Partha Sarathi Dey serves as Associate Professor in both Mathematics and Statistics at the University of Illinois at Urbana-Champaign, joining the faculty in 2014 after postdoctoral appointments at NYU's Courant Institute and the University of Warwick. His academic credentials include: Ph.D. in Statistics from UC Berkeley (2010) Undergraduate and Masters degrees from Indian Statistical Institute, Kolkata, specializing in Mathematical Statistics and Probability Dr. Dey's research bridges Probability Theory and Statistical Physics, with expertise in First/Last Passage Percolation, Random Growth Models, Stein's Method, Concentration Inequalities, Spin Glasses, Random Graphs, and Random Matrices. His work develops rigorous probabilistic frameworks for physical systems. Recent publications (2023-2025) demonstrate consistent focus on disordered systems and phase transitions, examining random walks on discrete tori, nonlinear Schrödinger equations in higher dimensions, critical-strip path structures, monomer-dimer models, and spin glasses under external fields. These studies reveal deep connections between probabilistic fluctuations and thermodynamic behavior. His distinguished recognitions include: Simons Fellowship Harrison Early-Career Fellowship Though specific advising records and grants are unreported, his extensive co-authorship network reflects active collaboration across international research communities in mathematical physics.
Jop Briët is a Researcher at the Department of Algorithms and Complexity at Centrum Wiskunde & Informatica (CWI) in the Netherlands. His work focuses on theoretical computer science, quantum information theory, combinatorics, and tensor analysis. He has held grants including the Veni Innovational Research Grant from NWO and a Rubicon fellowship. He has authored over 50 publications in leading venues, exploring topics such as Grothendieck inequalities, quantum computing, and additive combinatorics. His research interests span the interplay between combinatorics and computational complexity, with particular emphasis on tensor analysis, probabilistic methods, and algorithm design. Recent work includes studies on Szemerédi’s theorem with random differences and the application of quantum query algorithms to entanglement-based problems. Awards: Outstanding paper award TQC (2020), Andreas Bonn medal (2013), Stieltjesprijs (2011). Professional Activities: Editor for ERCIM News, Board Member of Koninklijk Wiskundig Genootschap, and frequent invited speaker at workshops on quantum computing and combinatorics. Grants: Veni Grant (2014), Rubicon Fellowship (2012). Current teaching includes courses on Additive Combinatorics and Quantum Information Processing, reflecting his commitment to bridging foundational theory with advanced applications in computing and mathematics.
Ross J. Kang is a Canadian mathematician currently serving as an Associate Professor at the Korteweg–de Vries Institute for Mathematics within the Faculty of Science at the University of Amsterdam since 2022. He is an active member of the Discrete Mathematics and Quantum Information group and the NETWORKS consortium. Previously, he held positions as Assistant/Associate Professor at Radboud University Nijmegen (2014-2022), Assistant Professor at Utrecht University (2013), and Researcher at Centrum Wiskunde & Informatica (2012-2013). His academic journey includes postdoctoral positions at Durham University (2010-2012) and McGill University (2008-2010), where he was advised by Bruce Reed and Louigi Addario-Berry. DPhil in Mathematics, University of Oxford (2008) - Thesis: 'Improper colourings of graphs', advised by Colin McDiarmid BSc (Hons) in Mathematics and Computer Science, University of Victoria (2003) - Governor General's Silver Academic Medal recipient Ross J. Kang's research focuses on probabilistic and extremal combinatorics, random discrete structures, graph coloring, geometric graphs, and algorithms. His work bridges theoretical mathematics with practical applications, exploring fundamental questions in discrete mathematics. He has made significant contributions to understanding graph coloring problems, particularly in the contexts of list coloring, distance coloring, and strong coloring. His research often employs probabilistic methods to establish bounds and structural properties in graph theory. Kang's work on the hard-core model, local occupancy method, and triangle-free graphs has advanced our understanding of the interplay between local constraints and global structure in discrete systems. Analysis of his recent publications reveals a strong emphasis on graph coloring problems, particularly list coloring variants and their extensions. His work frequently explores the relationship between graph structure (such as degree constraints, girth, or forbidden subgraphs) and coloring properties. A notable trend is his development and application of the local occupancy method to establish improved bounds for chromatic numbers in various graph classes. His research also demonstrates a consistent interest in extremal problems, seeking optimal configurations under specific constraints, particularly in the context of triangle-free graphs and geometric representations. NWO Open Competition M-1 grant entitled 'Asymptotic