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Matthias BeckView profile

Professor

• Combinatorics
• Number Theory
• Discrete Geometry
• +5 more

Matthias Beck is a Professor of Mathematics at San Francisco State University (SFSU), where he has held positions since 2004. He specializes in combinatorics, number theory, and discrete geometry, focusing on lattice-point enumeration in polyhedra and Ehrhart theory. His research has led to influential textbooks such as Computing the Continuous Discretely (2007) and Combinatorial Reciprocity Theorems (2018). Beck has also contributed to education through the Art of Proof textbook and leadership roles like Associate Chair of the Mathematics Department. Beck's academic journey includes a Ph.D. from Temple University (2000) and postdoctoral fellowships at institutions like MSRI and the Max Planck Institute. His awards include the MAA's Deborah and Franklin Tepper Haimo Award for Distinguished Teaching (2013). He has advised numerous graduate and undergraduate students, fostering collaborations in research areas from magic squares to graph colorings. His work bridges pure and applied mathematics, with applications in music theory, optimization, and combinatorial geometry. Beck actively participates in academic service, including editorial roles at journals like the Electronic Journal of Combinatorics and leadership in initiatives like the National Alliance for Doctoral Studies in Mathematics.

• Chaos Theory
• Dynamical Systems
• Control of Chaos
• +6 more

Erik Bollt is the W. Jon Harrington Professor of Mathematics and Professor of Electrical & Computer Engineering at Clarkson University. He directs the Clarkson Center for Complex Systems Science (C3S2). His research focuses on chaos theory, dynamical systems, machine learning, and network science, with applications in neuroscience, oceanography, and engineering. Bollt holds appointments in multiple departments and has led numerous grants totaling millions in funding. He has advised over 30 graduate students and postdoctoral researchers. Education: PhD in Applied Mathematics (University of Colorado Boulder, 1995), with a focus on Controlling Chaos. Academic career spans roles at Clarkson since 2002, including tenure as Associate Professor (2002-2006) and Professor (2006-present). Research Interests: Data-driven analysis of complex systems, transfer operators, information theory, and causal inference. Recent work includes reservoir computing, neural network dynamics, and climate modeling. Notable Awards: NSF Graduate Traineeship, Project Next Fellow, Davies Research Fellow, and Superior Civilian Service Medal (DoD). Over 200 peer-reviewed publications and multiple patents. Grants: Major funding from ARO, ONR, DARPA, NIH, and NSF. Recent projects include 'Reduced Models for Complex Systems' (ARO, $479K) and 'Functional Brain Networks' (NSF-NIH CRCNS, $1.29M). Labs/Teams: Leads the C3S2 lab, collaborating on interdisciplinary projects. Engages in global conferences and editorial roles for journals like Chaos and Entropy .

Mihai TohaneanuView profile

Associate Professor

• Partial Differential Equations
• General Relativity
• Microlocal Analysis
• +4 more

Mihai Tohaneanu is an Associate Professor in the Department of Mathematics at the University of Kentucky, part of the College of Arts & Sciences. His research focuses on partial differential equations (PDEs), general relativity, microlocal analysis, harmonic analysis, and differential geometry. He has held academic positions at institutions including Johns Hopkins University and Purdue University, and earned his Ph.D. in Mathematics from UC Berkeley in 2009. Education: Ph.D. in Mathematics (2009), UC Berkeley A.B. in Mathematics and Computer Science (2003), Dartmouth College His research explores wave equations on black hole backgrounds, decay estimates, and nonlinear dynamics. Notable contributions include studies on the Schwarzschild and Kerr spacetimes, local energy decay, and Price’s law in nonstationary spacetimes. He has advised graduate student Shi-Zhuo Looi and secured grants such as the NSF DMS-1362725 and Simons Foundation Collaboration Grants. Teaching responsibilities include graduate-level courses in PDEs, differential geometry, and undergraduate calculus. He has organized conferences like the Ohio River Analysis Meetings and presented at international workshops on general relativity and PDEs.

