Mariusz Mirek is an Associate Professor at Rutgers University's Department of Mathematics and a full Professor at the University of Wrocław's Mathematical Institute. He holds a PhD from the University of Wrocław (2011) and habilitation degrees from the University of Bonn (2016) and Wrocław (2017). His research focuses on convergence phenomena in analysis and ergodic theory, interacting with Fourier analysis, number theory, additive combinatorics, and probability. Recently, he explores high-dimensional effects and dimension-free estimates in convex geometry. He has held visiting positions at the Institute for Advanced Study (IAS) in Princeton during 2016/2017 and 2022/2023. His research is supported by NSF grants DMS-2154712 (2022-2025) and DMS-2236493 (2023-2028). He organizes the ETA(η) Ergodic Theory & Analysis Seminar (online via Zoom) and co-organizes the Current Trends in Mathematics workshop at Rutgers' DIMACS (June 2024). His work spans 70+ publications, emphasizing maximal functions, ergodic theorems, polynomial averages, and stochastic processes. Key contributions include dimension-free estimates for discrete operators and applications to additive number theory.
Julian Chaidez is an Assistant Professor of Mathematics at the University of Southern California (USC) in Los Angeles. His research focuses on smooth dynamical systems, symplectic topology, and symplectic field theory (SFT). He completed his PhD at UC Berkeley in 2021 under Michael Hutchings, followed by postdoctoral fellowships at Princeton University/IAS (2021-2023) and UCLA (2021 as UC President's Fellow). He teaches advanced graduate courses such as Math 641 (Floer Theory) and Math 540 (Algebraic Topology) at USC. Previously taught courses include UC Berkeley's Math 16B, Math 53, and symplectic topology seminars. Active in organizing academic events like the USC Topology Seminar and co-organizing reading groups on monopole Floer homology. Research interests include contact homology, Reeb dynamics, symplectic capacities, and applications to geometric topology. Collaborates with researchers like Oliver Edtmair, Ben Wormleighton, and Shira Tanny on projects involving SFT spectral gaps, convex contact forms, and non-semisimple invariants of 4-manifolds.
Olaf Lechtenfeld is a Professor at the Institute of Theoretical Physics, Leibniz University Hannover, within the Faculty of Mathematics and Physics. His research focuses on mathematical physics, string theory, quantum field theory, and integrable systems. He leads the Lechtenfeld Working Group, which explores topics like supersymmetric sigma models, Nicolai maps, and geometric aspects of field theories. He has advised multiple PhD and Master’s students, including Federico Arrighi, Fin Müller, and Simeon Rehra. Key projects include contributions to the Riemann Center for Geometry and Physics and involvement in the Saalburg WE-Heraeus Summer School. His work spans peer-reviewed articles in top journals like Phys. Lett. B and JHEP , addressing themes such as Yang-Mills solutions, Calogero models, and supermembrane theories. Lechtenfeld’s affiliations include administrative roles at the Institute and collaborations on international projects. His research often bridges algebraic structures and physical phenomena, with a focus on exact solutions and non-perturbative methods. Notable recent work includes studies on Nicolai maps in supersymmetric theories and applications of geometric techniques to gauge theories. Education: Doctorate in Theoretical Physics (university unspecified). Research Teams: Lechtenfeld Working Group, Riemann Center for Geometry and Physics. Grants: Ongoing projects in string theory and quantum field theory.
Shuyan Li is a Lecturer at the School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast. Her research focuses on foundational computer vision methods and their healthcare applications, including unsupervised learning, multi-modal learning, and medical imaging analysis. She actively mentors early-career researchers through the Cambridge Trinity College Postdoctoral Mentorship Program and serves as Director of the Tsinghua Alumni Association (UK) and Secretary-General of the UK Association of Distinguished Young Scholars. Education Background: While specific degree details are not explicitly listed, Dr. Li has received prestigious awards such as the First Prize Scholarship (Tsinghua University, 2020) and the National Scholarship (Ministry of Education, PRC, 2013), indicating a strong academic foundation. Research Interests: Central themes include unsupervised learning, digital twins for construction and healthcare, video understanding, representation learning, and domain adaptation. Her work bridges theoretical advancements and practical applications, such as medical image translation and point cloud-based building digitization. Awards and Recognition: Key achievements include the Athena Postdoctoral Fellowship (NSF AI Research Center), Forbes’ Top 100 Most Influential Chinese (2024), and the Excellent Doctorate Dissertation Award (2023). She is also a Guest Editor for Innovation and Technology of Computer Vision . Advising & Grants: Currently supervising PhD students Ben Redden (UK) and Shurui Xu (China). She offers multiple funded PhD opportunities, including EPSRC and CSC scholarships, and collaborates with institutions like Cambridge and UCL. Labs & Collaborations: Active in interdisciplinary projects involving digital twin construction, medical AI, and point cloud analysis. Recent collaborations include work with the University of Cambridge on digital construction modules and Newcastle University on AI-driven data analysis.
