Professor Imre Leader is a distinguished mathematician at the University of Cambridge, where he serves as Professor of Pure Mathematics in the Department of Pure Mathematics and Mathematical Statistics (DPMMS), which is part of the Faculty of Mathematics. His office is located in room C2.02 at the DPMMS building. Professor Leader's research primarily focuses on Extremal Combinatorics and Ramsey Theory , two fundamental areas of discrete mathematics. His work explores deep connections between combinatorial structures, set theory, and algebraic properties. He has made significant contributions to understanding partition regularity, monochromatic structures, extremal set theory, and combinatorial geometry. His research often bridges the gap between pure combinatorics and applications in computer science and theoretical mathematics. Over his prolific career, Professor Leader has published numerous influential papers in top mathematical journals, collaborating with leading mathematicians worldwide. His work spans various aspects of combinatorics including hypergraph theory, geometric combinatorics, additive number theory, and combinatorial game theory. He has been particularly active in advancing our understanding of Ramsey-type phenomena in infinite structures and developing new techniques in extremal combinatorics. Research Group: Combinatorics Email: I.Leader@dpmms.cam.ac.uk Telephone: 01223 765902 Personal homepage: https://www.dpmms.cam.ac.uk/~ibl10
Kurt Johansson is a Full Professor of Mathematics at KTH Royal Institute of Technology, Sweden. His academic journey includes roles as Associate Professor at KTH (1993-2001) and Uppsala University (1988-1993), alongside research funded by the Swedish Natural Science Research Council (1998-2003). His primary affiliations are within the Department of Probability, Mathematical Physics & Statistics at KTH, where he also coordinates courses on Differential Equations and Fourier Analysis. Education: BSc in Physics (1982) and PhD in Mathematics (1988), both from Uppsala University. Research interests focus on Probability Theory , Mathematical Physics , and Random Matrix Theory , with contributions to stochastic models, determinantal processes, and universality in statistical mechanics. Key Awards: Wallenberg Prize (1995), Rollo Davidson Prize (2000), Göran Gustafsson Prize (2002), Fellow of the American Mathematical Society (2012), and multiple Wallenberg Scholar grants (2011-2023). Grants: Major funding from the Swedish Research Council (VR), K&A Wallenberg Foundation, and others. His research group explores Random Matrices, Stochastic Models, and Analysis , with notable work on the Arctic Circle Theorem and KPZ universality class. Recent publications analyze Brownian directed percolation and domino tilings of the Aztec diamond, reflecting his focus on interdisciplinary applications of probability and mathematical physics.
Jan de Gier is a Professor at the School of Mathematics and Statistics, The University of Melbourne . He is also the Founding Director of MATRIX , Australia’s residential research institute in the mathematical sciences, and a former Deputy Director and Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) . Additionally, he co-founded the Australian and New Zealand Association for Mathematical Physics (ANZAMP) in 2011 and served as its inaugural Chair. His research focuses on solvable lattice models at the intersection of mathematical physics and statistical mechanics . Key areas include the application of quantum integrability , algebraic structures like the Yang-Baxter equation, Hecke algebras, and quantum groups, as well as analytical methods such as complex analysis and elliptic curves. His work bridges pure and applied mathematics through connections between enumerative combinatorics , representation theory , and real-world phenomena like traffic flow modeling via exclusion processes . The 15 most recent articles reflect his expertise in integrable systems , non-equilibrium statistical mechanics , and algebraic combinatorics . Topics span Macdonald polynomials , stochastic duality , quantum spin chains , and traffic modeling , with methodologies involving matrix product forms , exact solutions , and critical phenomena analysis. He has contributed to editorial efforts through the AustMS Gazette and MATRIX Annals, and has been involved in public science communication via opinion pieces on mathematics funding and applications. His work emphasizes the importance of fundamental research in driving technological innovation, as highlighted in media articles discussing pi calculation , zero-knowledge proofs , and mathematics education .
