جست‌وجوی استاد و پژوهشگر

Om P. Damaniمشاهده پروفایل

استاد

• Technology for Development
• System Dynamics
• Modeling and Simulation
• +۷ مورد دیگر

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.

Shashank Vatedkaمشاهده پروفایل

استادیار

• Information Theory
• Coding Theory
• Wireless Communication
• +۷ مورد دیگر

Shashank Vatedka is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad . His research focuses on information theory , coding theory , and their applications to data compression , statistical inference , and security . He holds a PhD from IISc, Bengaluru and has postdoctoral experience at Institut Polytechnique de Paris and The Chinese University of Hong Kong . Education : PhD and MSc (Engg) in Electrical Communication Engineering, IISc, Bengaluru (2011-17) Academic Positions : Assistant Professor, IIT Hyderabad (2019-present) Postdoctoral Fellow, Telecom Paris (2018-19) Research Assistant/Postdoctoral Fellow, Institute of Network Coding, CUHK (2016-18) His research spans three main areas: distributed inference (federated learning, wireless sensor networks), compression with locality constraints (local decoding, low-complexity algorithms), and communication in adversarial environments (jamming, list decoding). Recent work includes distributed mean estimation with limited communication and adversarial channel coding with partial information. He has received several honors including the Seshagiri Kaikini Medal for best PhD thesis at IISc in 2017, Best Paper Awards at NCC 2023 and Stanford Compression Workshop 2021, and the TCS Research Fellowship (2014-17). He serves as a Faculty Placement Coordinator at IIT Hyderabad and organizes international conference tracks. His research group advises students across PhD, MTech, BTech , and internships , with alumni pursuing advanced degrees at institutions like UCSD , Columbia University , and TU Delft . Collaborations include theoretical work with colleagues like Yihan Zhang and Sidharth Jaggi .

• Machine Learning
• Artificial Intelligence
• Federated Learning
• +۷ مورد دیگر

Rajesh M. Hegde is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. He holds a PhD in Computer Science from IIT Madras (2005), an M.E. in Electronics Engineering from Bangalore University (1988), and a B.E. in IT Engineering from Mysore University. His research focuses on Machine Learning , AI , and multimodal systems, with applications in wireless networks, IoT, and speech/audio processing. Specific interests include federated learning, WSN, and information fusion for ASR/VR systems. His lab is located in ACES 203-204. Publications predominantly explore signal processing techniques for multimedia and speech applications, showing consistent focus on feature extraction, multimodal fusion, and real-time system design across 15+ years of research. Awards & Honors: P.K Kelkar Research Fellowship (2009-2013) Undergraduate design mentorship award, UC San Diego ISCA Grant at INTERSPEECH-ICSLP 2004 IBM Best Thesis Award recommendation Teaching excellence commendation

Gururaj Mirle Vishwanathمشاهده پروفایل

استادیار

• Renewable energy integration
• Machine learning for power systems
• Power electronics
• +۵ مورد دیگر

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.

• Discriminant Analysis
• Inference based on Data Depth
• Characterization of Multivariate Distributions
• +۱ مورد دیگر

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.

Rameshwar Pratapمشاهده پروفایل

دانشیار

• Algorithms in Machine Learning
• Theoretical Computer Science
• Sketching and Dimensionality Reduction
• +۵ مورد دیگر

Rameshwar Pratap is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad). Previously, he served as an Assistant Professor at the School of Computing and Electrical Engineering, IIT Mandi for three years. Education: Ph.D. in Theoretical Computer Science, Chennai Mathematical Institute Research Interests: His research lies at the intersection of theory and practice, focusing on extremely simple yet practical approximation algorithms with provable guarantees . Key themes include: Sketching and dimensionality reduction algorithms for tensors and similarity measures Improving speed, scalability, and accuracy of existing sketching methods Applications in machine learning: node embedding in large-scale networks, itemset mining, model compression He extensively employs techniques from matrix and tensor algebra, sampling, random projection, and randomized hashing . Publications Overview: Across 2021–2025 his work has appeared in top venues such as IEEE Globecom, Theoretical Computer Science, Acta Informatica, Information Processing Letters, Algorithmica, UAI, ICALP, Machine Learning, TKDE, and ACML. Recurring themes are randomized sketching, locality-sensitive hashing, compressed matrix multiplication, variance reduction, and subspace approximation , demonstrating both theoretical depth and practical impact. Awards & Honors: Early Career Research Grant (PM-ECRG) 2025, Anusandhan National Research Foundation (ANRF) Best Paper Award, COCOON 2020 Students & Funding: First Ph.D. student: Bhisham Dev Verma (co-advised with Prof. Manoj Thakur) graduated June 2025 MS by Research student: Punit Pankaj Dubey graduated October 2022 Currently hiring 1 Junior Research Fellow for the PM-ECRG project “Improving Similarity Search in Practice” Labs & Teams: Works within the Algorithms & Theory group at IIT Hyderabad, collaborating with national and international researchers. Erdös number is 3.

