Find Academic Supervisors

• Algorithms for Big Data
• Parallel Computing
• External-Memory Algorithms
• +5 more

Ulrich Meyer is a Professor at the Institute for Computer Science at Goethe University Frankfurt. He serves as a prominent researcher in algorithms for big data, with extensive contributions to parallel and external-memory graph algorithms. His work spans theoretical foundations and practical implementations for processing large-scale data sets. Spokesperson of the DFG priority program (SPP 1736) on Algorithms for Big Data in Germany SEA23 Symposium on Experimental Algorithms, Steering Committee Chair ALENEX23 Algorithm Engineering and Experiments, Program Committee Member Professor Meyer's research interests focus on the theoretical and experimental aspects of processing large data sets on advanced computational models. His work particularly emphasizes parallel and external-memory graph algorithms, with recent focus on efficient large-scale network generation according to various stochastic models. His research has produced significant contributions including the parallel Delta-Stepping algorithm (which received the ESA Test of Time Award in 2019) and the first BFS approach with sublinear I/O. He has also explored more specialized topics like energy-efficient sorting (with records in the JouleSort competition 2009/10 and the Germany Land of Ideas Award) and fragile computing (which earned him a best-paper award at ESA 2019). His recent publications demonstrate a strong focus on graph algorithms, network generation, and parallel computing techniques. The research trends show consistent advancement in scalable algorithms for massive graphs, with particular emphasis on efficient sampling methods, shortcutting techniques, and communication-free distributed approaches. His work bridges theoretical computer science with practical engineering considerations for real-world big data applications. ESA Test of Time Award 2019 for Parallel Delta-Stepping algorithm Records in the JouleSort competition 2009/10 Germany Land of Ideas Award Best-paper award at ESA 2019 for fragile computing research Professor Meyer has made substantial contributions to the academic community through his leadership in the DFG priority program on Algorithms for Big Data, which has fostered significant research collaborations across Germany. His extensive publication record in top venues demonstrates sustained research productivity and impact in the algorithms community. While specific grant details aren't provided in the text, his role as spokesperson for a major DFG priority program indicates substantial research funding and leadership responsibilities. His work appears to be conducted within collaborative research environments focused on algorithm engineering and experimental evaluation. His research appears to be conducted within the Institute for Computer Science at Goethe University Frankfurt, likely involving collaborations with other researchers in the Algorithms for Big Data priority program. The extensive list of co-authored publications suggests active participation in research teams focused on parallel algorithms, graph processing, and network generation.

Steffen BondorfView profile

Professor

• Network Calculus
• Deterministic Networking
• Performance Modeling
• +4 more

Steffen Bondorf is a Professor of Distributed and Networked Systems in the Faculty of Computer Science at Ruhr University Bochum, Germany. His research focuses on performance modeling and analysis of deterministic networking, particularly using network calculus to provide rigorous performance guarantees for networked systems. Dr. Bondorf received his B.Sc., M.Sc., and Dr.-Ing. (Ph.D.) in Computer Science from TU Kaiserslautern (TUK), where he was part of the distributed computer systems lab. He was the first student to enroll in a B.Sc. program at TUK before finishing secondary education. After graduation, he held positions as postdoctoral researcher, lecturer and Carl-Zeiss Fellow at TUK, research fellow at the National University of Singapore, and visiting researcher at the University of Toronto. From fall 2018 to fall 2019, he was funded by an ERCIM Alain-Bensoussan fellowship at NTNU Trondheim, Norway, and spent time at INRIA Paris. His research interests include network calculus, deterministic networking, performance modeling, computer networks, distributed systems, and P2P overlays. Dr. Bondorf's work has significantly advanced the field of network calculus, particularly in developing methods for analyzing FIFO feedforward networks, multicast flows, and P2P overlay structures. His recent research has integrated machine learning techniques with network calculus to improve analysis accuracy and efficiency, creating hybrid approaches that leverage the strengths of both methodologies. Dr. Bondorf was appointed as assistant professor at Ruhr University Bochum on October 1, 2019, becoming the university's first hire in the joint tenure-track program for the promotion of young scientists. Since December 1, 2021, he has been a tenured full professor at RUB. Carl-Zeiss Fellow ERCIM Alain-Bensoussan fellowship At RUB, Dr. Bondorf teaches Advanced Topics in Networking, Distributed Systems, Deterministic Network Calculus, and Seminar Distributed and Networked Systems. His research group develops tools and methodologies for deterministic network analysis with applications in industrial networking, real-time systems, and time-sensitive communications. His work bridges theoretical networking principles with practical implementations, contributing to the advancement of deterministic networking standards and protocols.