Thomas Neubauer is a researcher affiliated with TU Wien's Department of E-Commerce, part of the Faculty of Informatics. He holds the title of Researcher and is actively involved in projects such as the 'Digitisation and Innovation Laboratory in Agricultural Sciences,' serving as Principle Investigator. His work focuses on applying artificial intelligence, digital twins, and machine learning to address challenges in sustainable agriculture and environmental systems. Neubauer has contributed to over 97 publications, emphasizing topics like precision farming, energy-efficient agrivoltaic systems, and predictive modeling in complex agricultural data. Education details aren't explicitly listed, but his academic titles include Dipl.-Ing. (Master of Engineering), Mag. (Magister), and Dr.techn. (Doctor of Technical Sciences). His research interests span digital agriculture, AI-driven crop management, and the integration of chaos theory with machine learning. Notable projects include exploring digital twin applications for grassland management and photovoltaic integration in farming systems. Neubauer has advised students such as Sebastian Raubitzek, Anja Klipic, and Enri Miho on theses related to digital twins and AI in agriculture. His work frequently intersects with sustainability goals, including reducing environmental impacts through technological innovation. He collaborates on interdisciplinary teams focused on energy resilience and precision livestock farming, leveraging explainable AI techniques to enhance decision-making in agricultural contexts.
William L. Pardon is a Professor in the Department of Mathematics at Duke University. He holds a B.A. from the University of Michigan and a Ph.D. from Princeton University. His research focuses on the Algebra and Geometry of Varieties, with particular emphasis on topics such as Hodge structures, Chern classes, and cohomological studies of singular varieties. His recent work includes studies on modular varieties, Hodge theory in singular spaces, and filtered resolutions in algebraic geometry. Though no specific awards or grants are listed, his contributions to geometric and algebraic research are evident through his publications. Teaching includes advanced mathematics courses such as Math 221. No current students or labs are mentioned in the provided data.
Ruhan Zhao is a Distinguished Professor in the Department of Mathematics at the State University of New York at Brockport. He holds a PhD in Mathematics from the University of Joensuu, Finland (now University of Eastern Finland). His research focuses on Complex Analysis and Operator Theory, with particular emphasis on Bergman spaces, Toeplitz operators, integral operators, and function spaces. His work often explores the interplay between operator properties and functional analytic structures. Dr. Zhao has published extensively on topics such as weighted composition operators, Carleson measures, and embedding theorems in spaces of analytic functions. Recent research includes studies on Berezin-type operators, Schur’s test applications, and Fredholm properties in operator theory. His contributions span functional analysis, harmonic analysis, and operator theory, with over 80 peer-reviewed articles in mathematics journals. His expertise is reflected in his 2008 monograph "Theory of Bergman spaces in the unit ball of ℂn" , which remains a key reference in the field. Despite no explicit mention of awards/grants in the provided text, his prolific publication record and focus on foundational operator theory suggest significant academic recognition. Teaching responsibilities include advanced mathematics courses at the undergraduate/graduate level, though specific advising details are not documented here. His office is located in Brown Building 142, and further information can be found on his institutional webpage.
Franca Hoffmann is an Assistant Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech), and an International Scientific Advisor at Quantum Leap Africa (QLA) at the African Institute for Mathematical Sciences (AIMS). Previously, she held positions including a Bonn Junior Fellow at the Hausdorff Center for Mathematics and the AIMS-Carnegie Research Chair in Data Science. She leads the Doctoral Training Program in Data Science at QLA in Rwanda. Education : B.S. (Imperial College London, 2010), M.S. (2013), Ph.D. (University of Cambridge, 2017). Her thesis focused on partial differential equations and their applications, honored with the 2016 Imperial College Outstanding Student Achievement Award. Research Interests : Interface of model-driven and data-driven approaches, including PDE analysis (nonlinear drift-diffusion equations, kinetic theory, optimal transport) and data analysis (inverse problems, Bayesian inference, clustering algorithms). Her work bridges theoretical foundations with applications in mechanics, social sciences, and machine learning. Teaching : Courses include Environmental Physical Organic Chemistry and Special Topics in Applied Mathematics at Caltech. She has organized workshops and conferences globally, emphasizing capacity-building in African mathematical sciences. Awards : 2016 Imperial College Outstanding Student Achievement Award. Labs/Teams : Leads the DTP-DS at QLA and co-organizes initiatives like the Young African Mathematicians Bonn Visitor Program. Active in promoting interdisciplinary education and outreach in Africa.
