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Donald RobertsonView profile

Lecturer

• Ergodic Theory
• Additive Combinatorics
• Interval Exchange Transformations
• +1 more

Donald Robertson is a Lecturer in Pure Mathematics at the University of Manchester, specializing in ergodic theory with applications to additive combinatorics. His work connects measurable dynamics with combinatorial number theory problems. Research explores ergodic properties of interval exchange transformations, sumset configurations in infinite sets, and equidistribution in homogeneous dynamics. Recent publications address Erdős' sumset conjecture (2022), saddle connection distributions (2023), and disjointness in measurable group actions. He teaches measure theory and ergodic theory courses, employing problem-based learning through weekly take-home tests. Coursework emphasizes Lebesgue integration, ergodic theorems, and connections between dynamics and combinatorics.

Paul Neville BalisterView profile

Professor

• Combinatorics
• Graph Theory
• Discrete Mathematics
• +4 more

Professor Paul Neville Balister is a faculty member and Fellow in the Mathematical Institute at the University of Oxford, where he serves as a University Lecturer and Professor of Mathematics. His research is centered in combinatorics and discrete mathematics, with strong ties to probabilistic methods and theoretical computer science. His research interests include combinatorics, graph theory, random graphs, probabilistic combinatorics, cellular automata, and discrete probability. These areas are evident from his extensive publication record in top-tier mathematical journals such as the Journal of the European Mathematical Society and Random Structures and Algorithms . The recent publications demonstrate a consistent focus on structural and probabilistic aspects of discrete systems, particularly in monotone cellular automata, graph saturation games, and random graph orderings. His work often explores threshold phenomena, extremal configurations, and asymptotic behavior in combinatorial models. While no formal awards are listed in the provided text, his active collaboration with leading mathematicians and publication in premier venues indicate significant recognition in the field. Professor Balister advises students and contributes to research grants, though specific names and projects are not detailed. He is part of the Combinatorics research group at Oxford, which fosters collaborative work in discrete mathematics and its applications.

Youness LamzouriView profile

Professor

• Analytic Number Theory
• Probabilistic Number Theory
• Character Sums and Exponential Sums
• +7 more

Youness Lamzouri is a Professor of Mathematics at the Université de Lorraine, France, affiliated with the Institut Elie Cartan de Lorraine (IECL) and a Junior Member of the Institut Universitaire de France (IUF). His research focuses on analytic and probabilistic number theory, particularly character sums, L-functions, prime number distributions, and random multiplicative functions. PhD in Mathematics from Université de Montréal (2009) B.Sc. in Pure Mathematics from Université de Montréal (2004) He has contributed extensively to understanding extreme values in character sums, biases in prime number races, and statistical properties of L-functions. His recent work explores GCD graphs, random walks in number theory, and probabilistic models for prime distributions. He has received prestigious awards including the CMS Blair Spearman Doctoral Prize and NSERC Postdoctoral Fellowship. Currently, he supervises doctoral and master students and contributes to editorial boards of leading journals.

• Analytic Number Theory
• Probabilistic Number Theory
• Random Multiplicative Functions
• +2 more

Professor Adam Harper specializes in analytic and probabilistic number theory at the University of Warwick. His research examines moments of random multiplicative functions, distribution of zeta sums, and extreme values in number theory. Teaches MA4L6 (Analytic Number Theory) and MA257 (Introduction to Number Theory). Recent publications (2019-2024) address Halász's theorem, Fyodorov-Keating conjectures, and character sum distributions. Research bridges combinatorics, probability, and statistical mechanics, with focus on multiplicative chaos and Gaussian processes.

Mihyun KangView profile

Professor

• Combinatorics
• Discrete Probability
• Algorithms
• +3 more

Mihyun Kang is a Professor in the Institute of Discrete Mathematics at Graz University of Technology (TU Graz), leading the Combinatorics Group. She holds significant academic positions and has been recognized with a Heisenberg Fellowship (German Research Foundation) and a Friedrich Wilhelm Bessel Research Award (Alexander von Humboldt Foundation). Her research focuses on combinatorics, discrete probability, and algorithms, with a specialization in random graph theory. She contributes to editorial boards, including Random Structures & Algorithms . Her research interests emphasize high-dimensional graphs, percolation processes, and structural properties of random graphs. She explores topics such as phase transitions, graph enumeration, and algorithmic applications in combinatorial problems. Her work bridges theoretical foundations with practical applications in algorithm design and probabilistic modeling. Dr. Kang’s scientific achievements include pioneering studies on hypergraphs, bootstrap percolation, and the evolution of random graph processes. Her recent publications highlight advancements in understanding graph components, connectivity thresholds, and universality phenomena in random structures. She collaborates widely, contributing to conferences and international initiatives like the SFB “Discrete random structures: enumeration and scaling limits.” Her professional activities include advising doctoral students and supervising research projects at TU Graz. She leads the Combinatorics Group, which hosts the Graz Combinatorics Seminar and actively engages in academic outreach. Her contributions extend to textbook authorship, including Diskrete Mathematik für die Informatik , and she maintains an active presence in discrete mathematics education and research.

