جست‌وجوی استاد و پژوهشگر

Sunita Sarawagiمشاهده پروفایل

استاد

• Machine Learning
• Data Analytics
• Databases
• +۱۰ مورد دیگر

Sunita Sarawagi is a Professor at Computer Science and Engineering , IIT Bombay, and a member of AI Labs@CSE . She is also associated with the Center for Machine Intelligence and Data Science (CMInDS), which she founded in 2020. Education: PhD in Computer Science from UC Berkeley (Thesis: Query Processing in Tertiary Memory Databases), BTech in Computer Science from IIT Kharagpur Research Interests span machine learning , data analytics , graphical models , and structured learning , with applications in text segmentation, sequence modeling, domain adaptation, and human-in-the-loop systems. Her publications reveal a strong focus on integrating data mining with database systems , temporal data analysis , and information extraction using probabilistic methods. Professional Activities include serving on the IEEE John Von Neumann Medal committee (2017-), VLDB 2011 Research Track Co-chair , and multiple program committee roles at top conferences like ICML, KDD, and SIGMOD. Labs & Teams : Leads the SS Lab , a research group focused on probabilistic graphical models, sequence modeling, and data integration techniques.

Ajit Rajwadeمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Ajit Rajwade is a Professor at the Department of Computer Science and Engineering , Indian Institute of Technology Bombay. His research spans Artificial Intelligence , Compressed Sensing , and Medical Imaging , with affiliations to the Centre for Machine Intelligence and Data Science and the Koita Centre for Digital Health . Education : PhD in Computer and Information Science and Engineering, University of Florida (2010) MSc in Computer Science, McGill University (2004) BTech in Computer Engineering, University of Pune (2002) His research interests focus on intelligent data acquisition, particularly in neural network analysis , graph signal processing , and medical imaging . He develops compressed sensing algorithms for inverse problems like tomography and MRI reconstruction , alongside applying group testing to pandemic response. Scientific awards include the Prof. S. P. Sukhatme Award (2024) and Departmental Teaching Excellence (2019). His publications demonstrate expertise in image restoration , noise modeling , and epidemiological algorithms . He has advised PhD students like Sabyasachi Ghosh and Jerin Geo James , with a focus on computationally efficient methods in medical imaging and machine learning .

Sharat Chandranمشاهده پروفایل

استاد

• Computer Graphics
• Computer Vision
• Visual Computing
• +۳ مورد دیگر

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.

Arpit Agarwalمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Human-AI Interaction
• +۴ مورد دیگر

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.

• Databases
• Data Mining
• Information Retrieval
• +۲ مورد دیگر

Dr. Arnab Bhattacharya is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Kanpur since December 2020. He previously served as Associate Professor (2014–2020) and Assistant Professor (2007–2014) at IIT Kanpur. Education: PhD in Computer Science (2007), University of California, Santa Barbara MS in Computer Science (2007), University of California, Santa Barbara Bachelor of Computer Science and Engineering (2001), Jadavpur University Research Focus spans Databases , Data Mining , Information Retrieval , and Artificial Intelligence . His work emphasizes graph analytics , skyline queries , probabilistic data , and knowledge graph management . Article Trends reveal expertise in graph neural networks , trajectory-aware systems , statistical significance in databases , and legal/medical data mining . His methodologies often integrate chi-square statistics , approximate indexing , and provenance tracking . Scientific Awards: IBM Faculty Research Award Yahoo! Faculty Research and Engagement Program Award Best Paper at COMAD 2011 Best Student Paper at COMAD 2010 Top-Five Student Paper at ICDM 2005 ICDM Student Travel Award sponsored by IBM Contact: Office RM 409, Department of Computer Science and Engineering, IIT Kanpur Email: arnabb@iitk.ac.in | Phone: +91-512-259-7650