Alexey Bufetov is a Professor at Leipzig University, holding an ERC Starting Grant for his research in Integrable Probability (2022-2027). Previously, he served as a W2-Professor ("Bonn Junior Fellow") at the Hausdorff Center for Mathematics (2018-2021) and as a CLE Moore Instructor at Massachusetts Institute of Technology (2015-2018). His research centers on Probability Theory , with deep connections to Mathematical Physics and Combinatorics . Key areas include integrable probability, stochastic particle systems (ASEP/TASEP), random tilings, Schur generating functions, and representation-theoretic aspects of probability. His work often bridges abstract mathematical structures with physical models from statistical mechanics. Bufetov's recent publications reveal a strong focus on integrable systems and asymptotic analysis , particularly exploring connections between Mallows measures, vertex models, and random matrix theory. His 2025 work on Aztec diamond domino tilings exemplifies his signature approach combining combinatorial structures with probabilistic methods. His primary recognition is the ERC Starting Grant "Integrable Probability" (2022-2027), supporting his cutting-edge research program. Bufetov has maintained a prolific collaborative network, frequently publishing with leading researchers including Alexei Borodin, Vadim Gorin, Leonid Petrov, and Kailun Chen. His work appears in top journals such as Advances in Mathematics , Duke Mathematical Journal , and Communications in Mathematical Physics .
David Damanik is the Robert L. Moody, Sr. Professor of Mathematics at Rice University, where he has established himself as a leading researcher in spectral theory, dynamical systems, and aperiodic order. His work bridges pure mathematics with mathematical physics, focusing on the spectral properties of operators arising in quantum mechanics and quasicrystal theory. Dr. Damanik received his academic training at Johann Wolfgang Goethe-Universität in Frankfurt, Germany, earning a Dipl.-Math. in 1995, Dipl.-Inform. in 1996, and Dr. phil. nat. in 1998. His educational background reflects a strong foundation in both mathematics and computer science, which informs his interdisciplinary research approach. His research interests center around spectral theory of Schrödinger operators, particularly those with ergodic, quasi-periodic, and aperiodic potentials. He has made significant contributions to understanding the spectral properties of operators associated with quasicrystals, substitution sequences, and other aperiodic structures. His work often connects spectral properties with dynamical systems concepts, particularly through the study of rotation numbers, Lyapunov exponents, and gap labeling theorems. Damanik's research has profound implications for understanding quantum transport in aperiodic media and the mathematical foundations of condensed matter physics. Analysis of his recent publications (2022-2024) reveals a continued focus on ergodic Schrödinger operators, with two comprehensive monographs providing a systematic treatment of the field. His work spans both theoretical foundations and specific applications, addressing problems in one-dimensional systems, quasi-periodic potentials, and aperiodic tilings. The research demonstrates strong connections between spectral theory, dynamical systems, and mathematical physics, with particular emphasis on the interplay between spectral properties and the underlying dynamics of the potential. Annales Henri Poincaré Prize (2014) for the paper "Continuum Schrödinger operators associated with aperiodic subshifts" Professor Damanik has mentored numerous PhD students and maintains an extensive network of collaborators across the globe, as evidenced by his long list of coauthors. His research has been supported by various grants that enable him to organize workshops and conferences, fostering collaboration in his field. He has been instrumental in organizing major conferences such as the Spectral Theory and Mathematical Physics conference honoring Barry Simon's 80th birthday (scheduled for 2026) and multiple workshops on aperiodic order at prestigious institutions like Banff International Research Station and Mathematisches Forschungsinstitut Oberwolfach. Through his teaching of specialized courses like "Mathematics of Aperiodic Order" and "Ergodic Theory and Topological Dynamics," Damanik has cultivated the next generation of researchers in his field. His leadership in organizing conferences and workshops has established him as a central figure in the international community studying spectral theory and aperiodic structures.
Luca Carloni is a Professor of Computer Science and Department Chair at Columbia University's Columbia Engineering. He leads the System-Level Design Group, focusing on heterogeneous system-on-chip (SoC) architectures, networks-on-chip (NoC), and embedded systems. Carloni holds a Laurea Summa Cum Laude in Electronics Engineering from the University of Bologna and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His work emphasizes specialized hardware design, energy-efficient computing, and FPGA-based prototyping. Research interests include system-level design methodologies for SoCs, embedded accelerators, and quantum computing hardware. He has pioneered frameworks like Embedded Scalable Platforms (ESP) and tools like MosaicSim for rapid SoC prototyping. Carloni has received numerous awards, including the NSF CAREER Award (2006), IEEE Fellow (2017), and multiple best paper awards at DATE and CloudCom conferences. He has served on editorial boards of IEEE Transactions on CAD and ACM Transactions on Embedded Computing , and chaired key conferences like EMSOFT and ESWeek. His research addresses challenges in heterogeneous architectures, power management, and the intersection of machine learning with embedded systems. Current projects explore quantum control systems, brain-computer interfaces, and energy-efficient datacenter computing.
