جست‌وجوی استاد و پژوهشگر

Dhananjay Dhamdhereمشاهده پروفایل

استاد

• Optimizing Compilers
• Partial Redundancy Elimination
• Operating Systems
• +۷ مورد دیگر

Dhananjay Dhamdhere is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay (IIT Bombay). He has maintained an active research and teaching career since at least the 1980s, with current involvement in course instruction and academic initiatives. Research Interests: Optimizing Compilers and Partial Redundancy Elimination Operating Systems and Distributed Systems Detection of Data Races and Atomicity Violations Safety issues in Dynamic Software Updating Debugging of Optimized Programs His research demonstrates a consistent focus on practical compiler optimizations, evolving from foundational work in data flow analysis to contemporary challenges in dynamic software updating. The publications show particular expertise in making theoretical compiler concepts implementable in real-world systems, with significant contributions to partial redundancy elimination techniques. Research Funding: Department of Electronics research grant on Optimizing Compilers (1985) Grants from Tandem Computers (1995), Intel (1998), Microsoft Research (2001, 2002), and Sun Microsystems (2001, 2002) Professor Dhamdhere has successfully transferred technology to industry through his Gensat system, a generator for static analysis tools. He actively contributes to academic culture improvement through the Forum for Academic Culture (FAC), which he co-founded in 2013 to address student motivation, teaching methodologies, and large class challenges at IIT Bombay.

• Game Theory
• Distributed Systems
• Temporal Logics
• +۲ مورد دیگر

Sunil Easaw Simon serves as an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur. His academic home is within one of India's premier technical institutions, where he contributes to both teaching and research in theoretical computer science. Education: PhD, Institute of Mathematical Sciences (2010) MSc, Chennai Mathematical Institute (2003) Dr. Simon's research focuses on the theoretical foundations of computer science, with particular emphasis on Game Theory, Distributed Systems, Temporal Logics, and Verification . His work bridges mathematical theory with computational applications, exploring how strategic interactions can be modeled and analyzed within computational frameworks. His research interests span both foundational theoretical questions and practical applications in multi-agent systems. Analysis of his publication record from 2009-2013 reveals a consistent research trajectory centered on game-theoretic approaches to computational problems. His work appears in high-quality venues including the Journal of Logic and Computation and major theoretical computer science conferences such as CONCUR and FSTTCS. The publications demonstrate expertise across multiple subdomains including social network games, weakly acyclic games, communication protocols under imperfect information, and verification frameworks. Dr. Simon maintains an active research profile with publications spanning multiple theoretical computer science subdisciplines. His office is located in CS 206 at IIT Kanpur, where he continues to contribute to the academic mission of the institution through teaching and scholarly work in theoretical computer science.

Sri Vanamalla Venkataramanمشاهده پروفایل

دانشیار

• Operations Research
• Optimization
• Game Theory
• +۳ مورد دیگر

Sri Vanamalla Venkataraman is an Associate Professor in the Department of Management Sciences at the Indian Institute of Technology Kanpur (IIT Kanpur). With a strong academic foundation in mathematics and operations research, he has established himself as a leading researcher in optimization, game theory, and supply chain management systems. Education: PhD in Management Studies, Indian Institute of Science (IISc) Bangalore (2010) MPhil in Mathematics, University of Madras (1999) MSc in Mathematics, Indian Institute of Technology (IIT) Madras (1995) Professor Venkataraman's research focuses on Applied Operations Research, Optimization, and Game Theory with particular emphasis on supply chain coordination, revenue management, and sustainable operations. His recent work (2023-2025) demonstrates a significant shift toward addressing sustainability challenges through operations research methodologies, with papers examining net-zero emissions in agricultural supply chains, strategic carbon emission controls, and sustainable deployment of electric vehicles through government policy interventions. His research bridges theoretical foundations with practical applications across transportation, agriculture, and public distribution systems. His extensive publication record in top-tier journals including Annals of Operations Research, Journal of the Operational Research Society, and Computers & Industrial Engineering reflects both theoretical rigor and practical relevance. The articles show consistent methodological sophistication with applications spanning airline revenue management, agricultural supply chains, and sustainable operations. Awards: Prof M.N.Gopalan award for best PhD thesis on Operations Research at Operational Research Society of India (ORSI)-2010 Professor Venkataraman has successfully guided PhD students including Ranjeet Singh Rajput (completed 2022) and Dereje Asfaw (completed 2017), focusing on contract design and mechanisms for agri-business supply chains. His teaching portfolio includes IME602: Probability and Statistics, IME605: Operations Research for Management, MBA651: Quantitative Methods for Decision Making, IME636: Introduction to Game Theory, IME642: Operations Management, and IME637: Advanced Decision Models, reflecting his expertise across quantitative business disciplines.

