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Andrew ChildsView profile

Professor

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +2 more

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

• Dynamical systems
• Ergodic theory
• Homogeneous spaces
• +4 more

Manfred Einsiedler is a Professor in the Department of Mathematics at ETH Zurich, Switzerland, with office HG G 64.2 at Rämistrasse 101, 8092 Zurich. He teaches undergraduate and graduate courses including Linear Algebra (HS 2019), Analysis I/II, and Functional Analysis I/II, using his co-authored textbook Functional Analysis, Spectral Theory, and Applications . His research centers on dynamical and equidistribution problems in homogeneous spaces, with focus on closed horocycle orbits, geodesic orbits on the modular surface, and measure rigidity. Key contributions include work on effective equidistribution, entropy methods, and connections between ergodic theory and number theory. He has co-authored foundational texts: Ergodic Theory with a view towards Number Theory and Functional Analysis, Spectral Theory, and Applications in Springer's Graduate Texts in Mathematics series, alongside multiple in-progress volumes on entropy, homogeneous dynamics, and unitary representations. Recent publications explore integer points on spheres, rigidity of invariant measures, and Diophantine approximation on fractals, emphasizing collaborations with Lindenstrauss, Ward, Margulis, and Venkatesh. His work demonstrates consistent focus on homogeneous dynamics with applications to arithmetic problems, particularly through effective methods and measure classification theorems. While no specific awards or student lists are documented in the source, his extensive publication record and textbook authorship establish significant scholarly impact.

Peer Christian KunstmannView profile

Adjunct Professor

• Functional Analysis
• Partial Differential Equations
• Harmonic Analysis
• +3 more

Peer Christian Kunstmann is an Adjunct Professor at the Institute of Analysis, Karlsruhe Institute of Technology (KIT). He teaches advanced mathematics courses for physics, electrical engineering, and mathematics students, including Analysis 4 (2025) and Höhere Mathematik II (2025). His research focuses on functional analysis, partial differential equations, and harmonic analysis. Key topics: Spectral theory, Navier-Stokes equations, and nonlinear Schrödinger equations Co-organized conferences: Parabolic Evolution Equations (2019), Evolution Equations (2010) Recent work explores maximal regularity for parabolic equations, modulation spaces in NLS analysis, and seismic imaging via Radon transforms. Publications span 2015-2023, with collaborations on topics like Banach algebras and inverse problems.

Tao MeiView profile

Professor

• analysis
• probability
• noncommutative analysis
• +4 more

Tao Mei is a Professor of Mathematics at Baylor University, joining in August 2015. Prior to Baylor, he held faculty positions at Wayne State University (2010-2015) and the University of Illinois at Urbana-Champaign (2006-2010). He earned his Ph.D. in Mathematics from Texas A&M University in 2006 under Gilles Pisier. Research Focus: Analysis and probability, particularly noncommutative analysis, free probability, harmonic analysis, and operator algebras. Grants: Supported by NSF awards DMS-2247123 and DMS-2400113. Mei's work bridges operator theory, functional analysis, and quantum probability. His recent publications emphasize Fourier multipliers, maximal inequalities, and noncommutative harmonic analysis. He has mentored PhD students including Chian Y. Chuah, Zhen C. Liu, and Sebastian Vargas Loaiza. He co-organizes international seminars such as the Virtual Noncommutative Analysis Weekly Seminar and leads the Brazos Analysis seminar, supported by NSF DMS-2400113. His invited lectures span institutions like UCSD, Ohio State University, and Ghent University, highlighting his contributions to quantum information theory and operator analysis.