Dr Jon Warren is a Reader in Statistics at the University of Warwick, specializing in probability theory. His research spans stochastic flows, random matrices, and properties of Brownian motion, with significant contributions to understanding complex stochastic systems. Research Interests: Dr Warren's work is centered on probability theory, particularly in the areas of stochastic flows, random matrices, and Brownian motion. His research delves into the intricate behaviors of these systems, exploring their properties and applications in various mathematical contexts. Publications: His recent publications cover a wide range of topics within probability theory, including stochastic heat equations, Dyson Brownian motion, and random matrix theory. These works highlight his expertise in both theoretical developments and practical applications of stochastic processes. Teaching: He teaches ST910 Introduction to graduate probability, demonstrating his commitment to educating the next generation of statisticians and probabilists. Contact: Dr Warren can be reached at J.Warren@warwick.ac.uk for academic inquiries or collaboration opportunities.
Professor Damien Woods is a faculty member at Maynooth University's Faculty of Science & Engineering, specifically affiliated with the Department of Computer Science and the Hamilton Institute. He leads groundbreaking research in DNA computing, molecular programming, and optical computing, focusing on self-assembly, algorithmic design, and computational complexity. ERC Consolidator Grant: 'Computationally Active DNA Nanostructures' SFI ERC Support Award EIC Pathfinder Challenge Grant: 'DISCO - DNA Infrastructure for Storage and Computation' His research projects explore programmable DNA storage, molecular robotics, and robust self-assembly systems. Recent publications span diverse topics like algorithmic DNA tile assembly, thermodynamic stability, and computational universality in nanosystems. Awards include ERC and SFI grants, with a focus on bridging theoretical computer science and experimental molecular biology. Scientific Contributions include: 2022: 'Turning Machines' - Molecular Robotics 2019: 'Diverse Molecular Algorithms' in Nature 2017: 'A Cargo-Sorting DNA Robot' in Science
Tamás Keleti is a Professor in the Department of Analysis at Eötvös Loránd University (ELTE) in Budapest, Hungary. He has been actively teaching various mathematics courses since at least 2006, including Univariate Analysis, Multivariate Analysis, Real Function Theory, Geometric Measure Theory, and Descriptive Set Theory. His office is located at Pázmány Péter sétány 1/c, Budapest, 1117 Hungary, with contact information including phone (36-1)-209-0555 / ext. 8510. Professor Keleti's research primarily focuses on Geometric Measure Theory , with special emphasis on Hausdorff Dimension and dimensional properties of sets in Euclidean spaces. His work investigates how dimension behaves under transformations, projections, and other operations, making significant contributions to understanding sets avoiding certain patterns and structures. He has developed deep connections between geometric measure theory, combinatorial geometry, and harmonic analysis. Analysis of his recent publication record reveals a consistent research trajectory in dimensional properties, with particular attention to Fubini-type theorems for Hausdorff dimension, Kakeya-type problems, and tiling problems with connections to Diophantine approximation. His work often bridges pure mathematical theory with applications in fractal geometry and combinatorial number theory. Scientific Awards and Achievements: Led ELTE's team to win the International Mathematics Competition for University Students in 2007 Led ELTE's team to win the International Mathematics Competition for University Students in 2008 As an advisor and mentor, Keleti has cultivated exceptional mathematical talent. In the 2007 and 2008 International Mathematics Competitions, his students Endre Csóka, Demeter Kiss, Péter Pál Pach, Roland Paulin, András Béla Rácz, and Balázs Strenner won first prizes, while Márton Hablicsek won a second prize. Several achieved remarkable individual rankings, with Roland Paulin placing 3rd overall and András Béla Rácz 5th in 2008. Professor Keleti has developed extensive course materials and problem sets for his analysis courses, contributing significantly to mathematics education at ELTE. His teaching spans from introductory analysis for first-year mathematics teacher training students to advanced topics like Geometric Measure Theory and Descriptive Set Theory for specialized students, demonstrating his commitment to both research and education.
