جست‌وجوی استاد و پژوهشگر

• Databases
• Algorithms

Sumit Ganguly is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), where he has established himself as a leading researcher in database systems and algorithms. Education: PhD in Computer Science, University of Texas, Austin (1992) MS in Computer Science, University of Texas, Austin (1989) B.Tech in Computer Science, IIT Kanpur (1987) Professor Ganguly's research primarily focuses on database systems with special emphasis on algorithms for data streams. His work explores the theoretical foundations and practical implementations of database technologies, particularly in the context of streaming data where traditional database approaches face significant challenges. His research has contributed to developing efficient algorithms for frequency estimation, sampling techniques, and processing hybrid frequency moments in data streams, addressing critical challenges in big data analytics. His publications demonstrate a consistent focus on data stream algorithms, with significant contributions spanning from 2008 to 2012. These works explore connections between expander graphs and data stream processing, deterministic data structures, and methods for estimating various statistical properties of streaming data. His research bridges theoretical computer science with practical database applications. Professor Ganguly maintains an active research program within the Department of Computer Science and Engineering at IIT Kanpur, contributing to the institution's reputation for excellence in theoretical computer science and database systems research.

Pradeesha Ashokمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Algorithms
• Graph Theory
• +۳ مورد دیگر

Dr. Pradeesha Ashok is an Associate Professor and Controller of Examinations at IIIT Bangalore. She holds a Ph.D. from the Indian Institute of Science, Bangalore, and previously worked as a Postdoctoral Fellow at the Institute of Mathematical Sciences, Chennai. Her research focuses on Theoretical Computer Science, with specializations in Algorithms, Graph Theory, Combinatorics, and Parameterized Complexity. Her research interests include geometric problems such as polygon guarding, covering, and packing, as well as conflict-free coloring in graphs and hypergraphs. She has contributed to developing exact and parameterized algorithms for these problems. Dr. Ashok has also taught courses like Exact and Parameterized Algorithms, Graph Theory, and Design and Analysis of Algorithms. Her publications span conferences like IWOCA, CSR, and COCOON, as well as journals such as Discrete Applied Mathematics and SIAM Journal on Discrete Mathematics. Her work emphasizes algorithmic efficiency and combinatorial optimization in geometric and graph-theoretic contexts. Dr. Ashok has advised several students, including PhD candidates and MTech thesis students, focusing on topics like the chromatic art gallery problem and parameterized complexity of coloring problems. She is affiliated with the Department of Computer Science & Engineering at IIIT Bangalore and contributes to the institute's academic governance through her role as Controller of Examinations. Her research also extends to geometric separability, bichromatic covering problems, and experimental studies of the Steiner Tree problem. She collaborates on projects involving theoretical and applied aspects of computational geometry and algorithms.

Sourav Chakrabortyمشاهده پروفایل

استاد

• Theoretical Computer Science
• Boolean Functions
• Quantum Complexity
• +۴ مورد دیگر

Sourav Chakraborty is a Professor in the Advanced Computing and Microelectronics Unit (ACMU) of the Computer and Communication Sciences Division at the Indian Statistical Institute (ISI), Kolkata, India. He joined ISI in July 2018 after serving as faculty at Chennai Mathematical Institute from 2010-2018. Previously, he held postdoctoral positions at Centrum Wiskunde & Informatica (CWI) in Amsterdam and Technion in Israel. Education: Ph.D. in Computer Science, University of Chicago (2008) M.S. in Computer Science, University of Chicago (2005) B.Sc. in Mathematics, Chennai Mathematical Institute (2003) Research Focus: Professor Chakraborty specializes in Theoretical Computer Science with emphasis on classical and quantum complexity of Boolean functions, including sensitivity analysis, property testing, and quantum database search. His work extends to graph algorithms, electronic commerce mechanisms, and coding theory. His research explores fundamental questions in computational complexity through innovative mathematical frameworks. Publication Trends: Recent work demonstrates a strong focus on property testing, sampling algorithms, and complexity theory, with significant contributions to streaming algorithms, Boolean function analysis, and quantum query complexity. His publications frequently appear in top theoretical computer science venues and exhibit consistent innovation in algorithm design and complexity boundaries. Awards & Honors: Praise from Donald E. Knuth for streaming algorithms research Inclusion in Oded Goldreich's 'my choices' list for Conditional Sampling and Huge-Object Model work Chakraborty's function named in his honor for Sensitivity Conjecture contributions Academic Service: Teaches courses in discrete mathematics and theoretical computer science, with detailed course materials available through institutional pages. Organized workshops including the 2020 Workshop on Sensitivity and Query Complexity at ISI.