Aditya T Siripuramمشاهده پروفایل

دانشیار

• Fourier analysis
• Signal processing
• Machine learning
• +۳ مورد دیگر

Aditya T Siripuram is an Associate Professor at the Indian Institute of Technology Hyderabad (IITH), holding joint appointments in the Department of Electrical Engineering and the Department of Artificial Intelligence. He completed his PhD at Stanford University and holds B.Tech and M.Tech degrees from IIT Bombay. Education: PhD in Electrical Engineering, Stanford University (2017) - GPA: 4.17/4 M.Tech in Electrical Engineering, IIT Bombay (2009) - GPA: 9.79/10 B.Tech in Electrical Engineering, IIT Bombay (2009) - GPA: 9.79/10 Research Interests: His research spans Fourier analysis, signal processing, machine learning, convex and combinatorial optimization, with applications in AI/ML and applied mathematics. His work particularly focuses on computational aspects of Fourier analysis, including fast DFT computation for structured signals, convolution idempotents, and graph-based signal processing techniques. His recent research directions involve developing efficient algorithms for computing Discrete Fourier Transforms for signals with structured frequency support, investigating relationships between additive structures in frequency domains and computational complexity, and exploring graph learning techniques under spectral constraints. Awards and Recognition: Excellence in Teaching Award, IIT Hyderabad (2019, 2022) Stanford Graduate Fellowship Qualcomm Innovation Fellowship (awarded to his PhD student Charantej Reddy P in 2021) Teaching and Service: He has taught courses including AI1110 Probability and Stochastic Processes, EE5609 Matrix Theory, EE5606 Convex Optimization, and EE5328 Introduction to Submodular Functions. He serves as Departmental Undergraduate Committee Chair for the Department of AI at IITH (2020-present) and was MTech Admissions Coordinator for the same department (2019-2022). Research Group: He currently advises three PhD students working on signal processing based graph learning techniques, DFT computation for structured signals, and coded computing problems.

Kaushik Nayakمشاهده پروفایل

دانشیار

• Semiconductor Devices
• Mesoscopic Electronics
• Nanoelectronics
• +۳ مورد دیگر

Kaushik Nayak is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad . His research spans semiconductor device physics, mesoscopic electronics, and electro-thermal effects in nanoscale transistors, with recent work on diamond MOSFETs, 2D material contacts, and thermal resistance in nano-sheet FETs. Ph.D., Indian Institute of Technology Bombay M. Tech., Microelectronics, IIT Bombay B.E., Electronics & Telecommunication, Utkal University He teaches advanced courses on semiconductor device modeling, mesoscopic electronics, and electromagnetic wave propagation. His publications focus on nanoelectronics, device variability, and high-temperature operations. Contact: knayak@ee.iith.ac.in .

Somnath Basuمشاهده پروفایل

استاد

• Metallurgical Engineering
• Materials Science
• Steelmaking
• +۷ مورد دیگر

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.

Saket Asthanaمشاهده پروفایل

استاد

• Ferroelectrics
• Energy Storage
• Piezoelectrics
• +۷ مورد دیگر

Prof. Saket Asthana is a Professor in the Department of Physics at the Indian Institute of Technology Hyderabad (IIT Hyderabad), where he leads the Advanced Functional Materials Laboratory (AFML). His academic qualifications include a Ph.D. from IIT Bombay, an M.Tech. from IIT BHU, and an M.Sc. from Banaras Hindu University. He has held postdoctoral positions at Osaka University (Japan), ICMCB-CNRS (France), and Kyungpook National University (South Korea). His research focuses on functional materials with emphasis on: Ferroelectrics and piezoelectric systems for energy storage Multiferroics and magnetoelectric composites Photocatalytic materials for energy conversion Lead-free relaxor ceramics and nanostructured oxides Cation engineering for property optimization Analysis of his 50+ publications reveals dominant themes in lead-free piezoelectric ceramics, rare-earth substituted bismuth ferrites, magnetocaloric effects, and photoelectrochemical materials. His work consistently bridges fundamental property characterization with applications in energy storage, sensors, and catalysis. Honors include being elected as a Fellow of the Royal Society of Chemistry . He has supervised 10+ PhD students and 15+ Master's students, with current advisees working on piezoelectric ceramics, multiferroic composites, and energy storage materials. His laboratory conducts research funded by DST-SERB, CSIR, DRDO, and international collaborations, including active projects on relaxor ferroelectrics (2020-2023) and organic solar cells (2019-2022). The Advanced Functional Materials Laboratory specializes in materials synthesis (hydrothermal/solid-state), structural characterization (XRD/SEM), and property measurements (ferroelectric/magnetic hysteresis, impedance spectroscopy, piezoelectric coefficient analysis).