K. V. Raghavanمشاهده پروفایل

دانشیار

• Programming Languages
• Program Analysis
• Software Engineering
• +۵ مورد دیگر

K. V. Raghavan is an Associate Professor at the Department of Computer Science and Automation in Indian Institute of Science, Bangalore . His research focuses on programming languages , program analysis , and software engineering , with an emphasis on automated tools for program verification and transformation. Teaching: Courses include Program Analysis and Verification (Aug-Dec 2024) and Principles of Distributed Software (Jan-Apr 2025), covering topics like abstract interpretation , dataflow analysis , lambda calculus , Hoare logic , Docker , and Kubernetes . Service: Served as PC co-chair for the Int. Symposium on Automated Technology for Verification and Analysis (ATVA 2025) . Research: Active opportunities for Project Assistant/Associate and Post Doc positions in his group.

Dinesh Acharya Uمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Image Processing
• +۴ مورد دیگر

Dinesh Acharya U serves as a Professor in the Department of Computer Science and Engineering at Manipal Institute of Technology, Manipal University. His academic leadership spans both foundational computer engineering and interdisciplinary medical applications, with research output consistently growing since 2006. Current affiliations include active roles at the School of Computer Engineering with verified ORCID profile (0000-0002-0304-4725) and institutional webpage. Research interests prominently feature Machine Learning (68% fingerprint weight), Data Mining (40%), and Medical Informatics applications. His work bridges computer science with healthcare challenges, particularly in neonatal sepsis detection, diabetic complications, and low-resource language processing. The research fingerprint shows strong emphasis on prediction (52%), algorithms (53%), and India -specific healthcare contexts (40%). Publication trends reveal accelerating output since 2018, with 12 papers in 2022 and continued productivity through 2025. Recent work demonstrates interdisciplinary convergence, particularly in Medical AI (neonatal sepsis, diabetic kidney disease) Natural language processing for low-resource languages Transformer-based architectures across domains Notable patterns include increasing clinical collaborations and emphasis on practical implementation tools. Professional recognition includes an h-index of 13 with 596 citations across 71 research outputs. Key distinctions: Scopus profile verification ORCID registration Multi-institutional collaborations evident in co-authorship Academic supervision and grant activity cannot be confirmed from available data, though 15+ recent publications suggest active research teams. Current projects appear focused on Medical diagnostic tool development Low-resource language technology Clinical decision support systems with evident laboratory infrastructure supporting computational healthcare research.

Suyash P. Awateمشاهده پروفایل

استاد

• Medical image computing
• Machine learning
• Image analysis
• +۲ مورد دیگر

Suyash P. Awate serves as the Asha and Keshav Bhide Chair Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Bombay, Mumbai, India. His research spans medical image computing, machine learning, image analysis, computer vision, and statistical modeling and inference. His work focuses on developing novel computational methods for medical image analysis, reconstruction, and quality enhancement. Prof. Awate's research interests center on medical image computing, where he develops advanced machine learning techniques for medical image reconstruction, segmentation, and quality enhancement. His work addresses critical challenges in medical imaging such as low-dose PET/CT imaging, uncertainty quantification in segmentation, robustness to out-of-distribution data, and accelerated MRI/fMRI acquisition. He has pioneered methods combining variational inference, expectation maximization, and deep learning to improve medical image quality while reducing radiation exposure and scan times. His research has significant clinical applications in neuroimaging, tumor analysis, and brain function mapping. His recent publications demonstrate a strong trend toward integrating deep learning with classical statistical methods, particularly focusing on uncertainty-aware models for medical image analysis. His work consistently addresses the challenge of robustness in medical imaging, developing methods that maintain performance even with degraded input data or distribution shifts. A significant portion of his research targets clinical applications, particularly in neuroimaging and oncology, with emphasis on practical implementation for real-world medical settings. Prof. Awate actively mentors PhD, MTech, and BTech students at IIT Bombay. His current PhD students include Vatsala Sharma (awarded Microsoft Research India PhD Award), Jimut Bahan Pal (CMInDS Fellow, Prime Minister's Research Fellow), Tejomay Padole (TCS Research Fellow), Subhankar Nag, and Koustav Pal. He also guides MTech/MS students Soumya Mukherjee, Jay Gorakhiya, and Russel Abreo, along with BTech student Varshith Anumalasetty. He teaches several courses including CS 736: Medical Image Computing (inaugurated in 2014), CS 663: Fundamentals of Digital Image Processing, CS 215: Data Analysis and Interpretation, CS 740: Mathematics for Visual Computing, and CS 101: Computer Programming and Utilization. His laboratory focuses on developing computational methods for medical image analysis, with particular emphasis on uncertainty quantification, robust deep learning for medical imaging, and accelerated acquisition techniques. The research group maintains strong collaborations with medical institutions to ensure clinical relevance of their computational methods.

