Polona Durcik is an Assistant Professor in the Department of Mathematics at Chapman University's Schmid College of Science and Technology. Her research lies at the intersection of mathematical analysis, harmonic analysis, and ergodic theory. Education: Master of Science, University of Bonn Ph.D., University of Bonn Durcik specializes in multilinear harmonic analysis, singular integrals, and ergodic theory. Her work addresses problems involving Brascamp-Lieb inequalities, isoperimetric problems on the Hamming cube, and ergodic averages with commuting transformations. Key research interests include density theorems, geometric configurations, and dimension-free estimates. Recent research trends focus on singular Brascamp-Lieb inequalities with cubical structures, dimension-free analysis of high/low degree functions, and convergence properties of multilinear ergodic averages. These works span from 2014 to 2025, with particular emphasis on applications to combinatorics and functional analysis. Contact: durcik@chapman.edu
Antonio Manzano Rodriguez is an Associate Professor in the Department of Mathematics and Computer Science at the School of Engineering, University of Burgos, Spain. His academic career spans over two decades with a focus on functional analysis and operator theory. He earned his doctorate from Universidad Complutense de Madrid in 2000 with a thesis titled 'Medidas asociadas a ideales de operadores y teoría de interpolación' supervised by Dr. Fernando Cobos Díaz and Dr. Antón Martínez Martínez. Manzano Rodriguez specializes in functional analysis, particularly in operator theory, interpolation theory, and Banach spaces. His research explores the connections between operator ideals, interpolation methods, and vector measures. He has made significant contributions to understanding weakly compact multilinear operators, closed operator ideals, and logarithmic interpolation spaces. His work often bridges theoretical mathematics with applications in mathematical modeling through the GMAMMI research group focused on Applied Mathematical Modelling of Materials and Engineering. His scientific output includes 19 publications since 1999 that have been cited 87 times across 59 documents. Recent works focus on multilinear operators, vector measures, and interpolation methods appearing in prestigious journals such as Mathematische Nachrichten and Banach Journal of Mathematical Analysis. He has collaborated extensively with researchers including Fernando Cobos (6 joint publications), Antón Martínez Martínez (6 joint publications), and Antonio Fernández Carrión (5 joint publications), demonstrating his active engagement in the mathematical research community. Manzano Rodriguez maintains an active research profile with publications extending to 2025, continuing to advance the theoretical foundations of functional analysis and its applications in mathematical modeling.
Anqi Dong is a Postdoctoral Fellow at KTH Royal Institute of Technology. They hold a BSc in Mechanical and Automation Engineering from Harbin Institute of Technology (2017) and a PhD in Mechanical and Aerospace Engineering from the University of California, Irvine (2023), supervised by Prof. Tryphon T. Georgiou. They were a visiting scholar with Prof. Li Qiu from 2023 to 2024 and are now co-supervised by Prof. Karl H. Johansson and Prof. Johan Karlsson at KTH. Education: BSc: Mechanical and Automation Engineering, Harbin Institute of Technology (2017) PhD: Mechanical and Aerospace Engineering, University of California, Irvine (2023) Research Interests: Anqi Dong's work focuses on control theory, optimal transport, and data-driven modeling of dynamical systems. Their research applies advanced mathematical frameworks to problems in multi-agent coordination, 3D scene understanding, and biomedical imaging. Key areas include tensor-based analysis, network learning, and computational methods for system identification. Recent Publications: Their 2025 studies explore dynamic optimal transport, neural network interpretability, and vessel segmentation, while 2024 contributions address temporal hypergraphs and toll station optimization. All work emphasizes interdisciplinary applications of mathematical and computational tools.