triangle-free structure (3Free)', 2022-2026 NWO Vidi grant entitled 'On the edge: theory and techniques at the frontiers of edge-colouring', 2017-2023 NWO Veni grant entitled 'Generalised colouring for random graph models', 2012-2015 Van Gogh travel grants (2020-2021 with Marthe Bonamy; 2016-2017 with Louis Esperet) Governor General's Silver Academic Medal (2003) Ross J. Kang has successfully supervised multiple PhD students including Eoin Hurley (defending May 2025), Stijn Cambie (defended April 2022), and François Pirot (winner of 2020 prix Charles Delorme). His research is supported by significant grants from the Netherlands Organisation for Scientific Research (NWO), including the prestigious Open Competition M-1 grant. Kang is actively involved in the academic community through his editorial role at Combinatorial Theory, co-organization of conferences like the Dutch Days of Combinatorics, and leadership in initiatives such as Innovations in Graph Theory, a diamond open access journal he helped launch in August 2023. As a member of the Discrete Mathematics and Quantum Information group at the University of Amsterdam and the NETWORKS consortium, Kang collaborates with researchers across various institutions. He has established strong international connections through his Van Gogh travel grants and participation in collaborative projects like the Sparse (Graphs) Coalition sessions. His research group focuses on theoretical aspects of discrete mathematics with connections to quantum information science, and he maintains active collaborations with researchers across Europe and North America.
Jared Duker Lichtman is a Szegö Assistant Professor at Stanford University's Department of Mathematics, beginning in the 2024-25 academic year. Previously, he served as an NSF Postdoctoral Fellow at Stanford under Prof. Kannan Soundararajan. He completed his PhD at the University of Oxford in 2023, focusing on multiplicative number theory. His research centers on prime number distribution, multiplicative structures, and analytic number theory. Notably, he established a world record in studying primes' distribution within arithmetic progressions. His work bridges classical number theory with modern techniques like sieve methods and L-function analysis. Jared's publications explore topics such as the abc conjecture, twin primes, and Erdős problems. While no formal awards are listed, his groundbreaking contributions to prime distribution and multiplicative number theory mark him as a rising star in the field. His academic trajectory includes a focus on primes in arithmetic progressions, Goldbach conjecture extensions, and probabilistic number theory applications. Ongoing research likely continues this trajectory, with potential implications for cryptography and additive number theory.
Kyla Pohl is a Visiting Assistant Professor of Mathematics at Colby College and an ABD PhD candidate at the University of Oregon, where she is advised by Ben Young. Her academic background includes a Bachelor of Arts degree in Mathematics with a concentration in Japan Studies from St. Olaf College and a Master's degree in Mathematics from the University of Oregon. Her research focuses on algebraic and enumerative combinatorics, with primary emphasis on Jack symmetric functions, hook length formulas, and probabilistic methods. She employs experimental approaches using SageMath and maintains an active GitHub repository showcasing implementations of combinatorial algorithms. Pohl's publications demonstrate expertise in both combinatorics and algebra, with recent work exploring probabilistic aspects of symmetric functions. Her research trajectory shows increasing focus on combinatorial algorithms and computational approaches to partition theory. She contributes to academic service through seminar organization and maintains educational resources including Jupyter notebooks demonstrating Markov Chain Monte Carlo methods. Her teaching experience includes courses in mathematics and mentorship through the Directed Reading Program.
Kevin Ford is a Professor of Mathematics at the University of Illinois at Urbana-Champaign, affiliated with the Department of Mathematics within the College of Liberal Arts & Sciences. His research focuses on Number Theory, including prime number theory, divisor theory, probabilistic methods, and sieve theory, with notable contributions to the Riemann zeta function and divisor distribution. Ford is also an editor for Research in Number Theory and the Bulletin and Journal of the London Mathematical Society . His recent work explores topics such as large gaps between primes, composite polynomial values, and the concentration of divisors. Ford’s publications often bridge analytic and probabilistic techniques to address classical number-theoretic problems. Despite extensive contributions, no specific academic awards are explicitly listed, though his editorial roles highlight his influence in the field. He advises no listed students, though his research group and collaborations with leading mathematicians like Terence Tao and Dimitris Koukoulopoulos are evident in his publications. Ford’s academic presence includes organizing the Illinois Number Theory Seminar and maintaining an active research agenda in number theory and combinatorics.