René Langøen is a PhD Candidate and Researcher at the Department of Mathematics, University of Bergen. His work bridges mathematical physics and differential geometry, with a focus on geometric structures in physical systems. Affiliation: Department of Mathematics, University of Bergen Research Interests: His research explores integrable systems through differential geometry and complex analysis. Key areas include curvature properties of diffeomorphism groups on non-orientable manifolds (e.g., Klein bottle, projective plane), Stokes graphs in the Rabi model, and applications to quantum mechanics and fluid dynamics. Recent Trends: Recent publications analyze geometric properties of non-orientable surfaces and Stokes phenomena in quantum systems, reflecting interdisciplinary work at the intersection of pure mathematics and theoretical physics. Teaching & Outreach: Active in education, he has taught courses like MAT101 and MAT121, and organized conferences such as the Norwegian National PhD Meeting in Mathematics (2023). Outreach includes public lectures and poster sessions on geometric analysis.
Bozhidar Velichkov is a Full Professor at the Department of Mathematics, University of Pisa, where he has been working since June 2020. Previously, he served as an Associate Professor at Università di Napoli Federico II (2019-2020) and at Université Grenoble Alpes (2014-2019). He is the Principal Investigator of the ERC VaReg project (2020-2025), a European Research Council Starting Grant focused on the regularity of free boundaries. His educational background includes PhD studies at Scuola Normale Superiore (2010-2013) and undergraduate studies at both Scuola Normale Superiore and University of Pisa (2005-2010). Professor Velichkov's research focuses on Calculus of Variations and Partial Differential Equations , with particular emphasis on Regularity Theory and Free Boundary Problems . His work investigates the fine structure of solutions to variational and PDE problems, especially concerning the regularity of free boundaries in various contexts including one-phase and two-phase Bernoulli problems, obstacle problems, and vectorial free boundary systems. His approach often involves developing new techniques such as epiperimetric inequalities and monotonicity formulas to analyze the structure of solutions near singularities. His recent publications demonstrate a strong trend toward understanding the regularity of free boundaries in increasingly complex settings, including capillarity problems, thin obstacle problems, and vectorial systems. His work bridges geometric analysis, PDE theory, and calculus of variations, with applications to shape optimization and geometric variational problems. Principal Investigator of ERC VaReg project (2020-2025) Deputy Coordinator of PhD program in Mathematics at University of Pisa Organizer of multiple international workshops on Free Boundary Problems Professor Velichkov has supervised numerous PhD students and post-doctoral researchers, leading an active research group focused on free boundary regularity. His ERC project supports a vibrant team of researchers working on cutting-edge problems in geometric analysis and partial differential equations.
Daniel Peralta-Salas is a CSIC Research Professor and Chair of the Group 'Differential Geometry and Geometric Mechanics' at the Institute of Mathematical Sciences (ICMAT) in Madrid, Spain. ICMAT is a joint research institute of the Spanish National Research Council (CSIC) and several Madrid universities. He is an active researcher with leadership roles in the ICMAT board and multiple international advisory boards. PhD in Mathematics, Universidad Complutense de Madrid, 2006 His research lies at the intersection of dynamical systems , partial differential equations , and differential geometry , with applications in fluid mechanics, plasma physics, quantum mechanics, and mathematical physics. He has developed a unifying theory to study geometrically complex structures in physical models. His work includes proving long-standing conjectures by Arnold, Lord Kelvin, and Michael Berry, and constructing fluid flows that simulate universal Turing machines, thereby demonstrating undecidable dynamics in fluid particle paths. The most recent articles highlight his ongoing focus on steady Euler flows , topological obstructions in magnetic fields , optimal eigenvalue problems , and Turing universality in fluid dynamics . His publications span geometric analysis, spectral theory, and mathematical physics, often combining deep topological insight with PDE techniques. He has developed novel methods such as global approximation and inverse localization, which have broad implications across mathematical physics. His scientific awards include: ERC Starting Grant (2014–2019) Barcelona Dynamical Systems Prize (2015) Plenary Speaker, European Congress of Mathematics (2016) The Floer Lectures (2019) MINT Distinguished Lectures, Tel Aviv (2020) Plenary Speaker at major national and international mathematical societies (2021–2024) EMS Distinguished Speaker (2023) Peralta-Salas advises and collaborates extensively with researchers including Alberto Enciso, Robert Cardona, Eva Miranda, and others. His work has been supported by prestigious grants such as the ERC Starting Grant. He has published over 100 papers in top journals including Annals of Mathematics , Acta Mathematica , PNAS , and Physical Review Letters . He is a member of editorial boards for journals such as Revista Matemática Iberoamericana and Journal of Dynamics and Differential Equations , and serves on the scientific advisory board of IMTECH (UPC-Barcelona Tech). He leads the research group on Differential Geometry and Geometric Mechanics at ICMAT, which focuses on geometric structures in dynamical systems and PDEs. The group explores topics like Beltrami fields, vortex dynamics, and topological aspects of eigenfunctions. Their work is highly collaborative and interdisciplinary, bridging pure mathematics and theoretical physics.