Jean-Philippe (JP) Richard is Professor of Industrial and Systems Engineering at the University of Minnesota, Twin Cities, and concurrently serves as Director of Faculty and Academic Affairs for the department. From 2018 onward he has held these roles, having previously been Professor (and PhD coordinator) at the University of Florida (2008-2018) and Assistant/Associate Professor at Purdue University (2002-2008). Education Ph.D. in Algorithms, Combinatorics, and Optimization, Georgia Institute of Technology, 2002 Bachelor of Engineering in Applied Mathematics, Université Catholique de Louvain, 1998 Research Interests Dr. Richard works at the intersection of theory and computation for mixed-integer linear and nonlinear optimization . His methodological focus spans convexification techniques , polyhedral approaches , lifting and cutting-plane methods , and global optimization algorithms . He translates these advances into impactful applications in data analytics , healthcare (radiation therapy & surgery scheduling) , railroad logistics , and infrastructure protection . Scientific Awards & Honors University of Florida Term Professorship (2017–2019) IIE Transactions Best Application Paper Award (2008) NSF CAREER Award (2004) Sigma Xi Best Ph.D. Thesis Award, Georgia Tech (2003) Russell J. Penrose ISyE Excellence in Teaching Award (2023) Grants & Funding Leadership Richard has been PI or co-PI on more than ten NSF awards totaling over $2 million, including recent grants on network interdiction, complementarity constraints, and opioid-policy analytics. Industry partnerships with Union Pacific Railroad and CSX Transportation have funded applied projects exceeding $150,000. Student Mentorship & Lab Culture He has (co-)advised 19 PhD dissertations and numerous Master’s and undergraduate researchers. Current advisees include Bouchra Er-Rabbany and Chengwenjian Wang; recent graduates hold positions at Google, ExxonMobil, Bayer, and leading universities worldwide. His group emphasizes rigorous theory coupled with real-world impact.
Masoud Ataei is an Assistant Professor, Teaching Stream in the Department of Applied Statistics at the University of Toronto's Mathematical and Computational Sciences school. His research spans statistical geometry, financial chaos indices, neural network optimization, and spatio-temporal systems analysis. He holds a position focused on teaching excellence within the applied statistics discipline. Research interests include developing mathematical frameworks for complex systems analysis, with applications in finance, materials science, and biomedical signal processing. His work emphasizes interpretable machine learning models and optimization algorithms for high-dimensional data. Key contributions involve the Financial Chaos Index for market volatility modeling and the GEOM-BP algorithm for bin packing problems. Publications demonstrate interdisciplinary impact across mathematics, computer science, and finance. No scientific awards are listed, but his active publication record reflects ongoing research productivity. Advising and grant activities are not detailed in available information.
Matthias Walter is an Assistant Professor in the Department of Mathematics of Operations Research. His research focuses on optimization, mathematical programming, and algorithm design, with applications in transportation, combinatorial optimization, and logistics. He contributes to the SCIP Optimization Suite and has developed the Combinatorial Matrix Recognition Library. His work spans topics such as linear programming relaxations, pseudo-Boolean solving, and multilinear optimization. Key research interests include operations research, integer programming, and algorithmic solutions for complex optimization problems. He has collaborated on projects like optimizing parcel transportation and analyzing congestion games. His recent publications address challenges in flow shop scheduling, graph realization, and pseudo-Boolean functions. Walter actively participates in academic activities, organizing events like the Mathematical Olympiad in Saxony-Anhalt and presenting invited talks on topics such as McCormick relaxations. His contributions to computational tools and theoretical advancements highlight his role in advancing optimization methodologies.
Tin-Yau Tam is the Chair of the Department of Mathematics and Statistics at the University of Nevada, Reno (UNR), holding the Seneca C. and Mary B. Weeks Endowed Professorship. His primary affiliation is within the College of Science, where he contributes to both teaching and research. Dr. Tam earned his Ph.D. in Mathematics from the University of Hong Kong in 1986, following a B.Sc. in Mathematics from the same institution in 1982. His research focuses on advanced topics in linear algebra and matrix theory, including Lie groups/algebras, multilinear algebra, numerical ranges, operator theory, and their applications. His work bridges pure mathematics with interdisciplinary applications, such as quantum information theory and geometric analysis. Dr. Tam has contributed to over 150 scholarly articles, with recent work exploring geometric means in matrix analysis, spectral inequalities, and Lie group structures in matrix theory. His research trends emphasize the interplay between algebraic structures and geometric interpretations, with applications in data science and quantum computing. Though no specific awards are listed, his extensive publication record and endowed chair position reflect his scholarly impact. He advises students and collaborates on research projects within the department’s vibrant academic community, though specific advisee names are not documented here. His work is often centered in the Davidson Mathematics and Science Center on the UNR campus.
