Jan Dreier is a Research Fellow at the Institute of Logic and Computation at Vienna University of Technology. His research centers on structural graph theory and algorithmic meta-theorems, particularly exploring the boundaries of tractability for model checking problems. Dreier's work bridges theoretical computer science and discrete mathematics, focusing on graph decompositions, parameterized complexity, and logical expressiveness. Key research themes include monadic stability in graph classes, applications of model theory to computer science, and efficient algorithms for logical queries on structured graphs. His publication record shows consistent focus on graph sparsity concepts and algorithmic applications of logic, with recent work expanding into approximation methods for counting queries. Research demonstrates sophisticated applications of combinatorial methods to fundamental problems in computational complexity.
Asaf Ferber is Associate Professor in Mathematics at University of California, Irvine, School of Physical Sciences. His research spans discrete mathematics including combinatorial games, random graphs, extremal hypergraph theory, and quantum computation. Research explores Hamiltonian cycles in random graphs, structural properties of pseudorandom graphs, and quantum algorithms for combinatorial problems. Recent work develops quantum approaches to graph learning and sparse recovery in random matrices. Awards: NSF CAREER Award Sloan Fellowship Distinguished Early Career Faculty Award for Research Air Force Research Grant NSF-BSF Grant Organizes conferences including SoCalDM Symposium and Desert Discrete Math Workshop, mentoring graduate students through UCI's Probability and Combinatorics Seminar.
Thatchaphol Saranurak is an Assistant Professor at the University of Michigan , specifically in the Computer Science and Engineering Division . Prior to this, he earned his PhD in Computer Science from KTH Royal Institute of Technology in 2018 under Danupon Nanongkai , followed by a postdoctoral research assistant professorship at Toyota Technological Institute at Chicago (2018-2020). Research Focus : His work bridges fundamental problems in graph theory, including Dynamic graph algorithms for max-flow and min-cut Expander graph decompositions and their applications Robust algorithms against adaptive adversaries Continuous optimization for combinatorial problems Scientific Contributions : He has made breakthroughs in deterministic graph algorithms, notably improving vertex connectivity bounds, developing near-linear time Gomory-Hu trees, and advancing dynamic matching algorithms. His research has been recognized by Sloan Research Fellowship NSF CAREER Award Presburger Award 2023 Teaching : He teaches courses like Expander and Graph Algorithms and Introduction to Algorithms (Winter 23, Winter 25). His lecture videos and notes are publicly available. Collaborations : He works with leading researchers including Sayan Bhattacharya , Joakim Blikstad , and Jason Li , with affiliations to institutions like TTIC , KTH , and SODA conferences.
Giorgis Petridis is an Associate Professor at the University of Georgia, specializing in arithmetic combinatorics, a field rooted in combinatorial number theory with modern extensions into discrete analysis and finite field geometry. Born in Athens, Greece, he earned his PhD from the University of Cambridge under Tim Gowers and held a Visiting Assistant Professor position at the University of Rochester. He serves as an editor for Combinatorial Theory and is affiliated with the Number Theory and Arithmetic Geometry group, particularly its additive combinatorics and discrete analysis subgroup. Doctor of Philosophy (2011), University of Cambridge Certificate of Advanced Studies in Mathematics (2002), St John’s College, Cambridge BA (Hons) in Mathematics (2001), St John’s College, Cambridge His research focuses on additive combinatorics, exploring sumset estimates, polynomial configurations in prime lattices, and geometric incidence problems over finite fields. He investigates combinatorial geometry, including pinned distance problems and bisector arrangements, while also contributing to exponential sum bounds and expander graph theory. His work bridges theoretical mathematics with applications in pseudorandomness and discrete geometry. Recent publications highlight trends in finite field analysis, with 6 of 15 articles addressing arithmetic structures in prime-order fields. Key keywords include Combinatorics , Number Theory , and Finite Fields , with sub-fields spanning polynomial configurations, energy bounds, and geometric combinatorics. Scientific awards include the Creative Research Medal (2024) from the University of Georgia for mid-career research impact. Grants from the Simons Foundation (MPS-TSM-00007816) and multiple NSF DMS Awards (2054214, 1723016, 1500984, 1804049) support his work on discrete analysis and conferences. He co-advises five PhD students and has supervised multiple Master’s theses on topics like point-plane incidences and additive energy. Outreach includes leading high school math teams, organizing discrete analysis sessions, and contributing to public science communication guides.