Maria José Serna Iglesias is a Full Professor at the Departament de Ciències de la Computació of the Universitat Politècnica de Catalunya (UPC), Barcelona Tech . She leads the research group ALBCOM (Algorithmics, Bioinformatics, Complexity and Formal Methods) and coordinates doctoral programs in Computing. Her research focuses on algorithmics, computational complexity, social network analysis, and game theory. She actively participates in conferences such as SEA 2023-2025 , CIAC , and Algorithmic Decision Theory . Teaching includes advanced algorithmics courses for undergraduate and master’s programs. Current projects include the MOTION initiative (PID2020-112581GB-C21) on large-scale data processing. Past projects involve EU initiatives like WISEBED and DELIS . Her work bridges theoretical computer science with applications in networks and social systems, emphasizing algorithmic solutions for complex problems.
Noga Alon is a Professor of Mathematics at Princeton University, affiliated with the Mathematics Department. He is renowned for his contributions to Combinatorics, Graph Theory, and Theoretical Computer Science. His research emphasizes algebraic and probabilistic methods, with applications in circuit complexity and combinatorial geometry. Education & Affiliations Current position: Professor at Princeton University. Active in the Princeton Discrete Mathematics Seminar and has led conferences like the Noga60 Birthday Conference. Research Interests Focus areas include Combinatorics (e.g., Ramsey Theory, Graph Coloring), Theoretical Computer Science (e.g., Algorithms, Complexity), and probabilistic and algebraic methods in discrete mathematics. His work bridges combinatorial structures and algorithmic applications, with contributions to expander graphs, randomized algorithms, and extremal graph theory. Publications Over 300 papers, including foundational work on the probabilistic method, expander graphs, and combinatorial algorithms. Notable recent topics include graph coloring, path-finding algorithms (e.g., Color-coding), and spectral techniques for graph problems. Grants & Awards No specific grants or awards listed in available texts, though his academic stature implies prestigious recognition in combinatorics and computer science. Labs & Collaborations Involved in collaborative research through Princeton’s Mathematics Department and international conferences. Leads seminars and co-authors work with prominent researchers like M. Naor, J. Spencer, and others.
Robert Guralnick is a Professor of Mathematics at the University of Southern California’s Dornsife College of Letters, Arts and Sciences. His research focuses on finite and algebraic groups, representation theory, and arithmetic algebraic geometry. He has made significant contributions to understanding group structures, character theory, and subgroup dynamics in both finite and algebraic contexts. His work spans advanced topics such as Sylow subgroup analysis, commutator properties, and probabilistic group generation. Recent studies include investigations into invariable generation in simple groups and generic stabilizers in algebraic group actions. Guralnick’s research often bridges abstract group theory with geometric and topological methods, addressing foundational questions in algebraic structures. His publications highlight interdisciplinary approaches to group theory, including applications to cohomology, combinatorics, and representation theory. Despite no explicit mention of awards, his extensive publication record reflects sustained academic impact in pure mathematics. Guralnick’s advising and grant activities are not detailed here, though his prolific research output suggests active mentorship and funding support. No specific lab affiliations or teams are noted in the provided texts.
Peter Winkler is William Morrill Professor of Mathematics and Computer Science at Dartmouth College, conducting research in discrete mathematics, probability, and theoretical computer science. His work connects combinatorial problems with statistical physics and algorithmic complexity. Key research areas include: Probabilistic methods in combinatorics and game theory Phase transitions in discrete structures Geometric probability and optimization Mathematical puzzles and paradoxes Winkler's publications resolve fundamental questions in pursuit-evasion theory, geometric set optimization, and combinatorial phase transitions. His work on mathematical puzzles has influenced both academic research and popular mathematics. Current projects explore limit permutations, abelian networks, and new puzzle collections. Honored with the Mathematical Association of America's Lester R. Ford Award and David P. Robbins Prize, Winkler has held visiting positions at the Institute for Advanced Study and Mathematical Sciences Research Institute.
Raimund Seidel is a Professor in the Department of Computer Science at Universität des Saarlandes, leading the Chair of Theoretical Computer Science. He is actively involved in research and teaching, focusing on foundational aspects of algorithms and data structures, particularly in computational geometry. His primary research interests include theoretical computer science , design and analysis of efficient algorithms , geometric data structures , randomized algorithms , and combinatorial geometry . His work addresses fundamental problems such as planar point location, convex hull computation, and efficient encoding of triangulations. He also investigates geometric algorithms under the transdichotomous model, leveraging word-level parallelism. The selected publications reflect a long-standing contribution to computational geometry and data structure theory , with a focus on randomized methods and exact complexity analysis. His research combines theoretical rigor with practical implications for algorithm design. Award or honor not found in the provided text. Prof. Seidel has advised several students, including Alexander Malkis , Ralf Osbild , Udo Adamy , Christian Sohler , and others, many of whom have gone on to academic and research careers. No explicit information about grants or funding is available in the text. He leads a research group within the Department of Computer Science at Universität des Saarlandes, mentoring current staff such as László Kozma , Giorgi Nadiradze , and Lavinia Dinu . The group maintains active research in theoretical computer science and computational geometry.
