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Euiwoong LeeView profile

Assistant Professor

• Approximation Algorithms
• Hardness of Approximation
• Discrete Optimization
• +3 more

Euiwoong Lee is an Assistant Professor in the Computer Science and Engineering Division at the University of Michigan. He holds a PhD from Carnegie Mellon University, advised by Venkatesan Guruswami, and has held postdoctoral positions at New York University and the Simons Institute for the Theory of Computing. His research focuses on approximation algorithms, hardness of approximation, and parameterized complexity. **Education:** PhD in Computer Science, Carnegie Mellon University (2017), advised by Venkatesan Guruswami Postdoctoral Fellowships: NYU (2017–2020), Simons Institute (2017–2020) **Research Interests:** Approximation Algorithms & Hardness of Approximation Convex Hierarchies (e.g., Sum-of-Squares) Clustering Algorithms (e.g., Correlation Clustering) Parameterized Complexity Facility Location & Metric Optimization **Awards:** Edmund M. Clarke Doctoral Dissertation Award (2017) Simons Award for Graduate Students in Theoretical Computer Science **Advising & Grants:** PhD Students: Anthony Della Pella, Aditya Anand, Amatya Sharma, Ian DeHaan Co-organizes the Michigan Theory Seminar **Labs/Teams:** Collaborates with researchers in approximation algorithms, optimization, and theoretical computer science at the University of Michigan and beyond.

Maria ChudnovskyView profile

Professor

• Graph Theory
• Applied Mathematics
• Combinatorics
• +3 more

Maria Chudnovsky is a Professor in the Department of Mathematics at Princeton University. Her research focuses on structural graph theory, particularly in areas such as graph decomposition, induced subgraphs, and algorithmic applications of graph structure. She is renowned for her contributions to understanding perfect graphs, even-hole-free graphs, and the Erdős–Hajnal conjecture. Her work often explores the interplay between graph structure and algorithmic efficiency, with applications in combinatorial optimization and theoretical computer science. Notable contributions include foundational results on tree decompositions, chromatic number bounds, and the structure of metrizable graphs. Recent research trends include investigations into induced subgraph obstructions, tree independence numbers, and the properties of sparse graphs. She has published extensively on topics such as clique-stable set separation, rainbow matchings, and the complexity of graph coloring problems in restricted graph classes. Chudnovsky has been involved in significant collaborative projects, including work funded by the DMS-EPSRC grant 'The Power of Graph Structure' (2021). Her research frequently bridges theoretical insights with practical algorithm design, contributing to both fundamental and applied areas of discrete mathematics.

Alexander ScottView profile

Professor

• Combinatorics
• Probability
• Algorithms
• +3 more

Professor Alexander Scott is a faculty member at the University of Oxford, holding positions as Professor of Mathematics and Dominic Welsh Tutor in Mathematics at Merton College. His research focuses on combinatorics, probability, algorithms, and graph theory, with a particular interest in the interplay between local and global structures in networks. He has organized the Oxford Combinatorics Seminar and co-founded the online Oxford Discrete Mathematics and Probability Seminar, fostering collaboration in these fields. Professor Scott’s work bridges theoretical foundations with applications in statistical physics and algorithmic design. He has supervised numerous graduate students in combinatorics and regularly teaches undergraduate courses in analysis and discrete mathematics. His contributions include advancements in extremal graph theory, probabilistic methods, and structural combinatorics, with over 150 publications in prestigious journals. He actively organizes academic events such as the annual One-Day Meeting in Combinatorics, hosting speakers from around the world. Despite the absence of explicit awards noted, his prolific research output and academic leadership reflect significant contributions to the field. His current interests continue to explore the Erdős-Hajnal conjecture, induced subgraph densities, and algorithmic challenges in combinatorial structures.

• Combinatorial Optimization
• Approximation Algorithms
• Stochastic Optimization
• +3 more

Viswanath Nagarajan is an Associate Professor of Industrial & Operations Engineering and Computer Science Engineering (courtesy) at the University of Michigan. His research focuses on combinatorial optimization, approximation algorithms, and stochastic models for routing, scheduling, and location problems. He previously served as an Assistant Professor at the University of Michigan (2014–2020) and a Research Staff Member at IBM T.J. Watson Research Center (2009–2014). He holds a Ph.D. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University (2004–2009) and a B.Tech. in Computer Science from IIT Bombay (1999–2003). His research explores uncertainty management in optimization, including stochastic models and approximation algorithms for decision-making under uncertainty. He has contributed to adaptive algorithms, submodular optimization, and applications in logistics, network design, and scheduling. Education: Ph.D., Algorithms, Combinatorics, and Optimization (Carnegie Mellon University, 2009) B.Tech., Computer Science and Engineering (IIT Bombay, 2003) Prof. Nagarajan has organized major conferences like IPCO 2019 and served on editorial boards for journals including Operations Research , ACM Computing Surveys , and ACM Transactions on Algorithms . His service includes program committees for SODA, APPROX, and IPCO. He advises Ph.D. students focusing on optimization theory and applications, with advisees securing positions at Yahoo! Research, the University of Chicago, Ford Motor Company, and Georgia Tech.

