David Perkinson is a Professor of Mathematics at Reed College, where he holds a position in the Department of Mathematics. His research focuses on combinatorics, algebraic geometry, and discrete mathematics, with a particular emphasis on sandpile models, graph theory, and matroid theory. He is the author of the textbook *Divisors and Sandpiles: An Introduction to Chip-Firing*, which explores the combinatorial theory of chip-firing on graphs. Perkinson has also developed software tools like the Sandpile Java App, which visualizes and analyzes the Abelian Sandpile Model. He organizes the Cascade Lectures in Combinatorics (CALICO), a series of conferences funded by the National Science Foundation, aimed at fostering collaboration among researchers in combinatorics. His work bridges discrete mathematics with algebraic geometry, emphasizing connections between graph theory and geometric structures. Perkinson teaches advanced courses in analysis and contributes to the academic community through his research on topics such as divisor theory on graphs, sandpile groups, and combinatorial game theory. His recent publications (2015–2024) address matroid theory, sandpile dynamics, and applications of algebraic methods to discrete systems.
Dr. Antal Jarai is a Senior Lecturer in the Department of Mathematical Sciences at the University of Bath, where he also contributes to the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) and the Probability Laboratory at Bath. His work bridges probability theory and statistical physics, focusing on random processes with spatial and/or temporal structure. PhD in Mathematics from Cornell University (2000) BSc from Eötvös Loránd University (1996) Dr. Jarai's research explores problems motivated by statistical physics, including percolation, random walks, branching random walks, uniform spanning trees, and Abelian sandpiles. His recent publications address interlacement limits, asymptotics of optimal policies, resistance scaling, and wireless network proximity. He actively collaborates on interdisciplinary projects in network mathematics and wireless technology. Key trends in his publications include asymptotic analysis (5/5 papers), random walk theory (4/5), and probabilistic methods in statistical physics (4/5). Subfields span interlacement theory, self-organized criticality, stochastic geometry, and disordered systems. Royal Society Grant for 'Zero Dissipation Limit in Abelian Sandpiles' London Mathematical Society Grant for 'Critical Exponents in Sandpiles via Exact Sampling' EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) Dr. Jarai serves as Principal Investigator on multiple research grants and supervises students in probability and applied mathematics. He has contributed datasets on sandpile simulations and collaborates internationally on network mathematics projects.
Tatiana Smirnova-Nagnibeda is an Associate Professor in the Mathematics Section at the University of Geneva, where she obtained her PhD before holding positions at ETH Zurich and KTH Stockholm. She returned to UNIGE where she has established herself as a leading researcher in geometric and combinatorial group theory. Her research focuses on combinatorial, asymptotic and geometric group theory, as well as probabilities on groups and graphs. She has made significant contributions to the understanding of branch groups, self-similar groups, Schreier graphs, and spectral properties of group actions. Her work often bridges algebra, probability, and geometry, revealing deep connections between these areas through the study of Thompson's groups, Grigorchuk's group, and other important group constructions. Her recent publications demonstrate a consistent focus on subgroup structure in various classes of groups, spectral properties of Schreier and Cayley graphs, and connections to dynamical systems. She frequently collaborates with researchers from around the world, particularly with Rostislav Grigorchuk, and has mentored numerous doctoral students who have gone on to successful academic careers. Managing Editor for Groups, Geometry, and Dynamics Editor for L'Enseignement Mathématique Organizer of GAGTA conferences (2022, 2024) Organizer of specialized workshops on high-dimensional expanders (2015, 2016) She leads an active research group comprising postdoctoral fellows and doctoral students working on various aspects of group theory and its applications. Her teaching includes advanced courses on graph theory, random walks on groups, spectral theory of graphs, and amenability at the University of Geneva.