Jan DraismaView profile

Professor

• Algebraic Geometry
• Combinatorics
• Algebraic Statistics
• +8 more

Jan Draisma is a full professor of Mathematics at the University of Bern and a part-time full professor of Applied Algebra and Geometry at Eindhoven University of Technology (TU/e), where he is affiliated with the Department of Mathematics and Computer Science, specifically in Discrete Algebra and Geometry and Coding Theory and Cryptology. He obtained his Master's and Ph.D. degrees from TU/e cum laude and held a postdoctoral position at the University of Basel (2002–2005). He returned to TU/e as an assistant professor, later advancing to associate professor (2011–2016), and served as a part-time full professor at VU Amsterdam (2015–2016). His research focuses on the interplay between combinatorics, statistics, and algebraic geometry. Key areas include tropical geometry, algebraic statistics, symmetric systems of polynomial equations in infinitely many variables, and representation stability. His work often explores the structure of infinite-dimensional algebraic objects and their finite approximations. The most recent publications highlight trends in polynomial functors, topological Noetherianity, amoebas of linear spaces, and the geometry of tensor representations. These works reflect a deep integration of algebraic geometry with combinatorics and category theory, emphasizing stabilization phenomena and symmetry in algebraic structures. NWO Vici Award: Stabilisation in Algebra and Geometry (2015) NWO Vidi Award: Finite thanks to symmetry (2010) Draisma has received significant research funding, including the NWO Vidi and Vici grants, and two NWO Free Competition grants (2008, 2012). He has supervised 16 students and is actively involved in the academic community as an associate editor for Experimental Mathematics, SIAM Journal on Applied Algebra and Geometry, and Linear and Multilinear Algebra. He has held leadership roles in major conferences such as MEGA 2015 and SIAM AG 19. He is affiliated with the research groups in Discrete Algebra and Geometry and Coding Theory and Cryptology at TU/e and leads research activities centered on algebraic methods in discrete mathematics and statistics.

Alex ScottView profile

Professor

• Combinatorics
• Graph Theory
• Probability

Alex Scott is a Professor of Mathematics at the Mathematical Institute, University of Oxford, with active research contributions evidenced by publications through 2025. His work is centered within the university's Mathematical Institute, a key hub for theoretical mathematics research. Scott's research specializes in combinatorics, particularly graph theory and probabilistic methods. His investigations span structural graph theory, extremal combinatorics, and random graph models, addressing fundamental questions about graph minors, forbidden substructures, and combinatorial optimization. This focus reflects deep engagement with discrete mathematical structures and their theoretical applications. Analysis of his publication timeline (2014-2025) reveals consistent contributions to graph theory, with recent work emphasizing subdivisions, stable sets, and graph reconstruction algorithms. Earlier research examined Erdős-Hajnal properties, deviations in random graphs, and dimensional properties of posets, demonstrating both depth and evolution in his scholarly focus. No scientific awards were documented in the source material. The available information does not specify any advised students or research grants, though his extensive publication record suggests significant collaborative research activity. Scott is affiliated with the Combinatorics research group at Oxford's Mathematical Institute, contributing to one of the world's leading centers for discrete mathematics research through theoretical investigations and academic collaboration.

Paul HornView profile

Professor

• Combinatorics
• Graph Theory
• Probability
• +3 more

Paul Horn is a Professor and Associate Chair of Graduate Studies in the Department of Mathematics at the University of Denver, within the College of Natural Sciences and Mathematics. He earned his Ph.D. in Mathematics from the University of California, San Diego (2009), under the supervision of Fan Chung. Prior to joining DU in 2013, he held postdoctoral positions at Emory University and Harvard University. His research focuses on combinatorics, graph theory, and probability, with a particular emphasis on applying probabilistic, algebraic, and geometric methods to analyze networks and graphs. Dr. Horn co-organizes the Rocky Mountains-Great Plains Graduate Research Workshop in Combinatorics (GRWC) and contributes to the graph theory section of the Masamu Advanced Studies Institute in southern Africa. He also serves as the graduate coordinator in the Mathematics Department, overseeing graduate student advising and program administration. His work spans theoretical contributions to graph structure, stochastic processes on networks, and applications in multi-agent systems and sensor networks. Publications highlight his expertise in graph curvature, network robustness, and combinatorial optimization, reflecting his interdisciplinary approach to discrete mathematics and its real-world applications. His research bridges pure and applied mathematics, addressing challenges in algorithm design, network dynamics, and geometric graph theory. Horn’s advising and mentorship activities include guiding graduate and undergraduate students in mathematics, emphasizing hands-on research experiences through workshops and collaborative projects. His contributions to academic leadership and research dissemination are evident through editorial roles and conference organization in combinatorics and graph theory.