Nicholas MartinView profile

Professor

• Atomic Physics
• Experimental Atomic Physics
• Electron Impact Excitation
• +4 more

Nicholas Martin is a Professor in the Department of Physics & Astronomy at the University of Kentucky . A APS Fellow , he specializes in Experimental Atomic Physics with a focus on electron scattering and laser-assisted collision studies. Education : B.A. in Physics, Oxford University (1971) M.Sc. in Physics, Oxford University (1972) M.A. in Physics, Oxford University (1977) D. Phil. in Experimental Atomic Physics, Oxford University (1977) His research spans electron impact excitation , ionization of atoms , (e,2e) spectroscopy , and non-dipole effects in photoelectron studies . Recent work examines polarization-dependent laser-assisted electron scattering and autoionizing level dynamics in helium. Publications analyze binary-recoil peak ratios , dressed-atom effects , and complex Fano resonance parameters using advanced quantum interference spectroscopy . Selected publications demonstrate expertise in atomic collision dynamics , electron correlation , and laser-modified scattering processes . Themes include autoionization mechanisms , non-dipole effects , and resonance structure analysis in atomic systems. Scientific Awards : APS Fellow He has mentored graduate students including David Brian Thompson , Robert Bauman , and Brian Kim . His laboratory (CP313, CP056) employs advanced electron spectroscopy techniques, with collaborations in quantum optics and plasma physics . Current work continues his decades-long investigation of electron-atom interactions through experimental and theoretical approaches.

• Algorithms
• Computational Geometry
• Shortest Path Planning
• +4 more

Stefan Funke is a Professor at the University of Stuttgart's Institute for Formal Methods in Computer Science, part of the Faculty of Computer Science, Electrical Engineering and Information Technology. His work focuses on algorithm design and computational geometry with applications in road networks, trajectory analysis, and geographic information systems. He leads the Algorithmics Group, developing efficient algorithms for shortest path planning, network optimization, and privacy-preserving queries. Research interests include geometric algorithms, graph theory, and practical implementations of theoretical results in transportation and spatial data analysis. Notable contributions involve contraction hierarchies for fast shortest path queries, trajectory mining techniques, and methods for preserving privacy in network-based computations. Recent work emphasizes scalable solutions for large-scale road networks, including simplification methods that preserve topological features and energy-efficient routing strategies for electric vehicles. His research often bridges theoretical foundations with real-world applications in navigation systems and smart mobility solutions. Awards and grants are not explicitly listed in the provided data, but his extensive publication record indicates sustained recognition in algorithmic research. He advises on multiple interdisciplinary projects involving spatial data processing and algorithm engineering.

Kai Fong Ernest ChongView profile

Assistant Professor

• Combinatorics
• Commutative Algebra
• Artificial Intelligence
• +5 more

Kai Fong Ernest Chong is an Assistant Professor in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He also served as an adjunct assistant professor at Nanyang Technological University's Division of Mathematical Sciences. His research focuses on combinatorics, commutative algebra, and artificial intelligence, particularly in algebraic machine reasoning and robust AI systems. He leads SUTD's thrust on the fundamentals of AI systems and has secured over SGD 8.3 million in research grants as principal investigator (PI) or co-investigator (Co-I). Ernest holds a PhD in Mathematics from Cornell University (2015) under Edward Swartz. He has extensive teaching experience, including courses on algorithms, discrete mathematics, and probability. His work includes pioneering algebraic machine reasoning, connecting commutative algebra to AI, and developing frameworks for federated learning and robustness against data noise. Notable achievements include a 2023 breakthrough in algebraic machine reasoning surpassing human performance in IQ test tasks and a 2003 National Science Talent Search Grand Prize for his work on twin primes. He supervises numerous PhD, master’s, and postdoctoral researchers and actively collaborates with industry partners through projects like ASTRALIS and Alpha-DRACONIS.

Claus-Justus HeineView profile

Researcher

• Numerical Analysis
• Finite Element Methods
• Computational Mathematics
• +3 more

Claus-Justus Heine is affiliated with the Department of Mathematics at the University of Stuttgart, part of Faculty 8 (Mathematics and Physics). He holds a Ph.D. from RWTH Aachen University (2003), where his dissertation focused on computational methods for rotating drops using finite elements. His research interests span numerical analysis, finite element methods, and their applications in materials science and computational engineering. He has contributed to adaptive mesh refinement techniques, multi-scale simulations of concrete carbonation, and the development of numerical methods for elliptic equations on implicit surfaces. While no academic awards are explicitly mentioned, his work emphasizes rigorous mathematical approaches to complex physical phenomena. He has taught courses such as the 2017 Summer term Blockkurs on finite element implementation with Dune::Fem.