• Fast graph algorithms in different computation models
• Robust algorithms against adaptive adversaries
• Continuous optimization for combinatorial problems
• +3 more

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.

William GasarchView profile

Professor

• Complexity Theory
• Concrete Complexity Theory
• Combinatorics
• +3 more

William Gasarch is a Professor of Computer Science at the University of Maryland, College Park, with an affiliation in Mathematics. He holds a Ph.D. from Harvard University (1985) and a B.S. from SUNY Stony Brook (1980). His research focuses on complexity theory, combinatorics, and Ramsey Theory, with applications to computer science theory. Education: Ph.D., Harvard University, 1985 (Computer Science) B.S., SUNY Stony Brook, 1980 (Math and Applied Math) Research Interests: Gasarch specializes in theoretical computer science, particularly applying Ramsey Theory to computational problems. His work bridges combinatorics, logic, and algorithm design, emphasizing foundational questions in complexity theory. He is known for exploring how Ramsey Theory informs program termination proofs and lower bounds in computational models. Labs/Teams: Affiliated with the Computer Science department’s theory group, he contributes to collaborative projects on Ramsey applications and combinatorial algorithms. His REU (Research Experiences for Undergraduates) program highlights mentorship in combinatorial algorithms. Advising & Grants: Mentored numerous high school and undergraduate students, including Breakthrough Prize winner Jacob Lurie and Intel Science Talent finalist Louis Wasserman. Active in NSF-funded initiatives through UMD’s theory group (details unspecified).

Gene CoopermanView profile

Professor

• High-Performance Computing
• Computer Systems
• Transparent Checkpointing
• +4 more

Gene Cooperman is a Professor at the Khoury College of Computer Sciences at Northeastern University, with an affiliation in the College of Engineering. His research focuses on high-performance computing (HPC), transparent checkpoint-restart systems, and model checking. He leads the High Performance Computing Laboratory, where he explores checkpointing technologies like DMTCP, MANA for MPI, and CRAC for CUDA, aiming to enhance HPC workflows on supercomputers such as NERSC's Perlmutter. His work bridges distributed computing, parallel algorithms, and system software to address challenges in fault tolerance, scalability, and resource management. Cooperman has advised 10 PhD students and co-authored over 125 refereed publications, contributing to projects like Geant4-MultiThreaded and Roomy for disk-based computation. His teaching includes courses on computer systems and HPC seminars. Education: Background in computational algebra and parallel computing, transitioning to HPC systems and checkpointing. Research Themes: Transparent checkpointing, MPI agnostic solutions, CUDA integration, and HPC resource optimization. Recent articles emphasize MPI checkpointing, reversible debugging (FReD), and CUDA support, reflecting trends in distributed and GPU-accelerated systems. His grants include NSF, NERSC/DOE, and MemVerge funding. Cooperman collaborates with institutions like CERN and NERSC, advancing applications in particle physics simulations and supercomputing. Current students include Aayushi Gautam, Jiajun Cao, Rohan Garg, and Twinkle Jain.

Joachim RosenthalView profile

Professor

• Coding Theory
• Cryptography
• Algebraic Geometry
• +2 more

Joachim Rosenthal is a Professor of Applied Mathematics at the University of Zurich's Department of Mathematics, leading the Applied Algebra Group. His research integrates coding theory, cryptography, and algebraic geometry with applications in communications and security systems. His primary research explores algebraic coding theory including convolutional codes, subspace codes, and post-quantum cryptography. He develops algorithms for error correction, code optimization, and cryptographic protocol analysis, with emphasis on mathematical structures in finite fields and rings. Professor Rosenthal serves as President of the Swiss Mathematical Society (2024-2025) and sits on IEEE Information Theory Society's Board of Governors. He has organized multiple international conferences on coding theory and cryptography, including the Zurich COST Meeting and Workshop on Convolutional Codes. His editorial contributions include roles at Archiv der Mathematik and SIAM Journal on Applied Algebra and Geometry. Recent publications focus on code construction methods, complexity analysis in group-based cryptography, and algebraic approaches to error-correcting codes.