Gourab RayView profile

Associate Professor

• Probability Theory
• Statistical Physics
• Stochastic Processes
• +3 more

Gourab Ray is an Associate Professor in the Department of Mathematics and Statistics at the University of Victoria, Faculty of Science. He holds a PhD from the University of British Columbia, Vancouver. His research focuses on the intersection of probability theory, geometry, and mathematical physics, particularly large-scale patterns in stochastic models inspired by physics. Key areas include random planar maps, random walks, lattice spin models, dimer models, Gaussian free field properties, and Liouville quantum gravity. Recent work emphasizes establishing Gaussian free field-like behaviors in dimer models across various graphs and surfaces. He teaches courses such as MATH 236: Introduction to Real Analysis and MATH 555: Topics in Probability. His publications span leading journals including Inventiones Mathematicae , Annals of Probability , and Probability Theory and Related Fields . Notable contributions include studies on unimodular hyperbolic triangulations, half-planar map classifications, and conformal invariance in dimer models. No specific awards are listed for Dr. Ray, though his work has been recognized in peer-reviewed venues. He actively contributes to academic service, including roles on graduate committees and research collaborations. His research group engages with theoretical and applied aspects of probability theory, often bridging discrete and continuous mathematical frameworks.

Lutz WarnkeView profile

Professor

• Combinatorics
• Probability Theory
• Random Graphs
• +5 more

Lutz Warnke is a Professor of Mathematics at the University of California, San Diego, with prior affiliations at Georgia Institute of Technology (where he received tenure in 2021) and Peterhouse, Cambridge University (Junior Research Fellow until 2016). His research focuses on probabilistic combinatorics, random graphs, phase transitions, and combinatorial probability, with applications to extremal combinatorics and Ramsey theory. Education : Ph.D. in Mathematics from the University of Oxford (2012), supervised by Oliver Riordan. Dr. Warnke's research explores the structure and evolution of random graphs and processes, including Achlioptas processes, Ramsey numbers, and extremal problems. His work often bridges probabilistic methods with algorithmic applications and theoretical computer science. His publications from 2022–2025 reveal trends in random graph isomorphisms, clique coloring thresholds, extremal subgraph counts, and hardness of online algorithms. Key subfields include percolation, phase transitions, and probabilistic methods applied to combinatorial structures. Scientific Awards : Dénes König Prize (2016), Alfred P. Sloan Research Fellowship (2018), NSF CAREER Award (2020), Richard Rado Prize (2014). Dr. Warnke actively supervises PhD students and postdocs, including Matthew Cho (PhD ongoing), Erlang Surya (PhD 2025), Emily Zhu (PhD 2025), and He Guo (PhD 2021). He has received teaching accolades at Georgia Tech and contributes to graduate courses in probabilistic combinatorics, random graph theory, and stochastic processes.

Andrea CollevecchioView profile

Professor

• Probability
• Mathematical Physics
• Statistical Mechanics
• +3 more

Andrea Collevecchio is a Professor in the School of Mathematics at Monash University, Australia, where he has been a faculty member since 2012. His research focuses on the intersection of Probability, Mathematical Physics, and Statistical Mechanics, with particular expertise in stochastic processes and theoretical modeling. He earned his PhD in Statistics from Purdue University in 2004, followed by postdoctoral positions in Italy and Germany. In 2006, he became Assistant Professor at Ca’Foscari University in Venice before joining Monash University. Collevecchio specializes in Reinforced Processes and Large Deviations, investigating complex systems through random walk models. His work bridges abstract probability theory with applications in statistical mechanics, examining phenomena like memory effects in stochastic processes and phase transitions in lattice systems. Recent research emphasizes hypercube structures, non-reversible dynamics, and reinforcement mechanisms. His 2021-2025 publications reveal a concentrated focus on hypercube random walks, with increasing exploration of non-reversible processes, vertex-reinforced dynamics, and bootstrap methods. These works consistently apply probabilistic frameworks to problems in mathematical physics, demonstrating strong connections between theoretical probability and physical modeling. Collevecchio has secured multiple research grants including ARC-funded projects on self-interacting random walks (2023-2026) and random walks with long memory (2018-2022). He contributes to interdisciplinary initiatives like the Smart Vehicles project for dementia support (2025-2027) and actively organizes academic events including the AIM Day series connecting mathematics, AI, and industry applications.

