Spring 2025), which covers topics such as AI alignment, learning from pairwise comparisons, crowdsourcing, human-in-the-loop decision making, recommendation systems, interpretability, privacy, fairness, causality, and AI governance.

• Machine Learning
• Artificial Intelligence
• Human-AI Interaction
• +4 more

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.

• Real-Time Programming
• Reactive Programming
• Logic Programming
• +7 more

Nisanth N. Nair is Professor of Chemistry at the Indian Institute of Technology Kanpur (IITK), India, holding the position since 2018. He obtained his PhD from the Universität Hannover, Germany (2004) after completing his MSc in Chemistry at IIT Madras (2001). His research group pioneers advanced computational-chemistry methods to address grand-challenge problems in energy, healthcare and materials science. Education PhD (2004), Universität Hannover, Germany MSc (2001), Chemistry, Indian Institute of Technology Madras Research Interests Professor Nair’s work is organized around five tightly linked thrusts: Method development: massively parallel QM/MM algorithms, polarizable force-fields, metadynamics and hybrid functionals for large-scale catalytic systems. Energy catalysis: computational design of Rh/Al₂O₃ and Rh/TaON catalysts for efficient water-splitting and H₂ production. Healthcare: molecular mechanisms behind antibiotic resistance in NDM-1 and Class-C β-lactamase enzymes, guiding de-novo inhibitor discovery. Aerospace materials: multi-scale modelling of thermo-oxidative degradation of high-temperature polymers in collaboration with Boeing. Heterogeneous catalysis: olefin hydrogenation on Rh/Y-zeolite and single-atom catalysis phenomena. Publications Trend His recent articles (2011–2013) highlight an integrative approach combining rigorous electronic-structure calculations with micro-kinetic modelling to unravel complex catalytic cycles, antibiotic-resistance pathways and support-effects in single-atom catalysts. Honours & Awards P. K. Kelkar Young Faculty Research Fellow, IIT Kanpur (2012–2015) Young Associate, Indian Academy of Sciences, Bangalore (2012–2015) Young Scientist Medal, Indian National Science Academy, New Delhi (2013) Contact & Resources Office: SL 302, Department of Chemistry, IIT Kanpur, Kanpur 208016, India Phone: +91 512 259 6311 Email: nnair@iitk.ac.in Web: http://home.iitk.ac.in/~nnair

• Computational chemistry
• QM/MM simulations
• Catalysis
• +5 more

Arijit Bishnu is an Associate Professor at the Indian Statistical Institute in the Advanced Computing and Microelectronics Unit (ACMU). He has taught courses such as Design and Analysis of Algorithms , Randomized Algorithms , Computational Geometry , and Algorithms for Big Data over multiple years (2008–2025), focusing on theoretical and applied aspects of computer science. Research Interests: His work spans Theoretical Computer Science , Randomized and Approximation Algorithms , Computational Geometry , and Combinatorics . He explores problems in sublinear algorithms, streaming computation, geometric data analysis, and complexity theory. Publications: Recent papers include contributions to STOC 2025 , RANDOM 2025 , and APPROX 2024 , covering topics like property testing, triangle counting complexity, and streaming algorithms. Collaborations with researchers like Sourav Chakraborty, Gopinath Mishra, and Sayantan Sen highlight his interdisciplinary approach. Academic Leadership: He has co-organized research courses such as Approximation Algorithms and Topics in Algorithms and Complexity , emphasizing mentorship and knowledge dissemination in theoretical computer science. His comprehensive work integrates algorithmic innovation with rigorous mathematical analysis, advancing computational techniques for large-scale and geometric data.

• Theoretical Computer Science
• Randomized Algorithms
• Approximation Algorithms
• +6 more