• Stochastic Processes
• Financial Mathematics
• Systemic Risk
• +6 more

Jean-Pierre Fouque is a Professor in the Department of Statistics and Applied Probability (PSTAT) at the University of California, Santa Barbara. His research focuses on stochastic processes, financial mathematics, systemic risk, and reinforcement learning, with a particular emphasis on mean field games and multi-scale stochastic models. He explores applications in portfolio optimization, risk management, and algorithmic finance. His work combines theoretical advancements in stochastic analysis with practical applications in economics and finance. Notable contributions include developing models for systemic risk in financial networks, analyzing reinforcement learning algorithms in mean-field frameworks, and studying stochastic volatility effects in derivatives pricing. Recent research trends include integrating deep learning techniques for systemic risk quantification, advancing multi-scale asymptotic methods for portfolio optimization, and investigating strategic interactions in financial systems using game-theoretic approaches. His publications frequently address topics such as stochastic volatility calibration, optimal investment strategies under uncertainty, and the dynamics of financial markets under stress scenarios. Dr. Fouque has contributed to foundational textbooks and edited volumes on systemic risk and mean field games. His interdisciplinary work bridges probability theory, mathematical finance, and computational methods, impacting both academic research and practical risk management practices.

Gerold AlsmeyerView profile

Professor

• Theory of stochastic processes
• Stochastic fixed-point equations
• Iterated function systems
• +7 more

Prof. Dr. Gerold Alsmeyer is a faculty member at the Institute of Mathematical Stochastics, Department of Mathematics and Computer Science, University of Münster. He is an active researcher with a focus on stochastic processes, particularly stochastic fixed-point equations and iterated function systems. His work is supported by his role as an Investigator in Mathematics Münster in the project EXC 2044 - C1: Evolution and asymptotics. His primary research interests include the theory of stochastic processes, branching processes, Markov random walks, renewal theory, and the asymptotic analysis of random structures such as random trees and polytopes. He has made significant contributions to the understanding of fluctuation theory, perpetuities, and the smoothing transform. His recent publications (2017–2023) reveal a sustained focus on theoretical probability, with recurring themes in random difference equations, iterated function systems, and limit theorems for stochastic processes. The work spans pure mathematical theory and applications in mathematical biology and combinatorics, indicating a broad yet deep research profile. Prof. Alsmeyer has supervised numerous doctoral and master’s students, including Viet Hung Hoang, Christopher Eick, Philipp Godland, and Fabian Buckmann, whose dissertations cover topics in branching processes, random walks, and stochastic fixed-point equations. He has no listed scientific awards in the provided texts. He teaches courses in probability theory, mathematical statistics, branching processes, and stochastic recursion equations, demonstrating a strong commitment to academic mentoring and education.

Clyde KruskalView profile

Associate Professor

• Parallel Computing
• Algorithms
• Computer Architecture
• +3 more

Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.

Nathan LinialView profile

Professor

• Combinatorics
• Theoretical Computer Science
• Bioinformatics
• +6 more

Nathan (Nati) Linial is a Professor at the School of Computer Science and Engineering at the Hebrew University of Jerusalem, where he has been a faculty member since completing his postdoctoral period at UCLA. He earned his undergraduate degree in mathematics from the Technion and his PhD in graph theory from the Hebrew University. His research spans multiple areas of theoretical computer science and mathematics, with primary focus on combinatorics, theoretical computer science, and bioinformatics. Linial's work has made significant contributions to high-dimensional combinatorics, expander graphs, metric embeddings, and computational molecular biology. His research often bridges geometry, analysis, and combinatorial structures, demonstrating deep connections between seemingly disparate mathematical fields. Linial's recent publications reveal a strong trend toward high-dimensional combinatorial structures, including simplicial complexes, hypertrees, and high-dimensional permutations. His work frequently employs probabilistic methods, linear programming techniques, and geometric approaches to solve fundamental combinatorial problems. The breadth of his research is evident in both pure mathematical contributions and applications to computational biology. Fellow of the American Mathematical Society ISI Highly Cited Researcher Conant Prize (2008) for the influential survey paper "Expander graphs and their applications" Linial has served on the editorial boards of several prestigious journals including the Israel Journal of Mathematics (as Chief Editor 2013-2017), Random Structures and Algorithms, and Combinatorica. His academic leadership extends to organizing conferences and workshops in combinatorics and theoretical computer science. He has mentored numerous students whose work spans theoretical computer science, combinatorics, and computational biology. Linial is associated with research projects including ProtoNet (for protein sequence classification) and EVEREST (for evolutionary conserved protein domains), demonstrating his commitment to interdisciplinary research that bridges computer science with molecular biology.