Seshadri Sravan Kumar V.مشاهده پروفایل

دانشیار

• Power Engineering
• Applied Mathematics
• Time and Frequency Domain Modeling
• +۸ مورد دیگر

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.

Subrahmanya Sastry Challaمشاهده پروفایل

استاد

• Wavelets
• Sparse Optimization Theory
• Inverse Problems
• +۷ مورد دیگر

Professor Subrahmanya Sastry Challa is affiliated with the Department of Mathematics at Indian Institute of Technology Hyderabad. His academic journey includes a PhD from IIT Kanpur under Prof. P. C. Das, an M.Sc(Tech) from JNT University, and a B.Sc from Hindu College, Machilipatnam. Research Focus: He specializes in Wavelets and Sparse Optimization Theory Frame Theory and Data-driven Learning Methods Applications in Medical Imaging and Signal Processing His recent work explores sparsity-driven optimization techniques with applications in tomography, ECG signal recovery, and machine learning algorithms. Publications & Collaborations: He has contributed to advancements in compressive sensing, inverse problems, and numerical linear algebra through collaborations with researchers like Dr. Phanindra Jampana and Dr. Praveen Pradhan. Key journals include IEEE Transactions on Signal Processing , Inverse Problems , and Neurocomputing . Teaching: Courses taught include Wavelets & Applications, Compressive Sensing, Numerical Linear Algebra, and Mathematics Behind Machine Learning, emphasizing both theoretical and applied aspects. Administrative Roles: Served as Associate HoD/HoD (2010-2014), Chief Vigilance Officer (2015-2019), and participated in policy-drafting committees during IIT Hyderabad's formative years.

• Fuzzy Logic
• Soft-Computing
• Health Monitoring
• +۹ مورد دیگر

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.

Srijith P.K.مشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Computer Science
• +۱۶ مورد دیگر

Dr. Srijith P.K. is an Associate Professor in the Department of Computer Science & Engineering at Indian Institute of Technology Hyderabad , where he leads research in probabilistic machine learning, Bayesian learning, and deep learning. He is affiliated with the BRAIN (Bayesian Reasoning And INtelligence) Lab , focusing on bridging human and machine learning through interdisciplinary applications in social networks, astrophysics, autonomous navigation, and sustainable cities. Research Interests : Probabilistic machine learning Bayesian learning Continual learning and causal learning Multi-modal learning and physics-informed neural networks Uncertainty quantification and generative modeling Scientific Awards : Sony Research Award 2021 Major Research Grants : Funding from AGC Inc, Japan, on Scientific Large Language Modeling Ministry of Education (MoE) funding for the Centre of Excellence in AI for Sustainable Cities Hyundai funding for Physics-Informed Neural Networks Sony Research India funding for Multimodal Learning JICA funding for Causal Learning in collaboration with RIKEN SERB and DST grants for projects on continual learning and astrophysical data analysis Advising : Supervises a team of students and researchers including Manisha Dubey, Rohan Tondulkar, Uddipta Bhattacharjee, Ayush Jain, Shamik Kundu, Posham Ramesh, Shikhar Sanjay, and Priyambada

• Transportation Engineering
• Intelligent Transportation Systems
• Machine Learning
• +۲ مورد دیگر

Pranamesh Chakraborty serves as an Assistant Professor in the Department of Civil Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), where he specializes in Transportation Engineering with expertise spanning Intelligent Transportation Systems, Machine Learning, Big Data Analytics, and Naturalistic Driving Studies. Faculty position: Assistant Professor, Department of Civil Engineering Academic qualifications: PhD from Iowa State University (2019), M.Tech from IIT Kanpur (2014), B.E. from IIEST Shibpur (2012) Previous appointments: Assistant Professor at Techno India University and KIIT University Dr. Chakraborty's research program focuses on developing innovative computational approaches to transportation challenges, with particular emphasis on applying machine learning techniques to traffic management, incident detection, and policy analysis. His work bridges civil engineering principles with cutting-edge data science methodologies. Analysis of his publication record reveals a consistent research trajectory centered on data-driven transportation solutions, with increasing emphasis on deep learning applications and real-world policy implications. His work demonstrates strong interdisciplinary integration across engineering, computer science, and urban planning domains. Research Excellence Award, Iowa State University, 2019 Best Student Paper, TRB Managing Roadways and Transit Together Conference, Seattle, 2018 Student Essay Competition Winner, ITS America, San Jose, 2016 Academic Excellence Award, Indian Institute of Technology Kanpur, 2013 Dr. Chakraborty maintains an active research program with multiple publications in high-impact transportation journals. His previous experience includes serving as a Graduate Research Assistant at Iowa State University and teaching positions at multiple Indian institutions before joining IIT Kanpur.