Manuel PenschuckView profile

Research Fellow

• Algorithm Engineering
• Random Graphs
• Parallel and Distributed Computing
• +3 more

Manuel Penschuck is a Research Fellow at the Institute of Computer Science , Goethe University Frankfurt, Germany. His research focuses on algorithm engineering, graph theory, and scalable network generation, with emphasis on parallel computing, I/O-efficient algorithms, and random graph models. He actively contributes to conferences like ESA, SEA, and IPDPS, and has co-authored publications in top venues including LIPIcs , IEEE Transactions , and SIAM . His work includes engineering algorithms for non-linear preferential attachment , parallel shuffling , and hyperbolic graph generation . He has co-organized program committees for ESA, EuroPar, and SEA, and his collaborations span institutions such as MPI-INF, TU Darmstadt, and Australian National University. Recent publications highlight advances in uniform graph sampling, geometric network models, and distributed systems. His research integrates theoretical rigor with practical implementation, addressing challenges in big data and high-performance computing. He is a key contributor to the Networkit toolkit for large-scale network analysis.

Artur CzumajView profile

Professor

• Theoretical Computer Science
• Randomized Algorithms
• Parallel and Distributed Computing
• +4 more

Artur Czumaj is a Professor of Computer Science and Director of the Center for Discrete Mathematics and its Applications (DIMAP) at the University of Warwick, United Kingdom. He is a member of the Global Faculty at the University of Cologne and serves as President of the European Association for Theoretical Computer Science (EATCS). PhD and Habilitation from University of Paderborn Recipient of the IBM Award and Fellow of EATCS His research focuses on theoretical computer science, particularly in the design of randomized algorithms, analysis of large data, and applications to parallel/distributed computing, property testing, sublinear algorithms, optimization algorithms, and algorithmic game theory. His work has been funded by major institutions including EPSRC, NSF, Royal Society, European Union, Simons Foundation, and IBM. The 15 most recent publications reflect expertise in graph algorithms, distributed systems, approximation techniques, and algorithmic complexity. His research spans foundational algorithm design to practical applications in large-scale data processing. Fellow of the European Association for Theoretical Computer Science (EATCS) IBM Award recipient Czumaj has held leadership roles in prominent conferences, including Program Committee Chair for STOC, ICALP, SODA, and HALG. His academic career is supported by grants from multiple international research councils and organizations.

V. ArvindView profile

Professor

• Computational Complexity Theory
• Structural Complexity
• Randomized Computation
• +5 more