Benny SudakovView profile

Professor

• Extremal Graph and Hypergraph Theory
• Ramsey Theory
• Random Structures
• +5 more

Benny Sudakov is a Professor of Mathematics at ETH Zurich, where he conducts research in combinatorics. He has previously held positions at UCLA, Princeton University, and the Institute for Advanced Study. His work is supported by the SNSF grant 200021_196965. Research Interests: His primary research areas include Extremal Graph and Hypergraph Theory, Ramsey Theory, Random Structures, and the application of Algebraic and Probabilistic Methods in Combinatorics, with strong connections to Theoretical Computer Science. He investigates fundamental structural properties of discrete systems, such as the existence of regular subgraphs, extremal configurations, and the behavior of random combinatorial objects. The recent popular science articles on his work highlight a consistent trend of solving long-standing open problems in extremal combinatorics using sophisticated probabilistic and algebraic techniques. His research spans topics like equiangular lines, graph decompositions, and the emergence of cycles in sparse graphs, demonstrating a deep focus on the interplay between structure and randomness. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: He has advised numerous Ph.D. students, many of whom have gone on to become professors at top universities (e.g., Oxford, Stanford, CMU, ETH, Princeton). His research is currently funded by the Swiss National Science Foundation (SNSF). He has organized workshops and seminars, such as the Theory of Combinatorial Algorithms Mittagsseminar at ETH and a workshop at UCLA on Extremal and Probabilistic Combinatorics. Labs and Teams: He is a key member of the combinatorics group at ETH Zurich and co-organizes the Theory of Combinatorial Algorithms Mittagsseminar, a central forum for research discussions in discrete mathematics at the institution.

Stefan GlockView profile

Assistant Professor

• Discrete Mathematics
• Extremal Combinatorics
• Probabilistic Combinatorics
• +4 more

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.

• Operations Research
• Management Science
• Dynamic Pricing
• +4 more

Arash Asadpour Rahimabadi is an Associate Professor at the N. P. Loomba Department of Management within the Zicklin School of Business at Baruch College, CUNY . His research bridges Operations Research and Management Science , focusing on algorithmic design, dynamic pricing, and optimization in gig economy platforms. Education: Ph.D. in Operations Research, Stanford University (2010) BSc in Computer Engineering, Sharif University of Technology (2004) His research interests include stochastic optimization , submodular maximization , marketplace stability , and fair allocation . Recent work explores dynamic pricing in extreme value regimes , shared ride sustainability , and regulation of gig economy platforms . His scientific contributions span algorithmic game theory, combinatorial optimization, and resource allocation, with key publications in Management Science and Operations Research . Current projects analyze escrow payment mechanisms , shared mobility efficiency , and hotel reservation systems . Scientific Awards Best Paper Award, ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010 1st Rank in Iran’s National Graduate Entrance Exam in Computer Engineering, 2004 Silver Medals in Iranian National Olympiads in Informatics, 1999–2000 He serves on graduate and PhD committees at CUNY and has reviewed for journals including Management Science and Operations Research . His teaching includes courses like Decision Models and Analytics and Advanced Discrete Optimization .

Michael MolloyView profile

Professor

• Graph Theory
• Probabilistic Method
• Random Graphs
• +2 more

Michael Molloy is a Professor in the Department of Computer Science at the University of Toronto, with a cross-appointment to the Department of Computer and Mathematical Sciences at the University of Toronto Scarborough (UTSC). He teaches courses in Discrete Mathematics and the Probabilistic Method, including CSC/MAT A67 and CSC2427/MAT1500 . Research Focus: Graph Theory, Probabilistic Methods, Random Graphs, Constraint Satisfaction Problems, and Markov Chain analysis. His work includes foundational contributions to graph coloring, such as adaptable/conflict coloring and correspondence coloring, and exploring phase transitions in random graphs. He has supervised numerous graduate students, including Lora Hrisch, Jurgen Aliaj, and Hamed Hatami, advancing combinatorial and algorithmic research. Recent publications analyze random graph processes, the freezing threshold for k-colorings, and the resolution complexity of constraint satisfaction problems. These studies intersect theoretical computer science, combinatorics, and probabilistic modeling, often revealing deep structural insights through rigorous mathematical proofs.