Elette Boyle is an Associate Professor at Reichman University (IDC Herzliya) and a Senior Scientist at NTT Research . She holds a Ph.D. in Mathematics from MIT (advised by Shafi Goldwasser and Yael Tauman Kalai) and an undergraduate degree from Caltech . Education Ph.D. in Mathematics, MIT B.S. in Mathematics, Caltech Her research focuses on cryptographic solutions for secure data processing , particularly in secure multi-party computation , function/homomorphic secret sharing , and distributed point functions . Recent work explores topology-hiding communication , memory checking complexity , and sublinear-communication MPC . Key trends in her publications include: Advancements in Function Secret Sharing for branching programs and sparse vectors. Efficient Secure Multi-Party Computation protocols with preprocessing. Information-theoretic and computational Topology-Hiding Broadcast schemes. Optimized Oblivious Transfer with constant computational overhead. Scientific Awards European Research Council (ERC) Award Israeli Science Foundation (ISF) Grant United States Air Force Office of Scientific Research (AFOSR) Grant Google Research Scholar Award International Association for Cryptologic Research (IACR) Recognition As Director of the Foundations & Applications of Cryptography (FACT) Research Center , she leads collaborative work with institutions like Technion Israel , Cornell University , and NTT Research . Her students include Pierre Meyer (Ph.D.) , Matan Hamilis (Ph.D.) , and D'or Banon (MSc.) .
Venkatesan Guruswami is a Chancellor's Professor in the Department of EECS and a Senior Scientist at the Simons Institute for the Theory of Computing at UC Berkeley . He also holds a Professor position in the Department of Mathematics . His academic journey began with a B.Tech in Computer Science from the Indian Institute of Technology, Madras (1997) , followed by a Ph.D. in Computer Science from the Massachusetts Institute of Technology (2001) . After a Miller Research Fellowship at UC Berkeley (2001–02), he held faculty roles at the University of Washington and Carnegie Mellon University before returning to UC Berkeley in January 2022. Education : B.Tech, IIT Madras (1997) Ph.D., MIT (2001) Professional Affiliations : Chancellor's Professor, UC Berkeley (EECS) Senior Scientist & Interim Director, Simons Institute Professor, UC Berkeley (Mathematics) Guruswami's research spans multiple domains within Theoretical Computer Science , focusing on Error-Correcting Codes , Approximation Algorithms , Randomness in Computing , Probabilistically Checkable Proofs , and Computational Complexity . His groundbreaking work in List Decoding has enabled codes with minimal redundancy for correcting worst-case errors, while recent advancements include Polar Codes , Deletion-Correcting Codes , and Constraint Satisfaction Problems . He has also contributed to Quantum Coding Theory , Locally Recoverable Codes , and Approximation Hardness in various computational contexts. His publications reflect a deep engagement with interdisciplinary topics. Key trends include: Quantum Information Theory : Quantum LDPC codes, transversal gates, and quantum storage. Algebraic Coding : Reed-Solomon codes, AG codes, and polynomial-based constructions. Computational Complexity : Hardness of approximation, CSPs, and parameterized intractability. Data Transmission : Polar codes, deletion channels, and feedback mechanisms. Algorithmic Techniques : Spectral methods, semirandom models, and Lasserre hierarchy applications. Guruswami has received numerous accolades, including the Simons Investigator Award , Presburger Award , Packard Fellowship , Sloan Research Fellowship , ACM Doctoral Dissertation Award , and the IEEE Information Theory Society Paper Award . He is an ACM Fellow (2017) and IEEE Fellow (2019) , with recent honors like the Guggenheim Fellowship (2023) and AMS Fellow (2023) . As an advisor, he has mentored over 25 PhD and postdoctoral researchers , including Atri Rudra , Prasad Raghavendra , and Peter Manohar , whose work has won awards like the Edmund M. Clarke Doctoral Dissertation Award and CRA Outstanding Undergraduate Researcher Award . His research is supported by grants from the National Science Foundation , Packard Foundation , and Sloan Foundation . He also serves as Editor-in-Chief of the Journal of the ACM and holds leadership roles in IEEE and arXiv moderation. Guruswami is actively involved in Simons Institute programs and co-organized workshops on Coded Computation and Information Theory . His work bridges theoretical advancements with practical applications in Cloud Storage , Quantum Computing , and Group Testing , including pandemic-era contributions like AC-DC: Amplification Curve Diagnostics for SARS-CoV-2 .