Mohit Law is an Associate Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur. His research focuses on machining dynamics, machine tool design and analysis, vibration control, and manufacturing systems. With expertise spanning both theoretical modeling and practical applications, Dr. Law has established himself as a notable researcher in precision manufacturing technologies. PhD (2013), University of British Columbia, Canada. Thesis: "Position-dependent dynamics and stability of machine tools." MSc, Michigan Technological University, USA BE, Pune University, India Dr. Law's research spans multiple areas in manufacturing and mechanical engineering, with a strong focus on machining dynamics and machine tool performance. His work addresses critical challenges in precision manufacturing, vibration control, and advanced machining strategies. He has made significant contributions to understanding position-dependent dynamics in machine tools and developing innovative solutions for vibration damping and isolation. His research integrates analytical methods with experimental validation to improve machine tool performance and manufacturing efficiency. Dr. Law's publication record demonstrates a consistent focus on machine tool dynamics, particularly position-dependent behavior. His work bridges theoretical modeling with practical applications in manufacturing, with emphasis on substructuring techniques, vibration isolation, and stability analysis. He has developed novel approaches that have advanced the field of precision manufacturing, particularly in high-performance machining strategies. International Partial Tuition Scholarship, The University of British Columbia, 2009-2013 Graduate Scholar, Sustainable Futures Institute, Michigan Technological University, 2007-2008 Dr. Law has extensive industry experience as a Machine Tool Design Engineer at TAL Manufacturing Solutions (TATA) and Bharat Fritz Werner Ltd. He also served as a Research Associate at the Fraunhofer Institute for Machine Tools and Forming Technology in Germany. He maintains active professional affiliations as a CIRP Research Affiliate and SME Member. His research has practical applications in industrial manufacturing settings, particularly in improving machine tool performance and reliability. Dr. Law is associated with the Manufacturing Science and Solid Mechanics and Design research groups at IIT Kanpur. His work involves developing advanced modeling techniques and experimental methods to improve machine tool dynamics and manufacturing processes. He collaborates with international research institutions and maintains strong industry connections to ensure his research addresses real-world manufacturing challenges.

• Machining dynamics
• Machine tool design and analysis
• Dynamic substructuring
• +6 more

Neeraj Misra is a Professor in the Department of Mathematics & Statistics at the Indian Institute of Technology Kanpur (IIT Kanpur), where he has held faculty positions since 1996. He earned his PhD (1991) and M.Sc. (1985) in Statistics from IIT Kanpur, and a B.Sc. from Kanpur University (1982). His research focuses on theoretical statistics and applied probability. Research Interests: His work spans entropy estimation, stochastic ordering theory, estimation under parameter restrictions, and ranking/selection methodologies, with applications in reliability engineering and molecular sciences. Key themes include: Development of nonparametric entropy estimators Stochastic comparisons for system reliability Optimization in statistical decision theory Inference for restricted parameter spaces Publication Trends: His recent articles (2003–2015) demonstrate a consistent focus on reliability modeling, stochastic ordering, and entropy estimation. Works frequently involve gamma distributions, redundancy allocation in engineering systems, mixture models, and multivariate circular distributions, blending theoretical rigor with practical applications. Awards & Honors: Jacob Wolfowitz Award (2003) for theoretical advances C. L. Chandna Mathematics Award (2003) for research/teaching excellence All India Rank #2 in Mathematics (National Entrance Exam, 1985) Outstanding Teaching Recognition at IIT Kanpur He has held visiting positions at West Virginia University, Marquette University (USA), and KU Leuven (Belgium).

• Entropy Estimation
• Theory of Stochastic Orders
• Estimation in Restricted Parametric Space
• +1 more

Dr. Preethi Srivathsa is an Assistant Professor - Senior Scale in the School of Computer Engineering at Manipal Academy of Higher Education (MAHE), Bengaluru. She holds a B.Tech, M.Tech, and Ph.D. (awarded by Presidency University in 2022). Her academic career includes positions at Presidency University (2019-2023) and East Point College of Engineering (2008-2019). Her research focuses on: Computer architecture and low-power hardware design IoT applications and cyber-physical systems Cryptography and blockchain security Machine learning implementations in hardware FPGA-based accelerators and optimization techniques Her publication portfolio shows strong emphasis on hardware-efficient algorithms, cryptographic systems (especially elliptic curve applications in blockchain), and emerging IoT architectures. Recent work integrates machine learning with hardware acceleration for smart home systems and agricultural technology. Awards and recognitions: Best Paper Award at IEEE iSES-2021 for low-power sorter design Infosys Bronze Partner Faculty (2013) She has developed intellectual property including IoT-based monitoring systems and blockchain educational frameworks. Technical skills include Verilog, FPGA design, IoT platforms (Arduino/Raspberry Pi), and multiple programming languages.

• Computer Architecture
• Internet of Things
• Cyber Security
• +4 more

Jyothi Vedurada is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). Her research focuses on compilers, program analysis, high-performance computing (HPC), and software engineering. Prior to joining IIT Hyderabad, she was a postdoctoral researcher at Microsoft Research Lab in Bangalore and worked as a Software Engineer at Hewlett Packard in Chennai. Her research spans four major areas: Compiler Optimizations : Developing global compiler optimizations for CPU-GPU heterogeneous systems to enhance performance across varied hardware environments. ML for PL : Leveraging AI to overcome scalability and semantic challenges in program analysis, with applications in bug detection, API misuse recommendation, and algorithm description generation for Jupyter notebooks. Parallelization : Designing efficient GPU algorithms for tasks like Approximate Nearest Neighbour search and subgraph isomorphism optimization, alongside developing the Tensor Transposition Library for GPUs (TTLG). Concurrency Testing : Creating systematic testing frameworks for concurrent systems, including language-agnostic libraries and mock storage systems to validate weak isolation levels in databases. Scientific Awards & Recognition : Distinguished Artifact Award at ECOOP 2025 Google Research exploreCSR Award (2021) Tata Consultancy Services PhD Fellowship ACM SIGAI, SIGPLAN, and IEEE Travel Grants Advising & Collaborations : Supervising 11 PhD and MTech students, including Soumik Kumar Basu and Karthik V, with projects spanning compiler optimizations, HPC, and AI-driven software analysis. Collaborating with institutions like Microsoft Research and IIT Madras.