V. Arvind is a Professor in the Theoretical Computer Science faculty at the Institute of Mathematical Sciences (IMSc) , Chennai. His research is centered on computational complexity theory, with a focus on structural complexity, randomized and algebraic computation, and quantum information and computation. He explores the deep connections between theoretical computer science and mathematics. Institution: Institute of Mathematical Sciences (IMSc), Chennai School: Theoretical Computer Science Academic Rank: Professor Arvind's research interests include computational complexity, structural complexity theory, algebraic computation, derandomization, and quantum computing. He is particularly interested in the interplay between mathematical structures and computation. His work often bridges theoretical computer science with algebra, combinatorics, and logic. His recent publications, primarily expository articles in the EATCS Bulletin’s Computational Complexity Column, cover a wide range of topics such as robust oracle machines, the Alon-Roichman theorem, noncommutative arithmetic circuits, graph isomorphism, and quantum computation. These works reflect trends in foundational complexity theory, algebraic methods in computation, and the exploration of quantum models. The articles emphasize structural insights, lower bounds, and connections to mathematical disciplines. Professional Service and Editorial Roles: Associate Editor, ACM Transactions on Computation Theory Editor, EATCS Computational Complexity Column (since June 2011) Editorial Board Member, International Journal of Computer Mathematics (2009–2013) Co-organizer, ICM Satellite Conference on Algebraic and Probabilistic Aspects of Combinatorics and Computing Program Committee Member for WALCOM 2014, STACS 2012, COCOON 2009, FSTTCS (multiple years, including chair roles), CCC 2006, INDOCRYPT (2002, 2005), and others Teaching: Arvind has taught advanced courses including Computational Complexity, Algorithms, Algebra and Computation, and Discrete Mathematics, often based on foundational texts and notes from leading experts. Lecture notes from his courses have been compiled by students and collaborators. Collaborations: He has an extensive list of co-authors, including prominent researchers such as Manindra Agrawal, Eric Allender, Johannes Köbler, Meena Mahajan, Jacobo Torán, and Ramprasad Saptharishi, indicating strong collaborative research networks in complexity theory and algorithms.

• Theoretical Computer Science
• Property Testing
• Approximation Algorithms
• +8 more

Yuichi Yoshida is a Professor at the National Institute of Informatics (NII), affiliated with the Principles of Informatics Research Division. He also holds a concurrent position as Senior Researcher at Preferred Networks. His academic career at NII spans from Assistant Professor (2012–2015), Associate Professor (2015–2022), to full Professor since 2022. He serves as Vice Director of the Global Research Center for Big Data Mathematics at NII and has held advisory and research roles at Preferred Infrastructure and the Ministry of Education, Culture, Sports, Science and Technology (MEXT). Ph.D. in Informatics, Kyoto University, 2012 Master of Informatics, Kyoto University, 2009 Bachelor of Engineering, Kyoto University, 2007 His research focuses on theoretical computer science, particularly property testing , approximation algorithms , sublinear-time algorithms , and constraint satisfaction problems . He investigates how theoretical insights can be applied to real-world graphs, with recent emphasis on average sensitivity of algorithms and Lipschitz continuity in combinatorial optimization . His work bridges theory and practical scalability in large network analysis and machine learning. The most recent 15 publications (2022–2025) demonstrate a strong trend in algorithmic stability, spectral methods for hypergraphs, influence propagation in networks, and learning-augmented algorithms. Key venues include FOCS, SODA, ICALP, and NeurIPS, reflecting high impact in theoretical computer science and machine learning. Topics such as Lipschitz continuity, average sensitivity, spectral sparsification, and sublinear algorithms recur, indicating a cohesive research program on robust and efficient computation. Best Paper Award, AISTATS (2018) MEXT Commendation for Science and Technology – Young Scientists’ Prize (2017) Inoue Research Award for Young Scientists (2014) KDDI Foundation Award (2024) Funai Information Technology Award (2024) Yuichi Yoshida advises PhD students and hosts numerous postdocs, RAs, and international interns. He leads major research projects funded by JSPS and JST, including Grants-in-Aid for Scientific Research (S) and PRESTO programs. His service includes program committee roles for ICML, NeurIPS, SODA, and ICALP. He has co-authored a book on Property Testing and contributed to encyclopedias on big data technologies. He leads research teams on algorithm desensitization and large-scale graph algorithms, and has been program co-chair for GRADES-NDA'23. His lab fosters international collaboration, hosting interns from top universities worldwide.