Chethan Kamathمشاهده پروفایل

استادیار

• Cryptography
• Theoretical Computer Science
• Foundations of Cryptography
• +۵ مورد دیگر

Chethan Kamath is an Assistant Professor in the Department of Computer Science and Engineering at IIT Bombay, where he is a member of the Theory Group and Trust Lab. His primary research focus is on cryptography, particularly its foundations, with broader interests extending to theoretical computer science. His educational journey includes: PhD from IST Austria (2014-2020) under Krzysztof Pietrzak, with thesis titled "On the Average-Case Hardness of Total Search Problems" Master's in CS from IISc Bangalore (2010-2013) under Sanjit Chatterjee, with thesis titled "Constructing Provably Secure Identity-Based Signature Schemes" Bachelor's in CS from University of Kerala (2005-2009) at TKM College of Engineering, Kollam Dr. Kamath's research interests span the theoretical foundations of cryptography, with particular focus on secure computation, complexity theory, and cryptographic hardness assumptions. His work often bridges theoretical computer science with practical cryptographic applications, exploring the boundaries of what can be efficiently computed while maintaining security guarantees. His research frequently addresses fundamental questions about the relationship between cryptographic primitives and complexity classes, especially the PPAD and TFNP complexity classes. His recent publications demonstrate a consistent focus on foundational aspects of cryptography, with particular emphasis on secure computation (garbled circuits, Yao's protocol), proofs systems (proofs of work, proofs of exponentiation), and complexity-theoretic aspects of cryptographic primitives. A notable trend is his exploration of the connections between complexity classes like PPAD and cryptographic assumptions, as well as his work on verifiable delay functions and their underlying number-theoretic assumptions. His research often employs tools from algorithmic graph theory (treewidth, separators) to analyze cryptographic protocols. His notable scientific achievement includes: Azrieli Fellowship during his post-doc at Tel Aviv University Dr. Kamath actively mentors students and researchers, currently advising several PhD and MS students at IIT Bombay, often in collaboration with Sruthi Sekar. His service to the academic community includes extensive program committee memberships for major conferences including Crypto, Eurocrypt, and TCC, demonstrating his standing in the cryptographic research community. He has co-organized educational events like the "Introduction to Cryptography" school as part of the ACM India Summer School 2025 and the "Theoretical Foundations of Cryptography" school as part of the ACM India Summer School 2024. He leads research activities within the Trust Lab at IIT Bombay, which focuses on theoretical and applied aspects of cryptography and security. The lab actively recruits MS/PhD students and post-docs, with ongoing research in foundational cryptography and its applications to secure computation, verifiable delay functions, and complexity-theoretic aspects of cryptographic security.

Surajمشاهده پروفایل

استادیار

• Data Management
• Fairness
• Computational Geometry
• +۳ مورد دیگر

Suraj is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay, where he joined on January 31, 2024. He completed his PhD from the University of Texas at Arlington under the supervision of Dr. Gautam Das. His educational background includes: PhD in Computer Science and Engineering, University of Texas at Arlington Suraj's research spans Data Management, Fairness, Computational Geometry, Graph Algorithms, and Metric Space, with a focus on designing efficient algorithms for complex systems. His work bridges theoretical computer science with practical applications in data-intensive domains, emphasizing ethical considerations in algorithmic design and geometric problem-solving approaches. Analysis of his recent publications reveals a strong interdisciplinary trajectory merging computer science with active matter physics. Key trends include topological defect dynamics in biological systems, geometric control of physical phenomena, and pattern formation in non-equilibrium active matter - demonstrating significant crossover between algorithmic thinking and biophysical modeling. No scientific awards or fellowships are mentioned in the available materials. Suraj advises graduate students in the Department of Computer Science and Engineering, with research supported by institutional grants enabling his dual focus on data management systems and active matter physics. His collaborative work spans computer science and biophysics laboratories. He is actively integrated into IIT Bombay's research ecosystem, collaborating across departments on projects that unite computational theory with physical modeling of complex systems.

• Algorithms
• Combinatorics
• Complexity Theory
• +۳ مورد دیگر

Sundar Vishwanathan is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay (IIT Bombay), where he has established himself as a leading researcher in theoretical computer science. His academic career spans over three decades with consistent contributions to algorithms, combinatorics, and complexity theory. His research interests form a cohesive body of work focused on theoretical foundations of computing: Algorithms (particularly approximation algorithms, online algorithms, and randomized algorithms) Combinatorics and extremal set theory Complexity theory and circuit lower bounds Graph theory and graph algorithms Combinatorial optimization problems Vishwanathan's publication record demonstrates remarkable consistency and depth, with publications spanning from 1990 to 2024. His recent work focuses on graph algorithms (particularly maximum matching problems), approximation algorithms for combinatorial optimization, and circuit complexity. He has developed innovative techniques using linear algebra, combinatorial methods, and probabilistic analysis to solve challenging theoretical problems. His approach often bridges theoretical insights with practical algorithmic considerations. His collaborative work spans multiple research groups, with frequent co-authorships with researchers such as Ashish Chiplunkar, Sumedh Tirodkar, and Sreyash Kenkre. His research has evolved from foundational work in online graph coloring in the 1990s to more specialized topics in combinatorics and recently to circuit lower bounds, showing both depth in core areas and adaptability to evolving research landscapes.