• Intelligent Systems and Control
• Cognitive Robotics
• Nano-robotics
• +۹ مورد دیگر

Laxmidhar Behera is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, specializing in Intelligent Systems and Control. With over two decades of academic experience at IIT Kanpur and international research experience at institutions including Fraunhofer Institute of Autonomous Intelligent Systems in Germany, ETH Zurich, and University of Ulster, he has established himself as a leading researcher in cognitive robotics and intelligent control systems. Dr. Behera's research spans multiple cutting-edge domains including Cognitive Robotics, Nano-robotics, Vision based Control, Soft Computing, Information Retrieval in music and language, Semantic Information Processing, Physics of Complex Systems, Cyber Physical Systems, Formation Control of UAVs, Brain-Computer Interface (BCI), and Sanskrit Computational Linguistics. His interdisciplinary approach bridges traditional control theory with modern computational intelligence techniques, creating innovative solutions for complex real-world problems. His extensive publication record in top-tier journals like IEEE Transactions demonstrates his leadership in areas such as brain-computer interfaces, visual servoing, multi-robot systems, and music information retrieval. Notably, his work on quantum neural networks for EEG filtering and multisatellite formation control has received significant attention in the research community. UKIERI Standard Research Award 2008 Best Paper at International Conf. on Intelligent Sensors and Information Processing (ICISIP-2004) Best Paper at WoSco,02, Int. Conf. High-Performance Computing (HiPC, 2002) AICTE career award for young teacher (1997) Senior Member IEEE Multiple IEEE top accessed articles (2009-2010) As an Associate Editor for Autosoft Journal and Technical Committee Member for Intelligent Control at IEEE Control System Society, Dr. Behera actively contributes to the academic community. His laboratory in the Western Lab - 212A of the Department of Electrical Engineering serves as a hub for research in intelligent systems, where he mentors students and collaborates with researchers worldwide on cutting-edge projects in robotics, control systems, and computational intelligence.

Mathukumalli Vidyasagarمشاهده پروفایل

استاد

• Machine Learning
• Systems and Control Theory
• Computational Biology
• +۴ مورد دیگر

Mathukumalli Vidyasagar is a Distinguished Professor at the Indian Institute of Technology Hyderabad and previously held the SERB National Science Chair and Cecil & Ida Green Chair in Systems Biology Science at the University of Texas at Dallas. He earned his Ph.D. from the University of Wisconsin, Madison, and has authored 13 books and over 160 peer-reviewed papers.

Arijit Bishnuمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Randomized Algorithms
• Approximation Algorithms
• +۶ مورد دیگر

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.

Renu Johnمشاهده پروفایل

استاد

• Biomedical Imaging
• Optical Coherence Tomography
• Nanoparticles
• +۸ مورد دیگر

Renu John is a Professor in the Department of Biomedical Engineering at Indian Institute of Technology Hyderabad . He earned his Ph.D. in Physics (Optics) from IIT Delhi in 2006 and has held postdoctoral positions at Duke University and University of Illinois . He leads the Medical Optics and Sensors Laboratory (MOS) and co-founded the Center for Healthcare Entrepreneurship (CfHE) , focusing on affordable healthcare solutions for India. Research Interests : Biomedical Imaging, Optical Coherence Tomography (OCT), Digital Holography, AI/ML in Diagnostics, Microfluidic Biosensors, 3D Bioprinting, Nanoparticle-based Imaging, Optical Elastography. Awards : Best Paper & Poster Awards at international conferences (2018-2019), Samsung Innovation Award (2018) for smartphone-based oral cancer detection. Grants : Lead investigator for an ICMR Center of Excellence (15.2 Cr funding) in Medical Devices and Diagnostics. Students : Mentored over 20 researchers, including current and alumni Ph.D. candidates working on OCT, microfluidics, AI-driven imaging, and biosensor development. Labs & Innovations : The MOS Lab develops cutting-edge technologies like lensless microscopes, FF-OCT systems, and dual-modality biosensors. His team has filed 18 patents and published 117 international journal articles, with projects spanning from in vivo magnetomotive imaging to organ-on-chip platforms for disease modeling.