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.
Davi De Castro Silva is a Researcher at the University of Cambridge, affiliated with the Department of Computer Science and Technology and the Centre for Quantum Information and Foundations. His current work is advised by Tom Gur and Sergii Strelchuk. Previously, he was a postdoc at CWI (Amsterdam) in QuSoft, advised by Jop Briët, and completed his PhD in Applied Mathematics at the University of Cologne under Frank Vallentin and Fernando de Oliveira Filho. He holds a Master's from IMPA (Brazil) under Roberto Imbuzeiro Oliveira and a BSc/MSc from École Polytechnique (France). His research focuses on theoretical computer science, quantum computing, and combinatorics, with recent emphasis on quantum speedups' structural foundations, such as symmetry's role. Key areas include additive combinatorics (e.g., higher-order Fourier analysis), computational complexity (lower bounds), combinatorial optimization (semidefinite programming), and quantum information theory. Notable contributions include studies on quasirandomness in additive groups, quantum algorithms' limitations, and tensor analysis. His work bridges combinatorial methods with quantum computing, exploring algorithmic efficiency and structural properties. He has published in journals like Discrete Analysis , Combinatorica , and Forum of Mathematics, Sigma , with preprints addressing quantum computation symmetry, Goldreich-Levin algorithms, and hypergraph quasirandomness. His research highlights interdisciplinary approaches to foundational questions in computing and mathematics.
Dudley Stark is a Reader in Mathematics and Probability at the School of Mathematical Sciences, Queen Mary University of London. He holds a BA in Mathematics and BS in Physics from the University of Rochester, an MA in Mathematics from UCLA, and a PhD in Mathematics from the University of Southern California. Prior to his current role, he held postdoctoral positions at the University of Zurich, University of Melbourne, and Hewlett Packard Laboratories in Bristol, and was a visiting scholar at Green-Templeton College (University of Oxford) and on secondment to the University of Bristol. His research focuses on probabilistic and enumerative combinatorics, random combinatorial objects (e.g., permutations and graphs), Poisson approximation, generating functions, and asymptotic expansions. He teaches courses such as Bayesian Statistical Methods and Advanced Derivatives Pricing and Risk Management. His work spans over 30 years, with contributions to stochastic processes, graph theory, and combinatorial probability. His research has been published in top journals like Stochastic Processes and Their Applications , Discrete Mathematics , and Advances in Applied Mathematics . Stark collaborates with institutions globally and contributes to the Centre for Combinatorics, Algebra and Number Theory. His expertise includes random graph theory, asymptotic enumeration, and applications of probabilistic methods in combinatorial structures.
Julia Wolf is a Professor of Pure Mathematics at the University of Cambridge, affiliated with the Department of Pure Mathematics and Mathematical Statistics (DPMMS) and Trinity College. Her research focuses on arithmetic combinatorics, harmonic analysis, and analytic number theory, with interdisciplinary connections to model theory, discrete geometry, and theoretical computer science. She holds an EPSRC Open Fellowship and has organized events like the Warwick-Oxbridge-Manchester-Bristol-London (WOMBL) meetings. Wolf teaches advanced courses such as 'Higher-Order Uniformity' and 'Analytic Number Theory,' emphasizing structure and applications. Her work bridges combinatorial, analytic, and algebraic techniques, addressing problems like polynomial configurations in primes, extremal hypergraph theory, and Ramsey multiplicity. Recent research includes structural stability in finite abelian groups and applications of model theory to additive combinatorics. Wolf actively promotes open-access publishing and has mentored numerous postdoctoral researchers and students through initiatives like the Philippa Fawcett Internship Programme. She also contributes to academic equity efforts, such as gender-inclusive hiring in mathematics. Professional activities include editorial roles, conference organization (e.g., the Simons Institute's Pseudorandomness program), and leadership in collaborative projects like the 'Combinatorics Meets Model Theory' workshop. Her grants and fellowships underscore her contributions to advancing discrete mathematics and fostering international academic networks.