Karl BringmannView profile

Professor

• Theoretical Computer Science
• Fine-Grained Complexity
• Algorithm Design
• +5 more

Karl Bringmann is a Professor at Saarland University since November 2019 and is affiliated with the Max Planck Institute for Informatics, where he works in the Department of Algorithms and Complexity. He has established himself as a leading researcher in theoretical computer science, particularly in fine-grained complexity and algorithm design. His work bridges theoretical insights with practical applications in optimization problems. Bringmann's research focuses on conditional lower bounds (often based on the Strong Exponential Time Hypothesis) and algorithm design, with particular emphasis on optimization problems, string algorithms, and computational geometry. His work has significant implications for fundamental problems like Subset Sum, Knapsack, and Integer Programming, with applications ranging from scheduling to post-quantum cryptography. He develops innovative approaches combining modern algorithmic techniques, mathematical structure theory, and fine-grained complexity to design faster algorithms and establish optimality. His publication record shows a consistent trend toward developing near-optimal algorithms for fundamental problems, with significant contributions to fine-grained complexity theory. His work often establishes tight conditional lower bounds while simultaneously providing matching upper bounds, creating a comprehensive understanding of problem complexity. He has made notable advances in string algorithms (particularly edit distance), geometric problems, and optimization. ERC Starting Grant 2019: Technology Transfer between Integer Programming and Efficient Algorithms (TIPEA) EATCS Presburger Award for Young Scientists 2019 Heinz Maier-Leibnitz-Prize 2019 EATCS Distinguished Dissertation Award 2015 Google European Doctoral Fellowship 2012-2014 Bringmann leads the ERC-funded TIPEA project (2019-2024), which investigates fundamental optimization problems with the goal of developing next-generation industrial solvers. He advises several PhD students including Nick Fischer, Alejandro Cassis, and Vasileios Nakos, and has served on numerous program committees for top theoretical computer science conferences including STOC, FOCS, SODA, and ICALP. His teaching includes advanced courses on Fine-Grained Complexity Theory and Competitive Programming.

• Fast graph algorithms
• Dynamic algorithms
• Robust algorithms against adaptive adversaries
• +8 more

Thatchaphol Saranurak is an Assistant Professor in the Computer Science and Engineering Division at the University of Michigan, College of Engineering. He holds a Ph.D. in Computer Science from KTH Royal Institute of Technology (2018), advised by Danupon Nanongkai, and was previously a Research Assistant Professor at the Toyota Technological Institute at Chicago (2018–2020). His research lies at the intersection of theoretical computer science and algorithm design, with primary interests in fast graph algorithms , dynamic algorithms , robust algorithms against adaptive adversaries , and combinatorial optimization . His work has significantly advanced the state-of-the-art in areas such as maximum flow (Gomory-Hu trees), vertex and edge connectivity, dynamic matching, expander decompositions, and distributed graph algorithms. His recent publications (2023–2025) reveal a strong trend toward deterministic, near-linear time algorithms for fundamental graph problems, often leveraging expander hierarchies and dynamic sparsification techniques . He has made breakthroughs in dynamic matching, connectivity oracles, and multi-commodity flow, frequently publishing in top venues like FOCS, STOC, and SODA. He has received several prestigious honors, including: Presburger Award 2023 NSF CAREER Award Sloan Research Fellowship His advising and grant activities are supported by major funding such as the NSF CAREER Award and Sloan Fellowship, and he actively mentors and collaborates with a large network of co-authors. He is also involved in organizing academic events, such as the Dagstuhl Seminar on Graph Algorithms. He teaches courses such as Expander and Graph Algorithms and maintains an active research group focused on pushing the boundaries of algorithmic efficiency and robustness.

Shay SolomonView profile

Associate Professor

• Design and analysis of algorithms
• Graph compression problems
• Dynamic graph algorithms
• +4 more