Yuliya Babenko is a Full Professor of Mathematics at the Department of Mathematics, Kennesaw State University (KSU), within the College of Science and Mathematics. She specializes in Numerical Analysis, Approximation Theory, and Spline Theory. Her research focuses on optimal recovery of operators, functional inequalities, and computational geometry. Education : PhD in Mathematics, Vanderbilt University (2006) MA in Mathematics, Vanderbilt University (2003) MS in Mathematics, Dnepropetrovsk National University, Ukraine (2001) BS in Mathematics, Dnepropetrovsk National University, Ukraine (2000) Research Interests : Numerical Analysis, Approximation Theory, Spline Theory, Functional Inequalities, Optimization of Quadrature Formulas, and Computational Geometry. She co-organizes the Analysis and Applied Mathematics seminar and the Kennesaw Mountain Undergraduate Mathematics Conference. Publications : Her work spans topics like optimal recovery of integral operators, Hardy-Littlewood-Polya inequalities, and multivariate spline approximation. Recent contributions include studies on operator approximation in Banach spaces and Taikov-type inequalities. Awards : 2015-2016 CSM Distinguished Research Award 2014-2015 CSM Distinguished Teaching Award 2013 MAA Southeastern Section Distinguished Teaching Award Advising & Grants : Mentored undergraduate researchers like Najia Bacha. Active in promoting undergraduate mathematics through conferences and collaborative initiatives. Labs/Teams : Collaborates with researchers including Vladislav Babenko, Sergiy Borodachov, and Jean-Marie Mirebeau on interdisciplinary projects in approximation theory and computational mathematics.
Enrique Pedro Jaime Monso Burgues is a Researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mathematics at the Escola Superior d'Enginyeries Industrial, Aeroespacial i Audiovisual de Terrassa (ESEIAAT). He is a core member of the research groups MAPTHE (Matrix Analysis and Discrete Potential Theory) and OMGRAPH (Optimization Methods on Graphs). His work focuses on discrete mathematics, graph theory, and their applications in network analysis and inverse problems. Monso holds a doctoral degree in Mathematics from UPC, with his thesis titled "Discrete operators and distances on subdivision networks". He has led and participated in multiple competitive research projects, including "Design and valorization of an Electrical Impedance Tomography device for early detection of breast cancer" (2024) and "Análisis multifacético de problemas inversos en redes" (2021). His research integrates theoretical advancements with practical applications in biomedical engineering and healthcare technology. He has published extensively in peer-reviewed journals like *Linear and Multilinear Algebra* and *Applicable Analysis and Discrete Mathematics*, focusing on topics such as Green's functions, Kirchhoff indices, and group inverse matrices in subdivision networks. His work on Electrical Impedance Tomography (EIT) demonstrates interdisciplinary collaboration in medical imaging and device development. Monso has also contributed to educational innovation, developing blended learning tools for mathematics education in engineering and optics. He collaborates with institutions across UPC's Terrassa, Diagonal Sud, and Diagonal-Besòs campuses, reflecting his active role in both academic and applied research communities.
Joris Roos is an Assistant Professor at the University of Massachusetts Lowell within the Department of Mathematics and Statistics, part of the Kennedy College of Sciences. He holds a Ph.D. in Mathematics from the University of Bonn (2017). His research focuses on Fourier analysis, real analysis, and computer-assisted proofs, with particular emphasis on harmonic analysis applications in combinatorics, number theory, PDEs, and fractal geometry. He has been supported by grants including the NSF DMS-2154835 (2022-2025) and a Simons Foundation Grant (2021-2022). Roos has also participated in fellowships at the Hausdorff Research Institute for Mathematics and Oberwolfach. His work bridges pure analysis with computational methods, addressing problems in multilinear inequalities, maximal functions, and sparse domination techniques. Education: Ph.D. in Mathematics, University of Bonn, 2017 Research Interests: Fourier and harmonic analysis on Euclidean spaces Oscillatory integrals, maximal functions, singular integrals Discrete analogues in harmonic analysis Applications to combinatorics, number theory, dispersive PDEs Formalization of mathematics using interval arithmetic Grants & Fellowships: National Science Foundation Grant DMS-2154835 (2022-2025) Simons Foundation Grant ID 855692 (2021-2022) American Institute of Mathematics SQuaRE projects (2021-2025) Hausdorff Research Institute for Mathematics Fellowships (2021, 2022, 2024) Oberwolfach Research Fellowship (2023) Current Activity: Leading the 2024 HIM Trimester Program on Boolean Analysis in Computer Science and co-organizing the MLHA 2024 Spring School on multilinear singular integrals.