Jonathan Pakianathan is a Professor of Mathematics at the University of Rochester's School of Arts & Sciences, Department of Mathematics. He holds a PhD from Princeton University (1997) and a BS in Mathematics and Physics from Caltech (1992). His research focuses on algebraic topology, cohomology of groups and Lie algebras, geometric combinatorics, and finite fields. He has held leadership roles, including Director of Graduate Studies (2014–2020) and Director of Undergraduate Studies (2003–2010). Notable awards include the Goergen Award for Excellence in Teaching (2014) and the Sloan Foundation Doctoral Dissertation Fellowship (1996). His research explores applications of topology and algebra in discrete geometry, often collaborating with Alex Iosevich and students. Recent work addresses topics like Fuglede's conjecture over finite fields, geometric configurations, and probabilistic methods in combinatorics. His articles frequently intersect harmonic analysis, group theory, and number theory, reflecting interdisciplinary strengths. Education : PhD, Princeton University, 1997 BS in Mathematics and Physics, Caltech, 1992 Awards : Goergen Award for Excellence in Undergraduate Teaching, 2014 Sloan Foundation Doctoral Dissertation Fellowship, 1996 H. J. Ryser Scholarship, 1991 Grants include an NSA Mathematical Sciences Grant (2016–2017, $110,000 total) with A. Iosevich. He advises numerous PhD students, many of whom now hold academic or research positions. His teaching spans undergraduate to graduate courses, including algebra, topology, and financial mathematics. Research groups and collaborations extend to geometric combinatorics, algebraic topology, and applications in physics and data science. Ongoing projects explore topological methods in discrete geometry and probabilistic structures over finite fields.
Basile de Loynes is a Lecturer at the French National School of Statistics and Information Analysis (ENSAI), holding a permanent academic position since at least 2016. He maintains a dual affiliation as a CREST (Center for Research in Economics and Statistics) Affiliated Member, contributing to interdisciplinary economic-statistical research. His academic trajectory includes a postdoctoral position at the University of Neuchâtel (2012), followed by temporary lecturer roles at the University of Burgundy (2013-2014) and University of Strasbourg (2014-2016). His research centers on advanced probability theory with specific expertise in stochastic processes on non-Euclidean structures. Key areas include: Random walks on algebraic structures (groups, groupoids, tilings, graphs) Poisson-Martin boundary theory and potential analysis Long memory processes and invariance principles Graph signal processing with Fourier/wavelet methods His publication record shows consistent output in top-tier journals since 2012, with recent work (2021-2023) focusing on graph-based signal denoising and differential privacy applications. Analysis of his 10 most recent publications reveals a strong methodological thread connecting classical probability theory with modern graph-based signal processing. Approximately 60% of his work since 2016 involves graph-structured stochastic models, demonstrating an evolving research trajectory from theoretical random walk properties toward applied graph signal analysis. The recurring subfields across publications include Markov additive processes, spectral graph theory, and wavelet transforms on non-Euclidean domains. His academic service includes developing comprehensive teaching materials for core probability and measure theory courses at ENSAI, with publicly available lecture notes and examinations dating back to 2016.
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.
Richard Kenyon is the Erastus L. DeForest Professor of Mathematics at Yale University, serving as Director of Undergraduate Studies. His research focuses on statistical mechanics, probability, and discrete geometry, with notable contributions to dimer models, random tilings, and integrable systems. He has explored topics such as limit shapes, phase transitions, and combinatorial configurations. His work intersects algebraic geometry, combinatorics, and mathematical physics, often involving the analysis of lattice models and their applications. His research includes open problems such as tiling optimization, geometric spanning surfaces, number theory questions, and rigidity of tilings. Kenyon's gallery showcases visualizations of mathematical concepts, including random triangulations, Vinnikov curves, and conformal mappings. His academic contributions span over three decades, with recent articles addressing dimers, webs, and eigenvalue properties. He actively collaborates on projects like the six-vertex model, multiwebs, and renormalizable dynamical systems. Kenyon’s academic service includes directing undergraduate studies at Yale and contributing to initiatives in discrete differential geometry. His work highlights the interplay between pure mathematics and applied probability, with applications in physics and combinatorial optimization.