Shay Solomon is an Associate Professor in the School of Electrical & Computer Engineering at Tel Aviv University. His research focuses on theoretical computer science, particularly in the design and analysis of algorithms for graph problems, distributed systems, and computational geometry. He coordinates the EE-Systems Department Colloquium and has received funding from prestigious organizations including the European Research Council (ERC), the Israel Science Foundation (ISF), and the US-Israel Binational Science Foundation (NSF-BSF). Professor Solomon's research interests span several key areas in theoretical computer science. He has made significant contributions to dynamic graph algorithms, developing novel techniques for problems like set cover and graph coloring. His work on Euclidean spanners and metric embeddings has advanced our understanding of geometric data structures. In distributed computing, he has explored locality-sensitive approaches to network representation. His research on sublinear algorithms addresses fundamental questions about what can be computed efficiently with limited resources. Across all these areas, his work is characterized by mathematical rigor and practical significance for algorithm design. Analysis of Professor Solomon's recent publications (2023-2025) reveals a strong focus on advancing the state-of-the-art in graph algorithms. His work frequently appears in top theoretical computer science venues including STOC, FOCS, and SODA. A notable trend is his exploration of dynamic algorithms that can efficiently update solutions as input changes, with applications to set cover and graph coloring problems. He has also made significant contributions to the theory of graph spanners in Euclidean and metric spaces, establishing new bounds and constructions. His collaborative work with researchers like Hung Le and Sayan Bhattacharya demonstrates the interdisciplinary nature of modern theoretical computer science research. Professor Solomon acknowledges support from several prestigious funding sources: European Research Council (ERC) Israel Science Foundation (ISF) US-Israel Binational Science Foundation (NSF-BSF) As the coordinator of the EE-Systems Department Colloquium, Professor Solomon plays an active role in academic community building at Tel Aviv University. While specific information about his advisees isn't provided in the source material, his research group likely includes graduate students working on theoretical computer science problems. His extensive publication record suggests an active research program with numerous collaborations across the global theoretical computer science community.

Axel MunkView profile

Professor

• Mathematical Statistics
• Biosciences
• Biophysics
• +10 more

Prof. Axel Munk is a University Professor at the Institute for Mathematical Stochastics , Georg-August-University of Goettingen, and serves as the director of the Felix Bernstein Institute for Mathematical Statistics in the Life Sciences (FBMS) within the Faculty of Mathematics and Computer Science. His work bridges mathematical statistics with biosciences and biophysics, focusing on advanced statistical methodologies for complex data analysis. Research Interests: Shape analysis, stochastic models in biology, ion channel dynamics, optimal transport theory, and super-resolution microscopy. Awards: Institute of Mathematical Statistics (IMS) Fellow (2016). Collaborations: Involved in DFG Collaborative Research Centers (e.g., SFB 755, SFB 860) and Priority Programs (e.g., SPP 1590). Software Contributions: Developed packages like stepR , J-SMURF , and icmcstat for ion channel analysis and multiscale methods.

• Theoretical Computer Science
• Algorithms for Big Data
• Streaming Algorithms
• +7 more

Krzysztof Onak is the Shibulal Family Career Development Assistant Professor in the Faculty of Computing & Data Sciences at Boston University. He is actively engaged in research and teaching, with a focus on theoretical foundations of algorithms for big data and their applications in AI and machine learning. PhD, Massachusetts Institute of Technology (2010) Researcher, IBM T.J. Watson Research Center Simons Postdoctoral Fellow, Carnegie Mellon University His research interests include theoretical computer science , streaming algorithms , sublinear-time algorithms , and parallel and distributed computing models . He works on algorithmic techniques for taming big data, such as sampling, sketching, and dimensionality reduction, with applications in machine learning and artificial intelligence. His work bridges theory and practice, addressing challenges in modern data processing frameworks like MapReduce. The most recent publications highlight a strong focus on efficient graph algorithms in distributed and streaming settings, dynamic data structures , and fairness in machine learning . His work frequently appears in top-tier venues such as STOC, FOCS, SODA, and ICML, demonstrating both theoretical depth and practical relevance. Scientific awards and recognitions include: ACM ICPC World Champion Gold Medalist, International Olympiad in Informatics Krzysztof Onak advises several PhD students and postdoctoral researchers, including Esty Kelman, Dragos Ristache, Themistoklis Haris, and Zi Song Yeoh. He has secured research funding through academic appointments and fellowships, and he is actively involved in the theoretical computer science community as a program committee member and workshop organizer. He has taught courses such as Algorithmic Techniques for Taming Big Data and Algorithms for Data Science . He is involved in organizing key academic events, including the Workshop on Emerging Models of Colossal Computation (E=mc²), the Workshop on Local Algorithms (WOLA 2022), and the Simons Semesters on Algorithms for the Massive Parallel Computation Model. He also contributes to the community through SUBLINEAR.INFO, a curated list of open problems in sublinear algorithms.