• Compilers
• Program Analysis
• High-Performance Computing
• +3 more

Rushikesh K. Joshi is a Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Bombay. His research focuses on computational models for programs, their structures and dynamics, including processes, interactions, concurrency, and distributed systems. He has taught advanced courses like CS 770 (Process Engineering), CS 787 (Language Engineering), and CS 757 (Design and Re-engineering). Research Interests: He specializes in software engineering, distributed systems, program analysis, and code refactoring. His work includes modular process modeling, trace language mining, and consistency models for business processes. He also explores objectification of procedural code through projects like Ox and AccessViz. Notable Projects: Anonymous Remote Computing (ARC), Filter Objects, Constore Graph Database, and Ox (objectification of Linux kernel structures). Funding sources include IBM, Microsoft, Infosys, and the Ministry of Information Technology. Scientific Contributions: His research has led to publications in IEEE Transactions, LNCS, and other venues. He has advised over 100 theses, including Ph.D. students Karnika Shivhare, Omkarendra Tiwari, and Vrinda Yadav.

• Software Engineering
• Distributed Systems
• Program Analysis
• +5 more

Supratim Biswas is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay, where he has served since 1995. His academic career spans over four decades, beginning as a Lecturer in the Computer Center in 1980, progressing to Assistant Professor in 1985, Associate Professor in 1990, and achieving full Professorship in 1995. He has held significant administrative roles including Dean of Academic Programs (2007-2010), Head of CSE Department (2000-2003), and Director of IITB-Monash Academy (2009-2010). His research interests focus on Programming Languages, Compiler Optimization, Parallelizing Compilers, Parallel and Distributed computing, and Combinatorial Optimization . Professor Biswas has made substantial contributions to compiler technology, particularly in parallelization techniques for modern architectures. His work bridges theoretical compiler design with practical applications in high-performance computing and CAD systems, demonstrating how compiler optimizations can significantly enhance computational efficiency in real-world applications. The publication record shows a consistent research trajectory spanning nearly four decades, with recent work (2012-2015) focusing on GPU-based parallel algorithms, loop parallelization techniques for non-uniform data dependencies, and mesh processing for CAD applications. His research demonstrates evolution from foundational compiler theory to contemporary parallel architectures, maintaining relevance through practical applications in computational geometry, CAD systems, and high-performance computing. Excellence in Teaching Award (2000) Professor Biswas has supervised over 60 doctoral and master's students, establishing himself as a dedicated mentor in systems software education. His sponsored research portfolio includes significant projects with CDAC (350 lacs), MIT (133 lacs), TCS (81.3 lacs), and Intel Corporation (10 lacs), demonstrating strong industry-academic collaboration. His teaching portfolio spans both undergraduate and postgraduate levels, including foundational courses like Discrete Structures and advanced topics like Parallelizing Compilers, reflecting his commitment to curriculum development across multiple generations of computer science education. His laboratory work has supported students across B.Tech, M.Tech, and Ph.D. programs, with particular emphasis on compiler construction and operating systems. Through the Continuing Education Program, he has extended his expertise to industry professionals, conducting numerous specialized courses for organizations including VSNL, TCS, DRDO, and Reliance.

• Programming Languages
• Compiler Optimization
• Parallelizing Compilers
• +2 more

Hemant Gehlot is an Assistant Professor in the Department of Civil Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in transportation engineering and related fields. Education: PhD, Purdue University, 2021 BTech-MTech (dual degree), IIT Kanpur, 2015 Dr. Gehlot's research focuses on transportation network modeling, combinatorial optimization, intelligent transportation systems, and disaster management. His work addresses critical challenges in transportation systems, particularly in the areas of network resilience, congestion management, and emergency response planning. He employs advanced modeling techniques including optimal control approaches, stochastic network analysis, and agent-based simulation to develop solutions for complex transportation problems. His research bridges theoretical advancements with practical applications in transportation systems engineering. Dr. Gehlot has received several prestigious awards throughout his academic career: Best Student Paper Award Finalist, IFAC Workshop on Distributed Estimation and Control in Networked Systems 2019 Purdue Civil Engineering Awards: Essam and Wendy Radwan Graduate Fellowship 2019-20 STV Civil Engineering Graduate Assistantship Endowment 2018-19 Academic Excellence Awards 2012-13 and 2011-12, IIT Kanpur CBSE Merit Scholarship for Professional Studies 2010 National Talent Search Examination Scholarship 2008 His publications demonstrate expertise in developing innovative approaches to transportation network management, disaster response, and infrastructure resilience, with work appearing in leading journals such as IEEE Transactions on Automatic Control and Transportation.