Lionel Levine is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His academic research focuses on abelian networks, interacting particle systems, and the emergence of complex patterns from simple rules. He has held prestigious fellowships, including the Simons Fellowship and Sloan Research Fellowship, and has been honored with an endowed professorship. Levine's work bridges probability theory, combinatorics, and statistical physics, with notable contributions to the study of sandpile models and internal diffusion-limited aggregation (IDLA). Education: Ph.D. in Mathematics (2007), University of California, Berkeley. Research Interests: Applied Mathematics, Combinatorics, Probability, Abelian Networks, Sandpile Models, and their intersections with computer science and statistical physics. His research explores how local rules generate large-scale structures, such as in abelian networks and sandpile models. Awards and Honors: Simons Fellowship, Sloan Research Fellowship, Endowed Professorship in the College of Arts and Sciences. Teaching: Courses include Probability Theory (MATH 6710/6720), Topics in Probability: Math for AI Safety (MATH 7710), and undergraduate mathematics courses like Strategy, Cooperation, and Conflict (MATH 1340). Grants and Funding: Supported by the National Science Foundation (NSF), Simons Foundation, Sloan Foundation, and Institute for Advanced Study. Collaborations: Collaborates with prominent researchers such as Yuval Peres, Cris Moore, and Jim Propp. His work has been published in leading journals like the Annals of Probability and Duke Mathematical Journal. Future Work: Continues investigating AI safety, causal models, and multi-agent learning, including research on mathematical frameworks for transformer circuits and hidden incentives in AI systems.
Melanie Matchett Wood is the William Caspar Graustein Professor of Mathematics at Harvard University. Her research spans number theory, arithmetic statistics, algebraic geometry, and probability theory, with a focus on distributions of class groups, Galois groups of unramified extensions, and random algebraic structures. She has been supported by prestigious awards including the Packard Fellowship, the NSF Waterman Award, and the MacArthur Fellowship. Her work connects number theory to topology through function field analogs, studying moduli spaces of curves and their statistical properties. She has made significant contributions to understanding the universality of random matrix cokernels and their applications to sandpile groups of graphs. Her editorial roles include the Journal of the American Mathematical Society and Algebra and Number Theory . Recent publications emphasize arithmetic topology, proving universality theorems for 3-manifold groups, and developing new heuristics for class group torsion. She organizes seminars on arithmetic statistics and topology-number theory interactions. Her teaching includes advanced courses like Algebraic Number Theory and Class Field Theory, with research supervision spanning PhD and undergraduate projects. Scientific Awards: Packard Fellowship for Science and Engineering National Science Foundation Waterman Award MacArthur Fellowship
Grigory Mikhalkin is a Full Professor at the University of Geneva, where he has been a faculty member since 2008. He is considered one of the founders of Tropical Geometry, a domain of algebraic geometry governed by (max,+)-calculus where geometric objects degenerate to their piecewise-linear limits. He leads the "ALGEBRA AND GEOMETRY" research group at the university. Mikhalkin studied at Leningrad and Michigan State University under the supervision of Oleg Viro and Selman Akbulut. After receiving his PhD in 1993, he completed postdoctoral training at Princeton, Bonn, Toronto, Berkeley, and Harvard (1993-2000). He served as associate and then full Professor at the University of Utah before moving to the University of Toronto, eventually joining the University of Geneva in 2008. Mikhalkin's primary research areas are Geometry and Topology, with a particular focus on Tropical Geometry. His work bridges algebraic geometry with combinatorial structures, exploring how complex geometric objects can be understood through their piecewise-linear tropical counterparts. This approach has proven fruitful in solving problems in enumerative geometry and has connections to mathematical physics through the study of sandpile models and self-organized criticality. His research group actively explores the connections between tropical geometry, symplectic geometry, and real algebraic geometry, organizing regular seminars including the "Séminaire Fables Géométriques." The recent publications of Professor Mikhalkin demonstrate a strong focus on the intersection of tropical geometry with sandpile models and self-organized criticality. His work has evolved to examine tropical aspects of number theory, lattice sums, and even applications to economics through auction theory. A significant portion of his recent research explores the patterns and structures that emerge in sandpile models across various lattices and dimensions, connecting discrete mathematics with continuum limits through tropical techniques. Prize of the St. Petersburg Mathematical Society (1999) Silver Medal of the Mexican Mathematical Society (2011) Canada Research Chair (2004-2009) Friedrich-Wilhelm-Bessel Research Award of the Alexander-von-Humboldt Foundation (2007-2008) European Research Council Advanced Grant (2010-2015) Chair of Fondation Sciences Mathématiques de Paris (2013-2015) Mikhalkin has successfully advised several PhD students to completion, including Kristin Shaw (2011), Lionel Lang (2014), Nikita Kalinin (2015), Mikhail Shkolnikov (2017), and Johannes Josi (2018). His research has been supported by prestigious grants including the ERC Advanced Grant and the Canada Research Chair. He presented his work at the Bourbaki seminar in 2003 and was selected as a Geometry speaker at the International Congress of Mathematicians in 2006, highlighting the significance of his contributions to the field. Professor Mikhalkin leads the "ALGEBRA AND GEOMETRY" research group at the University of Geneva, which includes current members Thomas Blomme, Francesca Carocci, Aloïs Demory, Gurvan Mével, and Antoine Toussaint. The group has a strong track record of postdoctoral fellows and alumni, including notable researchers such as Ivan Bazhov, Johan Bjorklund, Rémi Crétois, and others. They organize several seminars including the "Séminaire Fables Géométriques" and have historical connections to the Battelle Seminar and Tropical working group Seminar.