• Sublinear-Time Algorithms
• Property Testing
• Graph Algorithms
• +6 more

Talya Eden is an Assistant Professor in the Department of Computer Science at Bar Ilan University. She previously held a postdoctoral position at the Foundations of Data Science Institute (FODSI), jointly affiliated with MIT and Boston University, hosted by Prof. Ronitt Rubinfeld, Prof. Piotr Indyk, and Prof. Sofya Raskhodnikova. She earned her PhD from the School of Electrical Engineering at Tel Aviv University under the supervision of Prof. Dana Ron. Her research focuses on sublinear-time algorithms and property testing , with a strong emphasis on approximating graph parameters efficiently. Her work lies at the intersection of theoretical computer science, graph algorithms, and data science, addressing fundamental problems in large-scale graph analysis. Her recent publications, appearing in top venues such as STOC, FOCS, SODA, and ICALP, demonstrate consistent contributions to the fields of graph sampling, counting, streaming algorithms, and learning-augmented computation. Key themes include k-clique and triangle estimation , arboricity-based complexity , and robustness in streaming models . She has collaborated extensively with leading researchers including Dana Ron, Ronitt Rubinfeld, Piotr Indyk, and C. Seshadhri. Her work often explores the theoretical limits of what can be computed efficiently on massive graphs with limited access. Notable Scientific Contributions: Developed nearly optimal algorithms for sampling k-cliques in sublinear time. Established tight connections between arboricity and the complexity of edge sampling and degree moment estimation. Contributed to adversarially robust streaming algorithms using dense-sparse trade-offs. Explored learning-based approaches to enhance sublinear-time support estimation. Talya Eden advises students and is actively involved in the theoretical computer science research community. She has not received any explicitly mentioned scientific awards in the provided text, but her publication record in elite conferences indicates high recognition.

Soheil BehnezhadView profile

Assistant Professor

• Theoretical Computer Science
• Algorithms for Big Data
• Sublinear Time Algorithms
• +7 more

Soheil Behnezhad is an Assistant Professor in the Department of Computer Science at Khoury College of Computer Sciences, Northeastern University. He previously served as a Motwani Postdoctoral Fellow at Stanford University and received his PhD from the University of Maryland (UMD) and BSc from Sharif University. Research Interests: His work centers on theoretical computer science, particularly the design and analysis of algorithms for large-scale data. Key areas include sublinear-time algorithms, dynamic algorithms, streaming algorithms, parallel computation (MPC), and graph sparsification, with a strong emphasis on matching, coloring, and clustering problems. Recent Trends in Publications: His recent publications (2023–2025) highlight groundbreaking work in dynamic and sublinear algorithms. He has made significant advances in maximum matching, edge coloring, and correlation clustering, often providing tight bounds or breaking longstanding approximation barriers. His work connects theoretical models with combinatorial structures such as Ruzsa-Szemerédi graphs and explores practical implications in massive data settings. Scientific Awards: NSF CAREER Award Google Research Award Best Paper Award at STOC'25 Best Paper Award at SODA'23 Charles A. Caramello Distinguished Dissertation Award Larry S. Davis Doctoral Dissertation Award Multiple invitations to TALG and HALG Advising and Grants: He advises multiple PhD students including Amir Azarmehr, Mohammad Saneian, and Alma Ghafari. His research is supported by an NSF CAREER Award and a Google Research Award, reflecting both federal and industry recognition of his impactful work. Labs and Teams: He co-organizes the Graph Simplification reading group with Ronitt Rubinfeld and Madhu Sudan and is a key member of the Theory Group at Northeastern University, fostering a collaborative environment for theoretical research.