• Transportation engineering
• Transportation network modeling
• Combinatorial optimization
• +2 more

Preeti Malakar is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur. She leads the Scalable Parallel Computing Laboratory (SParCL) and previously held positions as a postdoc and Assistant Computer Scientist at Argonne National Laboratory (USA) and was a Visiting Affiliate at Lawrence Berkeley National Laboratory (USA). She completed her PhD from the Indian Institute of Science Bangalore under Prof. Vijay Natarajan and Prof. Sathish Vadhiyar. Her research focuses on high-performance computing systems, parallel I/O optimization, in-situ analysis, and scientific visualization. Key areas include job scheduling, communication optimization for MPI applications, machine learning for performance prediction, and adaptive frameworks for large-scale simulations. Her work integrates HPC with climate modeling and extreme weather prediction. Recent publications emphasize job scheduling with SLURM, deep learning for climate applications, in-situ visualization, and auto-tuning of parallel I/O parameters. Her research consistently targets optimization of HPC systems for scientific domains. Awards: Best Paper Award, EduHiPC 2019 TCPP Best Paper Award, HiPC 2009 She actively advises students in HPC research, with alumni pursuing careers at NVIDIA, Microsoft, Apple, and SAP Labs. Her lab (SParCL) hosts internships and winter schools, including the ACM Winter School on HPC at IIT Kanpur.

• High Performance Computing
• Parallel Computing
• Computer Systems
• +4 more

Suvendu Samanta is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. His research focuses on power electronics, electric vehicles, and wireless power transfer technologies. He has published numerous papers in prestigious journals and conferences in the field of power electronics and energy conversion systems, with recent work emphasizing electric vehicle charging infrastructure and medium-voltage DC grid integration. Education: Ph.D. in Electrical Engineering from Concordia University, Montreal, Canada (2018) M.Tech from IIT Kanpur (2013) B.E. from BESU Shibpur (IIEST Shibpur) (2009) Dr. Samanta's research primarily centers on power electronics with a focus on wireless power transfer systems for electric vehicles. His work explores resonant converters using wide bandgap semiconductor devices, which offer higher efficiency and power density compared to traditional silicon-based devices. He has made significant contributions to the analysis and design of various converter topologies for inductive power transfer applications, addressing critical challenges in electric vehicle charging infrastructure including efficiency improvements, power density enhancement, and grid integration. His publication record demonstrates a consistent focus on wireless power transfer technology, particularly for electric vehicle applications. The research spans from fundamental converter topologies to practical implementation challenges, with a recent emphasis on medium-voltage DC grid integration for electric vehicle charging. His work bridges theoretical analysis with experimental validation, contributing significantly to the advancement of wireless charging technologies with particular attention to safety considerations like arc flash mitigation. Scientific Awards: Concordia University Distinguished Doctoral Dissertation Prize in Engineering and Natural Sciences (2019) Department of Electrical and Computer Engineering Ph.D. Convocation Award, Concordia University (2019) Canadian Governor General's Gold Medal—Technology, Industry and the Environment Category for PhD Thesis (2018) Best Paper Award for "A New Direct AC-AC Converter with Active Source Current Control for Wireless Inductive Power Transfer Application" (2018) Multiple Conference Travel Grants for IEEE IAS Annual Meeting 2017, APEC 2017, and IEEE IAS Annual Meeting 2016 Dr. Samanta has secured significant research funding for projects focused on next-generation electric vehicle charging systems and power electronics. His collaborations with institutions including NC State University and National University of Singapore have resulted in impactful research addressing practical challenges in power conversion systems. He actively mentors students in advanced power electronics research and has contributed to developing innovative solutions for electric vehicle infrastructure. Based in the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, Dr. Samanta leads a research team focused on developing cutting-edge solutions for wireless power transfer, electric vehicle charging, and high-efficiency power conversion systems. His laboratory work emphasizes practical implementation of theoretical concepts, with particular attention to the integration of wide bandgap semiconductor devices in power converter design for improved performance and reliability.

• Power Electronics
• Electric Vehicles
• Wireless Power Transfer
• +3 more