Jingbang Chen is a Research Assistant Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen) and holds a joint faculty position at Shenzhen Loop Area Institute (SLAI) starting September 2025. His academic journey includes a Ph.D. from the University of Waterloo, an M.S. from Georgia Institute of Technology, and a B.Eng (Honors) from Zhejiang University under the supervision of Can Wang. Education: Ph.D., Computer Science, University of Waterloo (2023-2025) M.S., Computer Science, Georgia Institute of Technology (2020-2022) B.Eng. (Honors), Pursuit Science Class, Chu Kochen Honors College (Joint Program with College of Computer Science and Technology), Zhejiang University (2016-2020) High School, Guangzhou No.2 High School (2010-2016) Dr. Chen's research focuses on the design, analysis, and implementation of provably efficient algorithms and data structures, with a particular emphasis on graph theory. He is also exploring intersections between traditional algorithm design and artificial intelligence. His work bridges theoretical computer science with practical applications in network analysis, temporal data processing, and optimization. The publication record shows a strong trajectory with papers in top venues including ICML, VLDB, KDD, and theoretical computer science conferences. Scientific Contributions: Published in premier venues including ICML 2025, VLDB 2025, KDD 2024, and multiple theoretical conferences Research spans graph algorithms, optimization techniques, network analysis, and the emerging field of learning-augmented algorithms Active contributor to the competitive programming community as both researcher and practitioner Dr. Chen is deeply involved in Competitive Programming activities, having competed in ICPC World Finals 2018 (Beijing) and 2022 (Egypt), winning regional champion titles and several gold medals. He serves as chief judge for multiple ICPC Asia regionals and coaches training camps including the North American Programming Camp (NAPC). He is also the founder and co-president of the Universal Cup, an international competitive programming contest platform. Currently, he is recruiting highly motivated PhD students with strong backgrounds in competitive programming and interest in research, collaborating with Prof. Chenhao Ma on algorithm design projects.
Henrik Jeldtoft Jensen is a Professor of Mathematical Physics and leads the Centre for Complexity Science at Imperial College London. His work spans multiple disciplines, focusing on the statistical mechanics of complex systems, with applications in physics, biology, neuroscience, and finance. Professor, Mathematical Physics Leader, Centre for Complexity Science Institution: Imperial College London His research interests lie at the intersection of theoretical physics and complex systems. He is best known for developing the Tangled Nature Model of evolving ecosystems, which has been extended into financial modeling through the Tangled Finance approach. His work in brain dynamics involves analyzing fMRI and EEG data using tools from statistical physics. He has made significant contributions to self-organized criticality and stochastic dynamics of complex systems, particularly in condensed matter and evolutionary contexts. The recent publications reflect a strong trend toward interdisciplinary complexity science, integrating concepts from physics, biology, economics, and neuroscience. Keywords across these works include complexity, statistical mechanics, dynamical systems, and network theory, with subfields ranging from neural avalanches to financial instability and biodiversity modeling. Henrik Jensen is the author of two influential books: Self-Organized Criticality and Stochastic Dynamics of Complex Systems (with Paolo Sibani), which have been widely cited across disciplines. He has supervised numerous PhD and postdoctoral researchers through the Centre for Complexity Science, though specific names are not listed. His research has been supported by grants from UK research councils and international collaborations, particularly in interdisciplinary complexity projects. He is affiliated with the Centre for Complexity Science, a multidisciplinary research hub at Imperial College London that brings together physicists, mathematicians, biologists, and social scientists to study complex adaptive systems.