Dr. Martin Bohner is the Curators' Distinguished Professor in the Department of Mathematics and Statistics at Missouri University of Science and Technology. He is a leading expert in difference equations and dynamic equations on time scales, with extensive contributions to mathematical analysis and applied mathematics. University: Missouri University of Science and Technology Department: Department of Mathematics and Statistics Academic Rank: Professor His research interests include difference equations, dynamic equations on time scales, oscillation theory, stability analysis, and interdisciplinary applications in biology and economics. He has pioneered the unification of continuous and discrete analysis through time scales calculus, influencing both theoretical and applied domains. The recent publications highlight a sustained focus on qualitative behavior of dynamic equations, nonlinear systems, boundary value problems, and applications across disciplines. His work consistently bridges pure mathematical theory with real-world modeling challenges. President of the International Society of Difference Equations (ISDE), 2017–2019 Curators' Distinguished Professor Recognized among the top 2% most cited scientists globally (2021–2024) Dr. Bohner has advised numerous graduate students and collaborates widely across international institutions. He has secured significant research recognition and leadership roles. He is actively involved in organizing conferences and editorial work, including founding and editing major journals in his field. He leads research initiatives connecting dynamic modeling with practical systems in engineering and natural sciences.
Hrushikesh Mhaskar is a Research Professor of Mathematics at Claremont Graduate University (CGU) since 2012, with a prior 32-year tenure at California State University, Los Angeles. He holds a PhD in Mathematics from Ohio State University, alongside an MS in Computer Science and an MSc from the Indian Institute of Technology, Mumbai. His research focuses on approximation theory, computational harmonic analysis, machine learning, and signal processing, with significant contributions to neural network theory and kernel-based methods. Mhaskar has authored over 150 papers, two books, and five edited volumes. His work includes pioneering studies on weighted polynomial approximation, Fourier domain conversions, and manifold learning. He currently serves on editorial boards for journals like Applied and Computational Harmonic Analysis and Journal of Approximation Theory , and collaborates with institutions like the University of California, Santa Barbara. Awards include five Alexander von Humboldt Fellowships and a John von Neumann Distinguished Professorship. His research is supported by the NSF and previously by the U.S. Air Force and intelligence agencies. Notable contributions include developing eignets for function approximation on manifolds and analyzing deep vs. shallow networks' approximation capabilities. His work bridges theoretical mathematics with practical applications in biomedical data analysis (e.g., blood glucose prediction) and signal processing.
Konrad Aguilar is an Assistant Professor of Mathematics and Statistics at Pomona College, currently on sabbatical for the 2025-2026 academic year. He holds a PhD in Mathematics from the University of Denver (2015), an M.S. in Mathematics from the same institution, and a B.S. in Applied Mathematics from California State Polytechnic University, Pomona. His research focuses on noncommutative/quantum metric geometry, blending tools from functional analysis, operator algebras, and metric geometry to study convergence of operator algebras and finite-dimensional approximations. Research Interests include compact quantum metric spaces, Quantum Gromov-Hausdorff convergence, finite-dimensional approximations, and compact quantum groups. His work has led to contributions in areas such as AF algebras, Podleś spheres, and quantum ultrametrics. He has collaborated with leading mathematicians like Frédéric Latrémolière and Jens Kaad, producing influential papers in Studia Mathematica , Journal of Operator Theory , and Journal of Geometry and Physics . Awards include the MAA Project NExT fellowship (2021-2022) and the AMS-Simons Travel Grant (2019-2022). He actively mentors undergraduates in matrix analysis and finite-dimensional algebraic structures, bridging foundational theory with advanced research. His articles explore topics such as quantum metric spaces, spectral triples, and convergence in noncommutative geometry, reflecting a deep engagement with both pure mathematics and its applications in quantum frameworks. Recent work includes studies on Podleś sphere spectra and quantum metrics on tensor products of C*-algebras.
Sandra Kingan is an Associate Professor of Mathematics at the City University of New York, with joint appointments in the Mathematics Ph.D. program at the Graduate Center and the Mathematics Department at Brooklyn College. Her research bridges combinatorics, geometry, and network science, focusing on matroid theory, graph theory, and combinatorial algorithms. Her work includes the publication of the book Graphs and Networks (Wiley, 2022), which integrates graph theory with network science for mathematicians and data scientists. She co-founded the New York Combinatorics Group , organizing seminars and workshops since 2011, including the annual Graph Theory Day of New York and biannual New York Graph Theory Workshop . Her broader interests span combinatorial optimization, linear and abstract algebra, probability, history of mathematics, and climate science. She is actively engaged in the scholarship of teaching and learning, experimenting with innovative pedagogical methods.