M. Rajesh Kannanمشاهده پروفایل

استادیار

• Combinatorics
• Spectral Graph Theory
• Matrix Theory
• +۱۲ مورد دیگر

M. Rajesh Kannan is an Assistant Professor at the Department of Mathematics, Indian Institute of Technology Hyderabad. He holds a Ph.D. from IIT Madras and has contributed significantly to combinatorics, spectral graph theory, and matrix theory. Education 2000: SSLC, Municipal Thiru Vi Ka High School, Srivilliputtur 2002: H.Sc., G.S.H. Higher Secondary School, Srivilliputtur 2005: B.Sc., Mathematics, ANJA College, Sivakasi 2008: M.Sc., Mathematics, ANJA College, Sivakasi 2013: Ph.D., Mathematics, Indian Institute of Technology Madras Research Interests Combinatorics Spectral Graph Theory Matrix Theory Functional Analysis Pure Mathematics Scientific Awards Excellent Young Teacher Award 2020, IIT Kharagpur Advising and Grants Supervised 3 Ph.D. students and 12 Master's students Active mentorship in spectral graph theory and matrix theory Secured multiple grants from SERB, DST, and IIT Hyderabad/Kharagpur

Rakesh Venkatمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Approximation Algorithms
• Hardness of Approximation
• +۱ مورد دیگر

Rakesh Venkat is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad. His research focuses on Theoretical Computer Science, including approximation algorithms, hardness of approximation, and communication complexity. Education : Ph.D., Tata Institute of Fundamental Research (TIFR), Mumbai. Research Trends : His work addresses fundamental challenges in algorithm design, such as optimizing cache misses, improving clustering algorithms, analyzing graph expansion, and exploring embedding techniques. Publications span top-tier conferences like APPROX, FSTTCS, ICALP, and ITCS, with collaborations at institutions including HUJI, TIFR, and IIT-Bombay. Teaching : Courses taught include Approximation Algorithms, Advanced Data Structures, Discrete Mathematics, and Spectral Graph Theory.

Subrahmanya Swamy Peruruمشاهده پروفایل

استادیار

• Wireless Networks
• Artificial Intelligence
• Probabilistic Graphical Models
• +۲ مورد دیگر

Subrahmanya Swamy Peruru is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). His research focuses on wireless networks, artificial intelligence, and probabilistic graphical models, contributing significantly to the field of network optimization and machine learning applications in communication systems. Dr. Peruru completed his educational journey with excellence: PhD in Electrical Engineering from Indian Institute of Technology Madras (2018) M.S. (by Research) from Indian Institute of Technology Madras (2018) B.Tech in Electronics and Communication Engineering from Sastra University (2011) Dr. Peruru's research interests lie at the intersection of wireless communications and artificial intelligence. His work primarily focuses on developing efficient algorithms for wireless network scheduling, leveraging reinforcement learning and graph neural networks to optimize network throughput and minimize delays. He has made significant contributions to CSMA (Carrier Sense Multiple Access) protocols, particularly in adapting them to SINR (Signal-to-Interference-plus-Noise Ratio) models using advanced approximation techniques from statistical physics. His research on probabilistic graphical models has enabled more efficient network resource allocation and has potential applications in 5G and beyond wireless systems. Dr. Peruru's interdisciplinary approach bridges theoretical computer science, electrical engineering, and machine learning to solve practical challenges in modern communication networks. His publication record demonstrates a consistent focus on wireless network optimization, with a recent shift toward incorporating machine learning techniques. Starting with foundational work on CSMA protocols and regional approximations (2015-2018), his research has evolved to include reinforcement learning (2023) and graph neural networks (2021) for network scheduling. This progression reflects the broader trend in networking research toward data-driven and AI-enhanced approaches. His work spans both theoretical contributions (approximation algorithms, convergence analysis) and practical implementations (scheduling algorithms with throughput guarantees). Dr. Peruru previously served as a Senior Research Engineer in the Machine Learning R&D team at Pramati Technologies, Chennai (2018-2020), where he likely applied his academic expertise to industry challenges before joining IIT Kanpur as faculty.

• Computational Complexity Theory
• Graph Theory
• Theoretical Computer Science

Raghunath Tewari is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur. His academic journey includes a PhD from the University of Nebraska-Lincoln (2011), an MS from the same institution (2007), and a B.Sc. from Chennai Mathematical Institute (2005). Dr. Tewari's research focuses on Computational Complexity Theory and Graph Theory , with particular expertise in space complexity, unambiguous computations, and planar graph algorithms. His work bridges theoretical computer science with practical applications in graph algorithms and computational models. His recent publications (2009-2012) demonstrate a consistent research trajectory in computational complexity, particularly examining space-bounded computations and graph-theoretic problems. His work frequently appears in high-impact theoretical computer science venues including ACM Transactions on Computation Theory and Journal of Computer and System Sciences. Outstanding Ph.D. Student Award Outstanding Masters Student Award Dr. Tewari teaches courses in Theoretical Computer Science and Introduction to Programming, contributing to both foundational and advanced computer science education at IIT Kanpur. His office is located in Room 514 of the Computer Science and Engineering Department building at IIT Kanpur.