Rushikesh K. Joshiمشاهده پروفایل

استاد

• Software Engineering
• Distributed Systems
• Program Analysis
• +۵ مورد دیگر

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.

Supratim Biswasمشاهده پروفایل

استاد

• Programming Languages
• Compiler Optimization
• Parallelizing Compilers
• +۲ مورد دیگر

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.

Hemant Gehlotمشاهده پروفایل

استادیار

• Transportation engineering
• Transportation network modeling
• Combinatorial optimization
• +۲ مورد دیگر

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.

• High Performance Computing
• Parallel Computing
• Computer Systems
• +۴ مورد دیگر

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.

• Control Engineering
• Nonlinear dynamical systems
• Control of Unmanned vehicles
• +۳ مورد دیگر

Soumya Ranjan Sahoo is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. His academic career at IIT Kanpur began with a contract position as Assistant Professor in 2014, progressing to Assistant Professor in 2016, and currently holding the position of Associate Professor since December 2020. Prior to joining IIT Kanpur, he worked as a Scientist Fellow at the National Aerospace Laboratories in Bangalore. PhD in Systems and Control Engineering from IIT Bombay (2013) Thesis Title: Coordination problems with minimal sensing and coarse actuation Thesis Supervisors: Prof. Ravi N. Banavar and Dr. Arpita Sinha B.Tech in Electrical Engineering from University College of Engineering, Burla, Odisha (2008) Dr. Sahoo's research spans the complex intersection of control theory and practical engineering applications. His work primarily focuses on nonlinear dynamical systems, with significant contributions to the control of unmanned vehicles and coordinated control systems. His research has evolved to address modern power system challenges, particularly in the domain of AC and DC microgrids, where he has developed innovative control strategies for improved performance. His work on discontinuous systems demonstrates his ability to tackle mathematically challenging control problems with practical implications. Analysis of Dr. Sahoo's publication record reveals a clear evolution from fundamental control theory to applied research with significant practical impact. His early work focused on theoretical aspects of multi-agent systems and network control, which has progressively shifted toward power systems applications, particularly microgrids. The consistent theme across his publications is the development of robust control strategies that work effectively under realistic constraints such as communication delays, incomplete information, and system heterogeneity. His research bridges theoretical control concepts with practical engineering implementations, particularly in the domains of autonomous systems and modern power grids. Dr. Sahoo teaches several key courses in the Electrical Engineering curriculum including Introduction to Electrical Engineering, Control Systems Analysis, Basics of Modern Control Systems, Nonlinear Systems, Adaptive Control Theory, and advanced topics in Nonlinear Systems. His teaching portfolio reflects his deep expertise in control theory and its applications. His laboratory work, particularly through the DiSCo Lab (as referenced in his homepage), focuses on practical implementations of control algorithms for various applications including unmanned vehicle coordination and microgrid management. This laboratory work bridges the gap between theoretical control design and real-world implementation challenges.

K R Guruprasadمشاهده پروفایل

دانشیار

• Robotics and Autonomous Systems
• Motion Planning
• Multi-Robot Systems
• +۷ مورد دیگر

K R Guruprasad is an Associate Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). With a PhD in Aerospace Engineering from the Indian Institute of Science (IISc) Bangalore, he has established himself as a leading researcher in robotics, motion planning, and multi-robot systems. His research interests span a wide range of topics in robotics including Robotics-Mechanics and Control, Motion Planning, Multi Robots Systems, Cooperative Control, Exo-Skeleton Control, and Voronoi Partition applications. His work particularly focuses on UAV/Drones motion planning, mobile manipulation, and artificial intelligence applications in robotics. His research integrates theoretical foundations with practical implementations, evidenced by his numerous publications in high-impact journals. Prof. Guruprasad's scholarly contributions include a book titled 'Robotics: Mechanics and Control' (PHI, 2019) and several edited volumes. His publication record shows consistent output with an h-index of 11, i10 index of 14, and 382 citations according to Scopus data. His recent work demonstrates strong focus on multi-robot coverage algorithms, UAV applications, and distributed control systems. Among his recognitions are a best presentation award at the IISc-IBM Research Workshop (2008) and a best paper award finalist at DARS 2014. His research has practical applications in search and rescue operations, landmine detection, and autonomous exploration. Prof. Guruprasad maintains active collaborations with researchers globally and has contributed significantly to advancing robotics research in India through his work at IIT Kanpur's Mechanical Engineering department.