Brett D. Wick is a Professor of Mathematics at Washington University in St. Louis, specializing in analysis with a focus on complex analysis, harmonic analysis, and operator theory. He holds a PhD from Brown University and has been recognized with prestigious awards including the NSF CAREER Award and the Alexander von Humboldt Fellowship. His research explores interactions between these fields, particularly extending results from complex and harmonic analysis to higher dimensions and addressing the Corona Problem in multiple variables. Education: PhD in Mathematics from Brown University. Research interests include several complex variables, operator theory, and multi-parameter harmonic analysis. He has contributed to studies on Riesz transforms, paraproducts, and weighted inequalities, with applications to quasiregular maps and functional spaces. Wick organizes conferences and collaborates internationally, appearing at events like the International Workshop on Operator Theory (IWOTA) and the Banff International Research Station. Scientific Awards: Fellow of the American Mathematical Society, Alexander von Humboldt Fellow, NSF CAREER Award, Jerrold E. Marsden Postdoctoral Fellow. Grants and Funding: His work is supported by the National Science Foundation. Collaborations involve researchers globally, focusing on topics like Schatten classes, commutators, and function spaces. Labs/Teams: Active in the Washington University Analysis group and collaborates with international teams on operator theory and harmonic analysis projects.
Dan-Andrei Geba is a Professor in the Department of Mathematics at the University of Rochester, part of the School of Arts & Sciences. His research focuses on nonlinear partial differential equations, with particular emphasis on wave maps, Skyrme models, and dispersive equations. He co-authored the book An Introduction to the Theory of Wave Maps and Related Geometric Problems (2016) and has contributed to foundational studies in harmonic analysis and applied mathematics. Prof. Geba has been actively involved in academic outreach, including organizing the University of Rochester Math Olympiad since 2007 and leading initiatives like the Mathcounts Club and Rochester Area Math Circle. His teaching spans advanced undergraduate and graduate courses in complex analysis, differential equations, and real/functional analysis. He emphasizes proof-based learning and independent problem-solving skills in his classes. His research interests include nonlinear wave equations, geometric PDEs, and applications to mathematical physics. Recent work explores global regularity, stability, and scattering properties in models like the Faddeev and Skyrme systems. He also investigates bilinear estimates and dispersive properties of equations like the Kawahara and Boussinesq models.
Prof. Dr. İbrahim Halil GÜMÜŞ is a distinguished faculty member at Adıyaman University, Faculty of Arts and Sciences, Department of Mathematics, where he currently holds the position of Professor (since 2023). Previously, he served as Associate Professor (2017-2023) and Assistant Professor (2011-2017) at the same institution. Before his academic career, he worked as a Teacher at Public Schools under the Ministry of National Education from 2002 to 2011. He earned his educational qualifications from Selçuk University: B.Sc. in Mathematics (1998-2002), M.Sc. in Mathematics (2002-2005), and PhD in Mathematics (2005-2011). His Master's Thesis focused on 'On the Hadamard Product of Matrices' (2005), while his PhD Thesis examined 'Bounds on arithmetic, geometric and Heinz means of positive definite matrices' (2011). Prof. GÜMÜŞ's research primarily centers on Matrix Theory and Operator Inequalities, with significant contributions to Positive Operators, Matrix Analysis, and Optimization. His work demonstrates a strong theoretical foundation in mathematical inequalities with increasing applications in data science and medical informatics. He has published extensively in high-impact journals such as Linear and Multilinear Algebra, Journal of Mathematical Analysis and Applications, and Operators and Matrices. His publication record shows a clear evolution from theoretical matrix inequalities toward practical applications in data analysis, particularly evident in his recent work on synthetic data generation for imbalanced datasets using geometric means and Heinz averages. This interdisciplinary approach bridges pure mathematics with machine learning applications, especially in medical data analysis. TÜBİTAK Publication Incentive Award, 2012 TÜBİTAK Publication Incentive Award, 2015 TÜBİTAK Publication Incentive Award, 2017 TÜBİTAK Publication Incentive Award, 2018 TÜBİTAK Publication Incentive Award, 2019 TÜBİTAK Publication Incentive Award, 2021 Prof. GÜMÜŞ has successfully supervised multiple Master's theses on topics including inequalities for positive multilinear mappings, geometric inequalities via majorization methods, determinants of positive semi-definite matrices, and mathematical approaches to synthetic data sampling. He serves as a referee for prestigious journals including Journal of Inequalities and Applications and Mathematical Reviews/MathSciNet. His administrative roles include Farabi Coordinator, Erasmus Coordinator, Bologna Coordinator for both the Faculty of Arts and Sciences and Institute of Science, and Mevlana Exchange Program Institutional Coordinator. His work bridges theoretical mathematics with practical applications in data science, particularly in addressing challenges related to imbalanced datasets in medical informatics through innovative mathematical approaches.