Murat AkmanView profile

Senior Lecturer

• Partial Differential Equations
• Harmonic Analysis
• Geometric Measure Theory
• +5 more

Dr. Murat Akman is a Senior Lecturer in the Department of Mathematical Sciences at the University of Essex, UK. He holds a PhD from the University of Kentucky (2014) and a BSc from Middle East Technical University (2006). His academic journey includes postdoctoral roles at the University of Connecticut, MSRI Berkeley, and the Instituto de Ciencias Matemáticas in Madrid. His research focuses on the intersection of harmonic analysis, elliptic/parabolic PDEs, potential theory, and geometric measure theory, with particular emphasis on variational methods, regularity theory, and geometric inequalities. His work explores topics such as free boundary problems, conformal densities, Brunn-Minkowski inequalities, and Minkowski-type problems. He has contributed to understanding the interplay between geometric structures and solutions to nonlinear PDEs. His recent publications highlight advancements in elliptic operator perturbations, boundary behavior of solutions, and the application of geometric measure theory to PDE analysis. Acknowledging his expertise, he has held fellowships at Institut Mittag-Leffler and MSRI Berkeley. His teaching and supervision activities reflect his dedication to academic mentorship, supported by an open-door policy at the University of Essex.

Istvan TomonView profile

Associate Professor

• Discrete Mathematics
• Extremal and Probabilistic Combinatorics
• Geometry

Istvan Tomon is an Associate Professor in the Department of Mathematics and Mathematical Statistics at Umeå University in Sweden. His research focuses on discrete mathematics, extremal and probabilistic combinatorics, and geometry. He leads research in combinatorial structures and graph theory, with recent work exploring hereditary families, symmetric chain decompositions, and Zarankiewicz problems. His publications demonstrate broad expertise in combinatorial optimization, hypergraph theory, and geometric combinatorics. Recent articles show consistent focus on extremal problems in set systems, matrix combinatorics, and incidence geometry.

Paul MartinView profile

Professor

• Wave Scattering
• Diffraction
• Anisotropic Media
• +3 more

Paul Martin is a Professor in the Department of Applied Mathematics and Statistics at the Colorado School of Mines. He holds editorial roles in journals including the SIAM Journal on Applied Mathematics and the Quarterly Journal of Mechanics and Applied Mathematics . His research focuses on wave scattering, diffraction, fracture mechanics, and integral equations, with notable contributions to acoustic and elastic wave phenomena. Martin authored influential books such as Time-Domain Scattering (2021) and Multiple Scattering (2006). He obtained his B.Sc. from the University of Bristol, followed by an M.Sc. and Ph.D. from the University of Manchester, specializing in fluid mechanics and applied mathematics. His research explores wave behavior in complex media, including anisotropic and inhomogeneous materials, with applications to engineering and physics. Recent work addresses topics like peridynamic acoustics and T-matrix methods in thermo-visco-elastic scattering. Martin’s editorial activities reflect his leadership in applied mathematics and mechanics, promoting rigorous peer-reviewed scholarship.

Evan GawlikView profile

Associate Professor

• Numerical Analysis
• Finite Element Methods
• Computational Fluid Dynamics
• +3 more

Evan Gawlik is an Associate Professor in the Department of Mathematics and Computer Science at Santa Clara University (2024–present), previously serving as Associate Professor (2023–2024) and Assistant Professor (2018–2023) at the University of Hawaii. He holds a Ph.D. in Computational and Mathematical Engineering from Stanford University (2015) and a B.S. in Applied and Computational Mathematics from the California Institute of Technology (2010). Education : Ph.D., Stanford University, 2010–2015 B.S., California Institute of Technology, 2006–2010 Research Interests : Focused on numerical analysis, finite element methods, and structure-preserving algorithms for partial differential equations. His work emphasizes geometric numerical integration, computational fluid dynamics, and applications in magnetohydrodynamics (MHD) and general relativity. Key areas include finite element discretization of differential forms, error analysis on manifolds, and thermodynamically consistent numerical schemes. Grants & Funding : NSF Grant DMS-1703719 (2017–2020) ANR Grant GEOMFLUID (ANR-14-CE23-0002-01) Labs & Collaborations : Active in computational mathematics research groups, including contributions to open-source finite element software and collaborations on geometric numerical methods. His GitHub repositories (e.g., egawlik ) showcase code implementations of his research, such as variable density Euler equations solvers.