Avi Wigderson is the Herbert H. Maass Professor in the School of Mathematics at the Institute for Advanced Study, Princeton. He is a leading authority in theoretical computer science, particularly computational complexity theory. Wigderson organizes the Computer Science and Discrete Mathematics (CSDM) program at the Institute, fostering interdisciplinary research at the intersection of mathematics and computer science. Wigderson earned his Ph.D. (1983), M.A. (1982), and M.S.E. (1981) from Princeton University. Prior to his current position, he held appointments at The Hebrew University of Jerusalem (1986-2003), Princeton University (1990-1992), Mathematical Sciences Research Institute, Berkeley (1985-1986), IBM Research (1984-1985), and University of California, Berkeley (1983-1984). Wigderson's research spans computational complexity theory, randomness and computation, algorithms and optimization, circuit complexity, proof complexity, quantum computation and communication, and cryptography. His work explores fundamental questions like whether mathematical creativity can be automated (P vs NP problem), the security of electronic commerce, the role of randomness in computation, and the potential of quantum mechanics to enhance computation. He has made significant contributions to understanding the power and limitations of efficient computation. Analysis of Wigderson's recent publications reveals a strong focus on optimization, complexity theory, and their mathematical foundations. His work connects diverse areas including non-commutative algebra, geometric complexity, graph theory, and quantum computing. A recurring theme is exploring whether fundamental computational problems like P vs NP can be addressed through optimization techniques such as gradient descent. His research shows increasing interdisciplinary connections between theoretical computer science, mathematics, and physics. ACM A.M. Turing Award (2023) Abel Prize (2021) Donald E. Knuth Prize (2019) Gödel Prize (2009) American Mathematical Society's Levi L. Conant Prize (2008) Rolf Nevanlinna Prize (1994) Yoram Ben-Porat Presidential Prize for Outstanding Researcher (1994) Bergman Fellowship (1989) Member, American Academy of Arts and Sciences Member, National Academy of Sciences While specific details about Wigderson's students are not provided in the source material, his extensive lecture series, workshops, and program organization suggest significant mentorship activities. His book "Mathematics and Computation" published by Princeton University Press serves as an educational resource for students and researchers. Wigderson has organized major programs at the Institute for Advanced Study including "Lower Bounds in Computational Complexity" (2018) and "Pseudorandomness" (2017), creating research opportunities for numerous scholars. Wigderson leads the Computer Science and Discrete Mathematics (CSDM) program at the Institute for Advanced Study, which brings together researchers from mathematics and computer science to explore fundamental questions in computation. His work with collaborators across multiple institutions has established connections between theoretical computer science and diverse fields including quantum information theory, algebraic geometry, and optimization. Recent projects focus on non-commutative optimization and its applications to computational complexity problems.
Elaine Shi is a Professor with a joint appointment in the Computer Science Department (CSD) and Electrical and Computer Engineering (ECE) at Carnegie Mellon University. She is also an Adjunct Professor of Computer Science at the University of Maryland. Her research focuses on cryptography, security, mechanism design, algorithms, blockchains, and programming languages. She co-founded Oblivious Labs, Inc., and her work on Oblivious RAM and differential privacy has been adopted by Signal, Meta, and Google. Education: Not explicitly listed, but her academic roles imply advanced degrees in computer science. Research Interests: Shi's work spans foundational areas such as secure computation, privacy-preserving algorithms, and blockchain protocols. She emphasizes practical implementations, such as Oblivious RAM and cryptographic compilers like Viaduct. Her research also explores game-theoretic mechanisms for decentralized systems and explores the intersection of theory and practice in secure distributed systems. Publications: Over 150+ articles in top venues like Eurocrypt, S&P, and CCS, covering topics like oblivious algorithms, blockchain security, and differential privacy. Recent work includes optimizing obfuscation, secure aggregation, and transaction fee mechanisms. Packard Fellow, Sloan Fellow, ACM Fellow, IACR Fellow Co-founder of CMU's Crypto Group and Crypto Seminar Series Advising & Grants: Supervises a large group of students and postdocs, with notable alumni holding academic and industry roles. Active in securing grants for research in secure computation and blockchain technologies. Labs & Teams: Leads research in Oblivious Labs and collaborates on projects like the Viaduct compiler and secure enclaves for privacy-preserving computation.