Aanuoluwapo Ojelade is a Distinguished Research Fellow in the Department of Industrial and Systems Engineering at the University at Buffalo, School of Engineering and Applied Sciences. His work bridges occupational ergonomics, biomechanics, and construction safety through advanced technologies. Education: PhD, Industrial and Systems Engineering, Virginia Tech University MEng, Industrial and Systems Engineering, Virginia Tech University BEng, Civil Engineering, Osun State University Research Interests: Focus on exoskeleton technology for construction workers, biomechanical analysis of manual tasks, and motion capture systems for ergonomic evaluation. His studies address physical demand reduction, workplace interventions, and technology adoption barriers. Recent Article Trends: Leverage machine learning (random forest, recurrent neural networks) for ergonomic analysis, compare exoskeleton efficacy across industries (construction, mining), and evaluate demographic impacts on technology readiness. Markerless motion capture and EMG-based force prediction are recurring methodologies. Contact: 317 Bell Hall, University at Buffalo, aojelade@buffalo.edu, (716) 645-4721.
Ron Peled is a Full Professor in the School of Mathematical Sciences at Tel Aviv University. Starting in summer 2024, he will serve as a Brin Professor in the Department of Mathematics at the University of Maryland, on leave from Tel Aviv University. During the 2022-2024 academic years, he visited Princeton University and the Institute for Advanced Study. His research spans multiple areas of probability theory and statistical physics, with significant contributions to understanding random surfaces, first-passage percolation, spin systems, and disordered models. Peled's research interests primarily focus on Probability Theory and Statistical Physics. His work examines the behavior of random systems, particularly in the presence of disorder or constraints. He has made significant contributions to understanding minimal surfaces in random environments, the structure of geodesics in first-passage percolation, phase transitions in spin systems, and the properties of random surfaces. His research often combines deep probabilistic insights with connections to statistical mechanics and mathematical physics, revealing universal behaviors in complex random systems. Analysis of Peled's recent publications reveals a strong focus on understanding the effects of disorder in statistical physics models. His work spans multiple domains including first-passage percolation, random surfaces, spin systems, and random matrix theory. A recurring theme is the investigation of how microscopic randomness affects macroscopic properties, with particular attention to phase transitions, correlation decay, and geometric structures emerging in random environments. His research often employs sophisticated probabilistic techniques combined with insights from statistical mechanics. Peled has received significant recognition through prestigious grants including multiple Israel Science Foundation grants (1048/11, 861/15, 1971/19, 2340/23), a Marie Skłodowska-Curie Actions International Reintegration Grant (SPTRF), an ERC Starting Grant (LocalOrder), and an ERC Consolidator Grant (Transitions). These awards reflect the importance and impact of his research in the mathematical community. Peled has supervised numerous students and postdocs throughout his career. His Ph.D. students include Daniel Hadas (joint with Wojciech Samotij) and Yinon Spinka (graduated August 2018). His Master's students include Michal Bassan (joint with Shoni Gilboa), Daniel Hadas, Yoav Bar Nir, Dor Elboim (who went on to do a Ph.D. at Princeton), Vital Kharash, Omri Cohen-Alloro, Alexey Gladkich, and Yinon Spinka. He has also mentored postdoctoral fellows including Lakshmi Priya, Paul Dario, Matan Harel, Raimundo Briceño, Alexander Glazman, Alexander Magazinov, Xiaolin Zeng, Nishant Chandgotia, Jeremiah Buckley, Wojciech Samotij, and Tom Ellis. Peled is actively involved in the academic community, serving as one of the organizers of the online Joint Israeli Probability Seminar and previously organizing the Horowitz Seminar on Probability, Ergodic Theory and Dynamical Systems. He has also organized several workshops and conferences including "Challenges in probability and statistical mechanics" at the Technion in 2022, the "Workshop on Strongly Correlated Random Interacting Processes" at Oberwolfach in 2018, and "Elegance in probability: A conference honoring Russell Lyons' 60'th birthday" at Tel Aviv University in 2017.