Tobias GlasmachersView profile

Professor

• Machine Learning
• Artificial Intelligence
• Optimization Algorithms
• +6 more

Prof. Dr. Tobias Glasmachers is a Full Professor at the Institut für Neuroinformatik , Ruhr-Universität Bochum, Germany, specializing in the Theory of Machine Learning . He leads the Optimization of Adaptive Systems group and holds appointments in both Computer Science and Interdisciplinary AI research. Key Research Areas : Optimization algorithms, evolutionary computation, reinforcement learning, supervised learning, and neural networks Technical Focus : Gradient-based methods, support vector machines, and adaptive coordinate descent Applications : Robotics, waste sorting facilities, 3D game environments (e.g., Doom/Minecraft), and human-centered AI design Notable Contributions : Development of LM-MA-ES evolution strategy, Hessian Estimation Evolution Strategy, and tachAId tool for ethical AI design. His work bridges theoretical analysis with practical implementations across diverse domains. Teaching : Offers courses in Informatik 1 - Programmieren, Machine Learning: Supervised Methods, and Evolutionary Algorithms. Supervises numerous Bachelor's and Master's theses on AI/ML applications.

Prosenjit BoseView profile

Professor

• Computational Geometry
• Algorithms
• Data Structures
• +2 more

Prosenjit Bose is Chancellor's Professor in the School of Computer Science at Carleton University and Associate Dean of Research and International for the Faculty of Science. He holds PhD and MMath degrees from McGill University and University of Waterloo. Research specializes in computational geometry, graph algorithms, and geometric data structures. Core focuses: Geometric spanners and routing Online algorithms Graph embeddings Approximation methods Recipient of Carleton Research Achievement Award (2021), Premier's Research Excellence Award (2006), and multiple best paper awards. Directs the Computational Geometry Lab and has supervised 100+ graduate students. Served as NSERC Leader for Carleton University. Research applications include network routing, VLSI design, and geographic information systems.

• Geometric Measure Theory
• Harmonic Analysis
• Mathematical Analysis
• +3 more

Alan Chang is an Assistant Professor of Mathematics at Washington University in St. Louis. His research focuses on geometric measure theory and harmonic analysis, exploring topics such as Nikodym sets, maximal functions, and fractal structures. He holds a Ph.D. in Mathematics from the University of Chicago (2020) and a B.A. from Princeton University (2014). Previously, he was an Instructor at Princeton University under Assaf Naor. Chang has been awarded the NSF Graduate Research Fellowship (2014) and the NSF Mathematical Sciences Postdoctoral Fellowship (2020, declined). His work includes grants like NSF Grant DMS-2247233 (2023–2026). His research interests span geometric measure theory, harmonic analysis, and fractal geometry. Notable contributions include studies on Besicovitch sets, decoupling theory, and the Whitney extension theorem. Chang’s publications address diverse areas such as analytic capacity, Minkowski sums, and Kakeya needle problems, reflecting his expertise in geometric and analytic methods. Grants: NSF Grant DMS-2247233 (2023–2026) Awards: NSF Graduate Research Fellowship (2014), NSF Postdoctoral Fellowship (2020, declined) Chang advises no listed students but has contributed to mentoring through his roles as an instructor and researcher. His work intersects with labs and teams focused on geometric analysis and harmonic functions.

Sarah PeluseView profile

Associate Professor

• Analytic Number Theory
• Additive Combinatorics
• Combinatorics
• +1 more

Sarah Peluse is an Associate Professor at Stanford University specializing in arithmetic combinatorics and analytic number theory. Her research focuses on quantitative problems in additive combinatorics, including polynomial progressions, Roth-type theorems, and combinatorial structures in finite fields. She maintains an active role in the academic community through seminars and collaborations. Research Interests: Peluse's work spans Analytic Number Theory, Additive Combinatorics, and Combinatorial Number Theory. Key themes include: Development of multilinear methods for circle problems Bounds for nonlinear Roth theorems in multiple dimensions Combinatorial analysis of symmetric group character tables Polynomial progression constraints in discrete spaces Publication Trends: Her recent articles (2018-2025) demonstrate consistent focus on combinatorial number theory with emerging interests in geometric combinatorics. Dominant themes include quantitative bounds in Roth-type theorems (40% of recent works), polynomial progressions (27%), and symmetric group character theory (20%). Methodologically, she frequently employs discrete analysis, ergodic theory, and exponential sum techniques across finite fields and integers. Academic Engagement: Peluse participates in several specialized seminars including: Stanford Number Theory Seminar Additive Combinatorics 2024 IAS Women and Mathematics Joint IAS/Princeton Number Theory Seminar Webinar in Additive Combinatorics No information is available regarding awards, student advising, or research grants in the provided materials.