Prof. Michael Krivelevich holds the Baumritter Chair in Combinatorics at the School of Mathematical Sciences, Tel Aviv University. His research focuses on probabilistic methods in combinatorics, random graphs, and positional games. He has authored influential books such as Positional Games and contributed to foundational work in random graph theory. Currently teaching Introduction to Combinatorics and Graph Theory (Spring 2025), he has extensive experience in courses like Graph Theory and Hypergraph Coloring. His work bridges theoretical computer science, coding theory, and combinatorics, with over 150 publications. Recent research explores game-theoretic thresholds, random graph evolution, and equitable coloring algorithms. Education: Ph.D. in Mathematics, Tel Aviv University (not explicitly stated, inferred from career trajectory). Research Interests Krivelevich's work emphasizes random structures , extremal graph theory , and probabilistic combinatorics . He investigates phase transitions in random graphs, positional game strategies, and algorithmic challenges in graph coloring. His contributions include proving sharp thresholds for Hamilton cycle games and analyzing WalkSAT performance on smoothed k-CNF formulas. Collaborations span theoretical computer science and discrete mathematics. Publications Recent articles address Hamiltonicity in Maker-Breaker games, equitable coloring of random graphs, and smoothed analysis of satisfiability processes. His work often combines rigorous proofs with algorithmic insights. Teaching & Mentorship Guides students through advanced combinatorial topics and has taught foundational courses since 2002. No explicit student listings available in provided texts.
Venkatesan Guruswami is a Chancellor's Professor in the Department of Electrical Engineering and Computer Sciences and Professor in the Department of Mathematics at the University of California, Berkeley. He previously served as faculty at Carnegie Mellon University for 13 years and held a Miller Research Fellowship at UC Berkeley. His research focuses on Theoretical Computer Science , particularly in Error-Correcting Codes , Approximation Algorithms , Quantum Computing , and Hardness of Approximation . Guruswami has made groundbreaking contributions to list decoding and quantum code constructions, with works featured in Science Magazine and the Journal of the ACM (where he serves as Editor-in-Chief). Education : B.Tech (1997, IIT Madras), Ph.D. (2001, MIT), Miller Research Fellowship (2001-02, UC Berkeley) Research Areas : Theory of error-correcting codes, approximation algorithms, pseudorandomness, probabilistically checkable proofs, and quantum coding theory Guruswami's recent work explores quantum LDPC codes , parameterized inapproximability , and stream decodable codes . He has received prestigious awards including the NSF CAREER award , David and Lucile Packard Fellowship , and Sloan Research Fellowship . His advising spans a wide range of students and postdocs, with notable contributions to coding theory and computational complexity .
Tibor Szabó is a Professor in the Combinatorics and Graph Theory group at the Department of Mathematics, Freie Universität Berlin. He holds a PhD from The Ohio State University, advised by Ákos Seress. Prior to his current position, he held roles at McGill University, ETH Zürich, the Institute for Advanced Study (Princeton), and the University of Illinois (UIUC) as a J.L. Doob Research Assistant Professor. Research Interests: His work focuses on combinatorics and combinatorial optimization, including extremal problems, random structures and algorithms, pseudorandom graphs, positional games, and the combinatorics of linear programming. He explores tools from algebra, probability theory, and topology applied to combinatorics. Teaching: He teaches courses such as Algorithmic Combinatorics, Extremal Combinatorics, and runs the Combinatorics Seminar. His lecture notes include works on positional games and explicit constructions in extremal combinatorics. Students & Postdocs: Notable PhD advisees include Yamaan Attwa, Silas Rathke, Simona Boyadzhiyska, and Patrick Morris. Postdoctoral fellows include Olaf Parczyk and Anurag Bishnoi. His research has involved collaborations with over 50 co-authors. Funding & Grants: Supported by grants from the Swiss National Science Foundation (SNF) and German Research Foundation (DFG), focusing on topics like positional games and extremal graph theory.
Li-Yang Tan is an Assistant Professor of Computer Science at Stanford University , focusing on theoretical computer science. His research emphasizes computational complexity, machine learning theory, and algorithm design. Education: Ph.D. in Computer Science from Columbia University , advised by Rocco Servedio His work explores: Boolean function complexity Decision tree learning algorithms Circuit lower bounds Computational-statistical tradeoffs Query complexity Massively parallel algorithms Recent publications analyze computational-statistical tradeoffs via NP-hardness, improve decision tree learning techniques, and establish direct sum theorems for query complexity. His research often bridges complexity theory, learning theory, and algorithm design, with applications in pseudorandomness and correlation clustering. Awards: Best Paper Award at FOCS Best Paper Award at CCC Best Paper Award at SAT Sloan Fellowship Li-Yang collaborates with students and researchers including Guy Blanc, Caleb Koch, and Carmen Strassle. He has delivered invited special issue papers at FOCS, CCC, and SAT conferences.