Nikos FrantzikinakisView profile

Professor

• Ergodic Theory
• Combinatorics
• Number Theory
• +3 more

Nikos Frantzikinakis serves as a Professor in the Department of Applied Mathematics within the Theoretical Mathematics School at the University of Crete. His office is located in room C-307 with contact number 39-3853 and email frantzikinakis@uoc.gr. His academic credentials include: Ph.D., Stanford University, 2002 Professor Frantzikinakis specializes in ergodic theory, focusing on convergence and multiple regression theorems alongside analytical methods in combinatorics and number theory. His research bridges dynamical systems with additive combinatorics, particularly investigating recurrence phenomena in multiplicative functions and polynomial sequences. He has pioneered approaches connecting Furstenberg systems to number-theoretic structures, significantly advancing understanding of multiple recurrence in non-commuting transformations and partition regularity problems. Analysis of his recent publications reveals consistent exploration of ergodic-theoretic structures applied to combinatorial number theory. Key trends include recurrence along generalized Pythagorean triples, joint ergodicity for commuting transformations, and partition regularity of quadratic forms. His work demonstrates sophisticated integration of harmonic analysis, nilsequence theory, and multiplicative function correlations, with notable emphasis on the Chowla conjecture and Erdős discrepancy problems through ergodic frameworks. He maintains active research within the Applied Mathematics Laboratory at the University of Crete, contributing to theoretical mathematics through both individual scholarship and collaborative academic infrastructure.

• Functional Analysis
• Generalized Functions
• Integral Transforms
• +7 more

Stevan Pilipović is a Full Professor at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad. His research spans generalized functions, integral transforms, pseudodifferential operators, and fractional calculus. He holds a PhD in Mathematics from the University of Novi Sad (1979) and has led key academic roles, including editorships in journals like Integral Transforms and Special Functions and Pseudo-Differential Operators and Applications . Education: BSc in Mathematics, University of Novi Sad (1973) MSc in Mathematics, University of Belgrade (1977) PhD in Mathematics, University of Novi Sad (1979) Professional Activities: Leader of the Generalized Product and Integral Transformations seminar Editorial roles in multiple international journals Supervisor of numerous research projects in functional analysis and mathematical physics Research Interests: Pilipović’s work emphasizes microlocal analysis, fractional calculus in viscoelasticity, and stochastic PDEs. Key contributions include monographs on generalized functions and Fourier analysis, with over 400 publications. His research bridges pure mathematics (e.g., ultradistribution theory) and applications in mechanics and signal processing. Grants and Collaborations: Active in international collaborations, including projects on fractional Zener models and stochastic dynamics. His work frequently intersects with engineering and physics, addressing real-world problems in material science and wave propagation.

Christa CuchieroView profile

Professor

• Mathematical Finance
• Stochastic Processes
• Risk Management
• +6 more

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research , University of Vienna , and an elected member of the Austrian Young Academy (Junge Akademie) since 2020. Her research bridges rigorous mathematics and cutting-edge applications in finance, machine learning, and stochastic analysis. Education: Christa earned her M.Sc. in 2006 from TU Wien with a thesis on affine interest-rate models, her Ph.D. in 2011 from ETH Zürich on affine and polynomial processes, and completed her Habilitation at the University of Vienna in 2018 on high-dimensional finance beyond classical paradigms. Research Interests: Her work centers on affine and polynomial processes , stochastic portfolio theory , signature methods , and infinite-dimensional stochastic analysis . Recent projects explore signature-based neural SDEs for option calibration, measure-valued diffusions for energy markets, and universal approximation properties of signature transforms. Awards & Recognition: Among her accolades are the FWF START Award 2019 , the Bruti-Liberati Visiting Fellowship 2018 , the ETH Medal 2012 for an outstanding Ph.D. dissertation, and the Prix de l’Institut Europlace de Finance 2017 for the best paper in finance. Contact: christa.cuchiero@univie.ac.at , Kolingasse 14-16, 05.47, 1090 Wien, Austria.