Sandeep Sangalمشاهده پروفایل

استاد

• Physical Metallurgy
• Mechanical Metallurgy
• Materials Characterization
• +۳ مورد دیگر

Sandeep Sangal serves as a Professor in the Department of Materials Science & Engineering at the Indian Institute of Technology Kanpur. His academic career spans several decades with significant contributions to metallurgical research and education. As a distinguished faculty member at one of India's premier technical institutions, he has established himself as an expert in physical and mechanical metallurgy. Dr. Sangal's educational background includes a PhD (1989) and M.S. (1985) from the University of Manitoba, Canada, along with a B.Tech from IIT Kanpur (1982), demonstrating his strong foundation in materials science. His research interests focus on physical and mechanical metallurgy, particularly examining grain boundary phenomena, material characterization techniques, and industrial applications of metallurgical principles. His publication record reveals a consistent research trajectory spanning multiple decades, with significant contributions to understanding polycrystalline materials, grain boundary engineering, and metallurgical applications in industrial contexts. His work demonstrates both theoretical depth in fundamental metallurgical concepts and practical applications in industrial settings, particularly evident in his research on railway components and material characterization systems. Dr. Sangal maintains an active email contact (sangals@iitk.ac.in) and office presence within the Materials Science & Engineering Department at IIT Kanpur, where he continues to contribute to academic and research activities in the field of metallurgy.

Triratna Muneshwarمشاهده پروفایل

استادیار

• Materials for Semiconductor Devices
• Atomic Layer Deposition
• Atomic Layer Etching
• +۷ مورد دیگر

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 Chakrabartyمشاهده پروفایل

استاد

• Random Matrix Theory
• Heavy-Tailed Distributions
• Large Deviations
• +۵ مورد دیگر

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.

Prem Palمشاهده پروفایل

استاد

• MEMS Technology
• Silicon Micromachining
• MEMS-based sensors
• +۳ مورد دیگر

Prem Pal is a Professor in the Department of Physics at the Indian Institute of Technology Hyderabad. His work focuses on MEMS technology, silicon micromachining, and thin film applications in sensors and energy systems. Education : Ph.D. in MEMS from IIT Delhi (2004), M.Tech in Solid State Materials from IIT Delhi (1999) His research spans wet anisotropic etching, microfluidic channels, and advanced MEMS fabrication techniques. He has developed novel processes for Borofloat glass and silicon wafer processing. Key trends in his publications include isotropic/anisotropic wet etching, masking layer behavior, and optimization of etching solutions (e.g., NH4OH, KOH, NaOH) for MEMS devices. His work addresses surface texturization and structural dynamics of microcantilever beams. Laboratory : Prem Pal leads the MEMS & Micro/Nano Systems Laboratory at IIT Hyderabad, advancing microsystem technologies and semiconductor physics applications.

Subhas Chandra Misraمشاهده پروفایل

استاد

• Business Process Management
• Project Management
• Supply Chain Management
• +۷ مورد دیگر

Subhas Chandra Misra serves as a Professor in the Department of Management Sciences at the Indian Institute of Technology Kanpur. PhD from Carleton University, Canada M.S. from University of New Brunswick, Canada M.Tech. from IIT Kharagpur, India B.E. from Andhra University, India Professor Misra's research spans multiple domains within management sciences, with particular emphasis on business process optimization and information systems. His work bridges theoretical frameworks with practical applications in enterprise environments. His research portfolio demonstrates a strong focus on how technological solutions can enhance organizational efficiency and governance structures, particularly through data-driven approaches to business challenges. His expertise encompasses both traditional management disciplines and contemporary digital transformation areas, reflecting the evolving nature of business operations in the information age.

P.M. Mohiteمشاهده پروفایل

استاد

• Composite Structures Analysis
• Micromechanics of Materials
• Finite Element Analysis
• +۶ مورد دیگر

Dr. P.M. Mohite is a Professor at the Department of Aerospace Engineering , Indian Institute of Technology Kanpur , with a career spanning over two decades in composite materials research. He holds a PhD in Aerospace Engineering from IIT Kanpur (2007) and has been a Visiting Assistant Professor (2008-2009) and later Assistant , Associate , and Professor (2019-present) at IIT Kanpur. Research Interests include: Advanced composite structures analysis Micromechanics and damage modeling Finite element adaptive methods Metal plasticity and polymer composites Aerostructural optimization Key Publications focus on damage mechanics, structural optimization, and micromechanical characterization, with recent works on evolutionary algorithm-based composite design and boundary layer effects in laminates. Scientific Awards received: Best Student Award (B.E. Mechanical, 1998) AIAA Students Paper Contest Finalist (2006) Teaching Contributions include core courses like Composite Materials and Finite Element Methods , alongside advanced postgraduate topics in aerospace structural analysis. Advising has impacted 30+ M.Tech/Ph.D. students, including international collaborations with Université de Biskra (Algeria) and Ecole Centrale de Nantes (France).