Valentine Kabanets is a Professor in the School of Computing Science at Simon Fraser University. He holds a Ph.D. in Computer Science from the University of Toronto (2000), M.Sc. from Simon Fraser University (1996), and B.Sc. from the National University of Kiev (1993). His research focuses on computational complexity theory, pseudorandomness, circuit lower bounds, and cryptography. He has received prestigious awards including the Nerode Prize (2013) and multiple best-paper awards at conferences like STOC and CCC. Teaching includes courses on computability and complexity (CMPT 308), data structures and algorithms (CMPT 307), and advanced complexity theory. His research explores foundational questions such as derandomization of algorithms, connections between upper/lower bounds in complexity, and cryptographic hardness assumptions. He leads the Algorithms and Complexity Theory Lab and has supervised numerous graduate students and postdocs. Kabanets' work bridges theoretical insights with practical algorithmic advancements, contributing to both foundational computer science and applied cryptography.
Professor Stefan Glock is an Assistant Professor of Discrete Mathematics at the University of Passau's Faculty of Computer Science and Mathematics, a position he has held since September 2022. Prior to this appointment, he spent three years as a Junior Fellow at the Institute for Theoretical Studies at ETH Zurich, following the completion of his doctorate at the University of Birmingham. Stefan Glock received his mathematics education at Technische Universität Ilmenau from 2009 to 2014, then pursued his PhD at the University of Birmingham, which he completed in 2018. His doctoral dissertation, "Decompositions of Graphs and Hypergraphs," was the runner-up for the Richard-Rado-Preis 2018. Professor Glock's research focuses on discrete mathematical structures, with particular emphasis on their asymptotic properties. His work spans several interconnected fields of combinatorics: Extremal Combinatorics : Investigating the maximum or minimum possible size of mathematical structures satisfying certain properties Probabilistic Combinatorics : Applying probability theory to solve combinatorial problems Graph Theory : Studying properties of graphs and networks Ramsey Theory : Examining conditions under which order must appear in large structures Design Theory : Creating arrangements of elements satisfying specific balance properties Discrete Geometry : Analyzing geometric problems with discrete structures Analysis of Professor Glock's recent publications reveals a consistent focus on solving long-standing open problems in combinatorics using innovative methods that combine probabilistic techniques with structural insights. His work often bridges theoretical mathematics with applications in theoretical computer science, particularly in the analysis of algorithms and network structures. A significant portion of his research addresses fundamental questions about graph and hypergraph decompositions, which have implications for coding theory, cryptography, and network design. Professor Glock has received notable recognition for his contributions to mathematics: Runner-up for the Richard-Rado-Preis 2018 for his dissertation "Decompositions of Graphs and Hypergraphs" Awarded funding through the prestigious DFG Emmy Noether Programme in 2024 for his research group on "the interplay of structure and randomness in mathematics" As a faculty member at the University of Passau, Professor Glock leads the Discrete Mathematics research group and actively collaborates with mathematicians worldwide. He has established a strong research program that has attracted funding for academic visitors and supports multiple research projects. His approach to mathematical problems emphasizes developing new methods that have far-reaching implications beyond the specific problems being solved. Professor Glock's research group at the University of Passau focuses on the interplay between structure and randomness in discrete mathematics. The group maintains active collaborations with leading institutions including ETH Zurich, University of Birmingham, and various research centers across Europe. Through the DFG Emmy Noether Programme funding, his group is expanding its research on combinatorial structures and their applications.
Shachar Lovett is a researcher at the University of California, San Diego (UCSD), specializing in computational complexity, combinatorics, and theoretical computer science. His work spans advanced topics in communication complexity, pseudorandomness, and coding theory, often intersecting with problems in additive combinatorics and Boolean function analysis. Education : Not explicitly detailed in the provided text. Research Interests : Lovett's research focuses on computational complexity, particularly in communication and circuit complexity, combinatorial structures like sunflowers and high-dimensional expanders, and the analysis of Boolean functions through Fourier and Gowers norms. His work explores the limits of deterministic vs. randomized computation, the structure of codes over finite fields, and the interplay between additive combinatorics and theoretical computer science. Article Trends : His recent publications address exact vs. approximate representations of Boolean functions, quasipolynomial bounds in combinatorics, hypercontractivity in high-dimensional expanders, and advancements in the log-rank conjecture. These works emphasize connections between computational complexity, discrete mathematics, and pseudorandomness, often yielding improved bounds or novel frameworks for understanding Boolean function behavior. Scientific Awards : No specific awards or honors were mentioned in the provided text. Advising and Collaborations : Lovett collaborates extensively with researchers like Hamed Hatami, Kaave Hosseini, and Jiapeng Zhang, contributing to fields such as non-malleable codes, matrix multiplication algorithms, and communication complexity. No formal student advising details were provided.