Tomasz KociumakaView profile

Professor

• String Algorithms
• Pattern Matching
• Edit Distance
• +5 more

Tomasz Kociumaka is a Professor and Group Leader in the Algorithms and Complexity Department at the Max Planck Institute for Informatics in Saarbrücken, Germany. He previously served as a Research Scientist at INSAIT in Sofia, Bulgaria (2024-2025), and as a Postdoctoral Researcher at the Max Planck Institute for Informatics (2022-2024). His academic journey includes postdoctoral positions at the University of California, Berkeley (2020-2022) and Bar-Ilan University, Israel (2019-2020). Dr. Kociumaka received his PhD in Computer Science from the University of Warsaw in 2019, with a thesis titled Efficient Data Structures for Internal Queries in Texts under the supervision of Professor Wojciech Rytter. He also completed both his BSc and MSc in Computer Science at the University of Warsaw between 2009 and 2014. His research focuses on string algorithms , particularly sequence similarity measures , approximate pattern matching , lossless data compression , and text indexing data structures . He approaches string problems from multiple perspectives including fine-grained complexity, dynamic algorithms, streaming, sketching, sublinear algorithms, and quantum computing. His work bridges theoretical computer science with practical applications in text processing and bioinformatics. Analysis of his recent publications reveals a strong emphasis on edit distance algorithms, pattern matching techniques, and data compression methods. His work demonstrates increasing sophistication in handling complex string problems with optimal time and space complexity, with growing interest in quantum computing applications for string processing. Presburger Award (2025) Cor Baayen Award (2021) Witold Lipski Prize (2018) Dr. Kociumaka serves on program committees for major theoretical computer science conferences including STOC, FOCS, SODA, and ICALP. He is also on the editorial board of Information Processing Letters and served as a guest editor for a special issue of SIAM Journal on Computing related to STOC 2024. His professional activities demonstrate significant leadership in the theoretical computer science community, particularly in the subfield of string algorithms and combinatorial pattern matching.

• Analysis of Algorithms
• Data Analysis
• Massive Data Sets
• +15 more

Robert Krauthgamer is the Harry Weinrebe Professor of Computer Science and currently serves as Department Head in the Department of Computer Science & Applied Mathematics at the Weizmann Institute of Science , within the Faculty of Mathematics and Computer Science . He is a leading researcher in theoretical computer science, particularly in the analysis of algorithms. Research Interests: His research focuses on Analysis of Algorithms , with deep expertise in Data Analysis and Massive Data Sets , Combinatorial Optimization , Approximation Algorithms , Hardness of Approximation , Embeddings of Finite Metrics , and Routing and Peer to Peer Networks . He also maintains a broad interest in Discrete Mathematics and High-Dimensional Geometry . His recent publications highlight work in graph algorithms, parameterized complexity, streaming algorithms, and metric embeddings. Publication Trends: His most recent work, including papers from SODA 2016, demonstrates a strong trend in the design and analysis of efficient algorithms for fundamental problems in graph theory, optimization, and data streams. Key themes include kernelization and sampling techniques for dynamic graph streams, subexponential parameterized algorithms, deterministic derandomization of the polynomial method, and structural results for graph modification problems. His research often bridges theoretical insights with applications in computational biology and network science. Service and Recognition: Journal Editorial: Editor-in-Chief of SIAM Journal on Computing (2019–2025), Associate Editor (2012–2017); Managing Editor of Theory of Computing (2007–2018), and current Editorial Board Member. Conference Leadership: Program Committee Chair for SODA 2016 and HALG 2018; Steering Committee member for SODA, ESA, and HALG; and committee member for the Gödel Prize (2019–2021). Workshops: Organizer of numerous workshops on sublinear algorithms, fine-grained complexity, and high-dimensional data. Teaching and Mentorship: He regularly teaches advanced courses such as Randomized Algorithms and Sublinear Time and Space Algorithms . He advises a large group of MSc and PhD students and hosts postdoctoral researchers, demonstrating a strong commitment to training the next generation of computer scientists. His former students have gone on to successful academic and research careers. Laboratories and Research Groups: He is a key member of the Foundations of Computer Science (theory) seminar at Weizmann and has organized the TheoryLunch and Reading Group in Algorithms, fostering a vibrant research community within the department.