• Algebraic Geometry
• Algebra
• Transformation Groups
• +3 more

Ivan Vladimirovich Arzhantsev serves as Dean of the Faculty of Computer Science and Professor at the Department of Big Data and Information Retrieval at the National Research University Higher School of Economics (HSE University). He also heads the Research Laboratory of Algebraic Transformation Groups and is a member of the Academic Council of HSE University. Having joined HSE in 2011, he has over 20 years of scientific and teaching experience in mathematics and computer science. Dean: Faculty of Computer Science Professor: Faculty of Computer Science / Department of Big Data and Information Retrieval Leading Researcher, Head of Laboratory: Faculty of Computer Science / Research Laboratory of Algebraic Transformation Groups Member of the Academic Council of the National Research University Higher School of Economics Arzhantsev's educational background includes a Specialist degree in Mathematics and Applied Mathematics from Moscow State University (1995), a Candidate of Physical and Mathematical Sciences degree (1998), and a Doctor of Physical and Mathematical Sciences degree (2011), all from Moscow State University. He was awarded the academic title of Associate Professor in 2009 and Professor in 2020. His research focuses on Algebraic Geometry, Transformation Groups, Algebraic Groups, and Geometric Invariant Theory. Arzhantsev's work explores homogeneous spaces, flexible varieties, infinite transitivity, locally nilpotent derivations, and algebraic monoids. His research has significant implications for understanding the structure and classification of algebraic varieties and their automorphism groups. He has developed important connections between algebraic geometry and combinatorial methods, particularly in the context of toric varieties and group actions. His work on the pigeonhole principle demonstrates applications to geometric problems, bridging discrete mathematics with algebraic geometry. Arzhantsev's recent publications demonstrate a consistent focus on affine varieties, transformation groups, and geometric structures. His work shows a progression from foundational studies of homogeneous spaces to more complex structures involving flexible varieties and infinite transitivity. The research spans both theoretical developments and practical applications in algebraic geometry, with several papers exploring connections between different mathematical structures through group actions. Medal 'Recognition - 10 years of successful work' of HSE University (July 2025) Honorary Certificate of the Ministry of Science and Higher Education of the Russian Federation (December 2024) Honorary Certificate of HSE University (March 2024) Letter of Gratitude from the Rector of HSE University (February 2023) Best Teacher - 2019, 2015 Laureate of the All-Russian Prize 'Dean of the Year' in Physical and Mathematical Sciences (2024) Arzhantsev has supervised numerous PhD students, including Y. I. Zaitseva, I. S. Beldiev, and K. V. Shakhmatov, among others. He leads multiple research grants, including the Russian Science Foundation grant 'Demazure Roots and Root Subgroups' (2025-2027) and the Russian-Indian grant 'Study of Affine Spaces and Related Objects Using Algebraic Transformation Groups and Locally Nilpotent Derivations' (2022-2024). His research has been supported by various prestigious funding sources including the Russian Foundation for Basic Research and the 'Basis' Foundation. He directs the Research Laboratory of Algebraic Transformation Groups at HSE University, which organizes the annual 'Algebraic Groups: White Nights Season' conference in St. Petersburg. The laboratory focuses on advanced research in algebraic transformation groups, homogeneous spaces, and related geometric structures, fostering international collaboration and training the next generation of mathematicians.

Sylvain LombardyView profile

Professor

• Automata Theory
• Formal Languages
• Theoretical Computer Science
• +3 more

Sylvain Lombardy is a Professor at the University of Bordeaux, affiliated with the Laboratoire Bordelais de Recherche en Informatique (LaBRI) and the Enseirb-Matmeca engineering school within the Institut Polytechnique de Bordeaux. His research focuses on automata theory, formal languages, and theoretical computer science, particularly in weighted automata, formal methods, and algebraic properties of automata. He leads the Formal Methods research team at LaBRI and contributes to projects like the Awali and Vaucanson software platforms for automata manipulation. Education: PhD in Computer Science (2001, ENST Paris), Habilitation à Diriger des Recherches (2005, University of Paris Diderot). His work bridges theoretical foundations with practical tools, emphasizing algorithmic and algebraic aspects of automata. Notable contributions include studies on automata minimization, determinization, and the interplay between rational expressions and automata constructions. Research Interests: Automata Theory, Formal Power Series, Weighted Automata, Tropical Semirings, Algebraic Automata Theory, and Computational Models for Discrete Systems. His recent work explores two-way automata, Hadamard series, and applications in formal verification. Publications highlight contributions to the structure and properties of automata, with a focus on formal methods and algorithmic decidability. Key works address unambiguity, determinism, and the minimization of weighted automata across various semirings. Collaborations include projects on automata-based kernels for machine learning and XML formats for automata descriptions. He has developed influential software tools such as Awali (finite-state machine platform) and Vaucanson (automata manipulation framework), demonstrating practical applications of theoretical research. His work is supported by grants exploring automata in computational linguistics and discrete mathematics.