Steven N. EvansView profile

Professor

• Probability
• Mathematical Analysis
• Applied Mathematics
• +11 more

Steven N. Evans is a Distinguished Professor at the University of California, Berkeley , affiliated with the Department of Statistics and the Center for Computational Biology . With over three decades of service since 1987, his work bridges probability theory , stochastic processes , and their applications in mathematical biology , computational genetics , and phylogenetics . His research spans: Probability on Algebraic Structures , including random matrices and local fields. Measure-Valued Processes and coalescent models in population genetics. Phylogenetic Inference in historical linguistics and ecology. Stochastic Models for gene expression, fitness landscapes, and mutation-selection balance. Markov Processes and their applications in phylodynamics. Recent publications highlight his contributions to phylogenetic networks , Frechet mean sets , and Levy process analysis , with keywords spanning Probability , Computational Biology , and Population Genetics . He has mentored 10 PhD students, including Boyan Xu (2024) and Nicholas Bhattacharya (2022). His email is evans@stat.berkeley.edu .

• Algebra
• Geometry
• Topology
• +5 more

Jonas Bergström is a Professor in the Department of Mathematics at Stockholm University specializing in Algebra, Geometry, Topology, and Combinatorics. His research focuses on arithmetic geometry, moduli spaces, Siegel modular forms, and number theory, with extensive collaborations across international institutions including KTH Royal Institute of Technology. His research interests span algebraic geometry, topology, combinatorics, and number theory, with particular emphasis on moduli spaces of curves, abelian varieties, Siegel modular forms, and arithmetic geometry. Bergström's work bridges theoretical mathematics with computational approaches, often developing algorithms for complex mathematical structures. His research group actively explores commutative and homological algebra, complex and real algebraic geometry, arithmetic geometry, homotopy theory, and Ramsey theory. The most recent publications reveal a strong focus on cohomology of moduli spaces, Siegel modular forms, abelian varieties over finite fields, and L-functions. His work demonstrates a consistent pattern of combining algebraic geometry with number theory, particularly investigating arithmetic properties of algebraic varieties and developing computational methods for modular forms. The research shows increasing emphasis on algorithmic approaches and connections to theoretical physics through moduli space cohomology. Bergström has supervised several PhD students including Sjoerd de Vries (current), Stefano Marseglia, and Olof Bergvall (with Prof. Carel Faber). He currently mentors postdoctoral researchers Séverin Philip and Thomas Wennink, while former postdocs include Angelina Zheng, Valentijn Karemaker, Oliver Leigh, and Alex Samuel Bamunoba. His research is supported through collaborations with major mathematical networks including the Nordic number theory network and joint seminars with KTH. He is affiliated with the Algebra and Geometry Seminar (KTH and SU) and maintains active research connections through multiple collaborative projects, including joint work with Gerard van der Geer and Carel Faber on Hecke operators and Siegel modular forms. Bergström also contributes to open mathematical research through GitHub repositories containing computational results on cohomology of moduli spaces.

Noga AlonView profile

Professor

• Combinatorics
• Graph Theory
• Theoretical Computer Science
• +7 more

Noga Alon is a Professor at Princeton University (previously at Tel Aviv University since 1985), renowned for transformative contributions to Combinatorics and Theoretical Computer Science. His work bridges deep mathematical theory with computational applications, earning him the 2024 Wolf Prize and 2022 Shaw Prize in Mathematical Sciences. Education Ph.D. in Mathematics, Hebrew University of Jerusalem, Israel (1983) Research Interests Alon pioneers combinatorial methods with profound impacts across mathematics and computer science. His expertise spans Graph Theory, Combinatorial Algorithms (including Streaming Algorithms), Circuit Complexity, and Combinatorial Geometry/Number Theory. He innovatively applies Algebraic and Probabilistic Methods to solve fundamental problems, such as necklace splitting and signrank applications, driving advancements in both pure and applied domains. Scientific Awards 1989 Erdos Prize, Israel 1991 Feher Prize, Israel 1997 Member of the Israel National Academy of Sciences 2000 Polya Prize, SIAM, USA 2001 Bruno Memorial Award, Israel 2005 Landau Prize, Israel 2005 EATCS-ACM Goedel Prize 2008 Israel Prize in Mathematics 2008 Member of the Academia Europaea 2011 EMET Prize 2015 Fellow of the American Mathematical Society 2015 Łojasiewicz Lecture at Jagiellonian University 2017 Fellow of the Association for Computing Machinery 2021 Leroy P. Steele Prize for Mathematical Exposition (with Joel Spencer) 2022 Shaw Prize in Mathematical Sciences 2024 Wolf Prize in Mathematics Advising and Grants While Alon has undoubtedly mentored numerous students during his tenure at Tel Aviv University and MIT, specific advisee names are not documented in the source material. Similarly, grant funding details remain unspecified despite his extensive research output.