Dr. Andrew McCarren is an Associate Professor and Head of the School of Computing at Dublin City University (DCU). He holds a PhD and BSc from DCU and is a funded investigator in the Insight Centre for Data Analytics. His research focuses on applying data analytics to Fintech, Agriculture, Health, and Sports Performance. As a former industry professional with 20+ years experience in Agri, Engineering, and Pharmaceuticals, he bridges academic and industrial collaboration. Professional Affiliations: Fellow of Royal Statistical Society and Advance HE Key Roles: PI on SFI/EI projects, Visiting Professor at Princess Nourah bint Abdulrahman University Research spans software engineering (microservices architecture), health informatics (exercise interventions), and agri-tech (automated food processing). Over 100 publications across data science, sports analytics, and engineering.
Christopher Hoffman is a Professor in the Department of Mathematics at the University of Washington. He holds a PhD from Stanford University (1996) and specializes in probability theory, stochastic processes, and related areas such as percolation, ergodic theory, and combinatorics. His research explores topics including activated random walks, first-passage percolation, and self-organized criticality. He teaches courses like Math 124 Calculus I and maintains active involvement in academic outreach through Google Scholar and LinkedIn. Education: PhD in Mathematics, Stanford University, 1996 Research focuses on probabilistic models with applications to statistical physics and graph theory. Key interests include analyzing phase transitions, geodesic paths in percolation models, and properties of interacting particle systems. Recent work addresses critical density thresholds in activated random walks and scaling limits of stochastic processes. Hoffman frequently collaborates on interdisciplinary projects involving combinatorics and ergodic theory. Teaching responsibilities include foundational calculus courses and maintaining detailed lecture notes for students. His work has been supported by grants from the National Science Foundation and other institutions.
Professor Peter Grassberger is a distinguished researcher at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre, one of Germany's leading national research institutions. His work spans multiple decades in theoretical physics and computational science, with a particular focus on complex systems and statistical mechanics. His research has significantly advanced our understanding of critical phenomena and phase transitions in various physical systems. Grassberger's research interests center around statistical physics and complex systems, with specializations in percolation theory, self-organized criticality, and random walk models. His work explores the universal properties of phase transitions, critical phenomena, and the behavior of complex networks. His theoretical contributions have provided fundamental insights into how simple local rules can lead to complex global behavior in physical systems. His recent work continues to push boundaries in understanding extreme-value statistics, entropy estimation methods, and the dynamics of interface models. Through his extensive publication record spanning over 40 years, Grassberger has established himself as a leading authority in computational statistical physics. His work shows consistent focus on understanding universal properties of critical systems while developing innovative computational methods to analyze complex phenomena. His research bridges theoretical physics with practical computational approaches, making significant contributions to both fundamental understanding and methodological development in the field. Grassberger's scientific impact is evident through his numerous influential publications and his development of important computational techniques like the Grassberger-Procaccia algorithm for estimating fractal dimensions. His work on self-organized criticality, particularly his 2022 review "Self-Organized Criticality, Three Decades Later," demonstrates his enduring contribution to this important field. His recent publications continue to explore cutting-edge questions in statistical physics, showing active engagement with contemporary research challenges.