Tadahiro Oh is a Professor at the School of Mathematics, University of Edinburgh , specializing in nonlinear partial differential equations (PDEs), harmonic analysis, and stochastic dynamics. His work bridges deterministic and probabilistic approaches to dispersive Hamiltonian PDEs, focusing on well-posedness, invariant measures, and turbulence phenomena. Academic Rank: Professor Affiliation: University of Edinburgh Research Interests include nonlinear dispersive equations like the cubic nonlinear Schrödinger and stochastic wave equations, using techniques from PDE analysis, Fourier analysis, and probability. He investigates soliton behavior, growth of Sobolev norms, and statistical hydrodynamics. Grants & Collaborations highlight support from an EPSRC small grant (2024–2025) and two ERC grants (“ProbDynDispEq,” 2015–2020; “SingStocDispDyn,” 2020–2026). His team includes postdocs and Ph.D. students working on stochastic quantization, Gibbs measures, and dispersive equations. Publications focus on stochastic PDEs, nonlinear wave equations, and probabilistic well-posedness, often in top journals like Invent. Math. and J. Eur. Math. Soc. . Key trends involve invariant measures, multilinear operators, and applications to mathematical physics. Awards : Sir William Darling Memorial Prize (2023) Students include Thomas Arthur, Ruoyuan Liu, and Andreia Chapouto, with theses on nonlinear Schrödinger equations, stochastic dynamics, and dispersive equations. Former students hold academic positions globally.
Andrea Nahmod is a Provost Professor and Full Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. She holds a Ph.D. in Mathematics from Yale University (1991) and an MSci. from the University of Buenos Aires (1985). Professor Nahmod's research lies at the intersection of Nonlinear Fourier Analysis/Harmonic Analysis and Nonlinear Partial Differential Equations, integrating tools from geometry, gauge theory and probability. Her work focuses on (i) the behavior of solutions to nonlinear dispersive equations arising as models in Physics and Geometry from deterministic and probabilistic viewpoints, and (ii) wave-packet analysis techniques and multilinear singular pseudodifferential operators. Her research has been partially funded by the National Science Foundation and the Simons Foundation. She is currently organizing a Fall 2025 Semester Program at SLMath/MSRI on "Recent Trends in Stochastic Partial Differential Equations" and has been involved in significant research programs including an ICERM Semester Program on "Hamiltonian Methods in Dispersive and Wave Evolution Equations" and the Simons Collaboration on Wave Turbulence. Professor Nahmod has received recognition for her award-winning teaching and has advised eight doctoral students to completion including Nikolaos Tzirakis (2004), Tadahiro Oh (2007), Viktor Grigoryan (2008), Allison Tanguay (2012), Haitian Yue (2018), Xueying Yu (2018), Michael Boratko (2018), and Dean Katsaros (2024), whose research primarily focuses on nonlinear dispersive PDEs, geometric nonlinear PDEs, and nonlinear wave equations. She has also mentored numerous undergraduate researchers through REU and Capstone projects on topics including Fourier analysis, wavelet theory, signal recognition, geometry, combinatorics, and harmonic analysis, demonstrating her commitment to developing the next generation of mathematicians.