• Distributed Computing
• Network Algorithms
• Mobile Robotics
• +۴ مورد دیگر

Anisur Rahaman Molla is an Associate Professor at the Indian Statistical Institute (ISI) in Kolkata, India, affiliated with the Cryptology and Security Research Unit (CSRU) and the R. C. Bose Centre for Cryptology and Security . His work spans distributed computing, network algorithms, and mobile robotics, with a focus on fault tolerance and Byzantine agreement. Education : PhD in Computer Science from Nanyang Technological University, Singapore (2014) M.Tech in Computer Science from ISI Kolkata (2010) M.Sc in Pure Mathematics from Calcutta University (2007) B.Sc in Mathematics (Honors) from Calcutta University (2005) Research Trends : His recent work emphasizes mobile agent algorithms for tasks like dispersion, leader election, and graph traversal, with applications in fault-tolerant systems and dynamic networks. Papers frequently address message complexity, Byzantine resilience, and optimization in unoriented/oriented grids. Scientific Awards : Best Contributor Award (PhD Forum), ICDCN 2013 Advising : Supervised Prabhat Kumar Chand (current PhD student at ISI) and graduated Manish Kumar (PhD, ISI 2023). Co-supervised master's and bachelor's theses at the University of Freiburg and ISI. Labs & Collaborations : Works within the CSRU and R. C. Bose Centre at ISI. Collaborates with institutions like IIT Madras, University of Freiburg, and ETH Zürich.

Palash Deyمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Parameterized Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Palash Dey is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Kharagpur. His research lies at the intersection of theoretical computer science and algorithmic game theory, with a primary focus on computational social choice, voting theory, and parameterized algorithms. His research interests include: Theoretical Computer Science Parameterized Algorithms Approximation Algorithms Algorithmic Game Theory Computational Social Choice Voting Theory Algorithmic Fairness Network Games His recent publications, spanning from 2023 to 2025, demonstrate a strong and consistent research trajectory in the analysis of voting systems, manipulation, and fairness. The articles focus on complex problems such as bribery, gerrymandering, rank aggregation, and networked public goods, primarily using tools from parameterized complexity and algorithmic game theory. Key venues for his work include AAMAS, IJCAI, AAAI, and Theoretical Computer Science, indicating a high impact in the fields of AI and theoretical computer science. His professional service includes being the Newsletter and Social Media Chair of the IEEE Kharagpur Section and serving on the Senior Program Committee for AAAI (2021-2024) and the Program Committee for AAAI, IJCAI, AAMAS, and COMSOC. He has also organized significant workshops such as CALDAM 2019 and GAME-ARTS. Palash Dey actively advises Ph.D. students, including Sipra Singh, Koustav De, Ashlesha Hota, and Narayan Sharma. He teaches courses such as Algorithms II, Randomized Algorithm Design, and Algorithmic Game Theory. His email is palash.dey@cse.iitkgp.ac.in.

Siddharthaمشاهده پروفایل

استادیار

• Energy Engineering
• Electrical Engineering
• Energy Conservation
• +۴ مورد دیگر

Siddhartha is an active Assistant Professor - Senior Scale in the Department of Electrical and Electronics Engineering at the Manipal Institute of Technology, a constituent unit of Manipal Academy of Higher Education in Manipal, Karnataka, India. His research focuses on sustainable energy systems with emphasis on electric vehicle infrastructure and building energy efficiency. His educational qualifications include: Bachelor of Engineering (BE) Master of Technology (MTech) Research interests span: Energy Conservation in Residential and Educational Buildings Electric Vehicle Charging Infrastructure Optimization Weather Impact on Energy Consumption Thermal Comfort Modeling Genetic Algorithm Applications Urban Energy Planning His work bridges computational optimization with practical energy challenges in Indian urban contexts, particularly Guwahati city. Analysis of his 12 research outputs (2016-2024) reveals increasing focus on transportation electrification since 2023, while maintaining core expertise in building energy systems. Recent publications demonstrate sophisticated application of non-dominated sorting genetic algorithms to charging station placement, building on earlier foundational work in residential energy conservation. No scientific awards or honors were documented in the provided information. Details regarding graduate student supervision, research grants, or collaborative funding mechanisms were not specified in the source material. The profile does not reference any dedicated research laboratories, centers, or structured research teams associated with his academic activities.