Jason Smith is a Senior Lecturer in Mathematics at the Department of Physics and Mathematics, Nottingham Trent University. His work bridges pure mathematics and neuroscience, focusing on combinatorial and topological methods for analyzing brain networks and functional data. His educational background includes: PhD in Computer and Information Science, University of Strathclyde (2015) MMath, University of Bath (2012) His research lies at the intersection of combinatorics, topology, and neuroscience. He applies tools from graph theory, topological data analysis (TDA), and algebraic topology to study the structure and function of neural systems. Key areas include the analysis of connectomes (such as C. Elegans and Drosophila), modeling brain network dynamics, and developing theoretical frameworks for understanding neural coding through combinatorial and topological lenses. His work often involves collaborations with neuroscientists and computational biologists. His recent publications demonstrate a strong trend toward interdisciplinary research, combining deep mathematical theory with applications in neuroscience. The articles span topics from the topology of directed flag complexes and tournaplexes to the combinatorics of permutation patterns and the Abelian sandpile model, all unified by their relevance to understanding complex biological networks. There is a clear progression from theoretical combinatorics toward computational and applied neurotopology. He has collaborated extensively with researchers from the University of Aberdeen, EPFL (including the Laboratory for Topology and Neuroscience and the Blue Brain Project), and other institutions. He has developed several open-source software tools such as Flagser-count, Tournser, and Deltser for computing persistent homology in directed networks, reflecting his commitment to computational reproducibility and tool development. He has presented his work in various venues, with talks and posters on topics including permutation posets, tournaplexes, and functional brain data classification. His research is supported by collaborative projects focusing on the topological analysis of neural systems and the mathematical foundations of pattern posets.
Ecaterina Sava-Huss is a Full Professor in Mathematics at the University of Innsbruck, Austria, affiliated with the Department of Mathematics within the Faculty of Mathematics, Computer Science and Physics. She holds a PhD from Graz University of Technology (2010) and a Habilitation in Mathematics (2019). Previously, she served as an associate professor and tenure-track assistant professor at the University of Innsbruck, and as an assistant professor and visiting scholar at institutions including TU Graz and Cornell University. Her research focuses on stochastic processes, particularly random walks and rotor walks on graphs, fractals, and aggregation models. Key interests include the interplay between structural properties of infinite state spaces and stochastic processes. She has organized conferences such as the Austrian Stochastics Days and is the outreach coordinator for the Institute of Mathematics, engaging in public science initiatives like the MIP Day and Girls' Day. Her funding includes an FWF Grant P34129 (2021–2025) on growth models and quasi-random walks, and a prior Erwin Schrödinger Fellowship (2015–2016). She has supervised numerous PhD and Master’s students, with research topics ranging from branching processes to quantum probability. Her work has been published in journals such as Advances in Applied Probability , Bernoulli , and Journal of Fractal Geometry .
Luis Sanchez Fernandez is a Full Professor at the Department of Telematics Engineering, Carlos III University of Madrid. His research focuses span Smart Cities, Semantic Web, and Distributed Systems. Contact information includes email luis.sanchez@uc3m.es and office location 4.1.F08 in Leganés. His research program integrates Blockchain Governance , Urban Mobility Analysis , and Complex Systems Modeling . Recent work examines approval-based voting mechanisms in decentralized networks and fractional transport equations for physical simulations. Publications demonstrate a strong emphasis on fair algorithm design for societal applications. Key article themes show convergence of Smart City Data Integration Multiwinner Election Algorithms Cellular Automaton Dynamics Semantic Annotation Frameworks As Deputy Director of Teaching Affairs, he leads curriculum innovation in Telematics Engineering. His educational background includes a Doctorate from Universidad de Salamanca, focusing on Wikipedia as a teaching resource in higher education.
Ari Shnidman is an Associate Professor in Mathematics at the Hebrew University of Jerusalem. For the 2024/25 academic year, he is a member of the Institute for Advanced Study in Princeton. His research focuses on number theory, particularly arithmetic geometry, special values of L-functions, and arithmetic statistics. Research Interests: Shnidman investigates deep connections between algebraic curves, abelian varieties, and L-functions. His work spans Tate-Shafarevich groups, Ceresa cycles, Heegner cycles, and rank distribution in elliptic curves. Key methodologies include algebraic geometry, representation theory, and computational number theory. Publications: Recent papers explore Ceresa cycles, torsion in Tate-Shafarevich groups, and arithmetic of curves like Picard curves. Collaborative work dominates his output, with frequent co-authorship on papers involving elliptic curves, L-functions, and geometric invariants. Theoretical frameworks are often complemented by computational experiments. Funding: European Research Council Israel Science Foundation Academic Leadership: Shnidman co-organizes the HUJI-BGU Workshop in Arithmetic and leads seminars including: Lunch Seminar on Transcendental Number Theory (Spring 2024) Seminar on Honda-Tate Theory (Spring 2023) Fundamental Lemmas and Fourier Transform Seminar (Spring 2021)