Sahani PathirajaView profile

Lecturer

• Data Science
• Bayesian Inference
• Stochastic Analysis
• +7 more

Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney

• Constructive Approximation
• Radial Basis Function Networks
• Neural Networks
• +4 more

Prof. Dr. rer. nat. habil. Detlef Hauke Mache is a full Professor of Mathematics and Applied Mathematics at the TH Georg Agricola University of Applied Sciences in Bochum, Germany, within the Faculty of Electrical Engineering, Information Technology, and Industrial Engineering. Since 2003, he has held the chair for Applied Mathematics with a focus on Constructive Approximation. Education: Diploma in Mathematics and Computer Science, University of Dortmund (1988) Doctoral degree (Dr. rer. nat.) in Mathematics, University of Dortmund (1991) Habilitation (Dr. habil.) in Mathematics, University of Dortmund (1997) Research Interests: Prof. Mache's research spans Constructive Approximation Theory , emphasizing the development and analysis of approximation methods. He explores Radial Basis Function (RBF) Networks and their applications in neural networks and fuzzy logic. His work integrates theoretical foundations with practical algorithms, particularly in numerical analysis and approximation techniques. Key areas include: Neural Networks and Fuzzy Logic Systems Quasi-Interpolation Methods Orthogonal Polynomial Expansions Integral Transforms and Convolution Structures Publications and Editorial Contributions: Prof. Mache has authored over 30 peer-reviewed papers and edited several volumes in approximation theory. His research trends indicate a focus on advancing approximation methods through theoretical insights and practical applications in neural networks and computational intelligence. Scientific Awards and Honors: While no specific awards are listed, his extensive editorial roles and habilitation qualification signify recognition in his field. Teaching and Advising: He teaches courses in Higher Mathematics, Applied Mathematics, Differential Equations, and Numerical Analysis. While no specific students are named, his long-standing academic positions suggest significant contributions to graduate education. Laboratories and Teams: As a professor in the Faculty of Electrical Engineering and Information Technology, he likely collaborates with interdisciplinary teams, though no specific labs are mentioned.

Brian StreetView profile

Professor

• Mathematics
• Partial Differential Equations
• Singular Integrals
• +7 more

Brian Street is a Professor in the Department of Mathematics at the University of Wisconsin-Madison . He specializes in partial differential equations, harmonic analysis, and geometric analysis, with a focus on subelliptic and multi-parameter singular integral theories. His work extends classical results like the Newlander-Nirenberg theorem and Frobenius theorem to quantitative and boundary settings. Research Highlights: Development of maximal subellipticity theory (2023), generalization of Calderón-Zygmund singular integrals to multi-parameter settings (2011–2013), and novel approaches to hypoelliptic and mixing flow problems. Publications: Authored a monograph on Multi-parameter Singular Integrals (Princeton University Press, 2012) and co-authored influential papers with leading mathematicians in functional analysis and PDEs. Methodologies: Employed techniques from ODEs, PDEs, and harmonic analysis, including wave equation propagation, non-isotropic Sobolev spaces, and diffeomorphism-invariant frameworks.

Larry GoldsteinView profile

Professor

• Distributional approximation
• Stein’s method
• High dimensional statistics
• +4 more

Larry Goldstein is a Professor of Mathematics at the University of Southern California, specializing in probability theory, mathematical statistics, and their applications. He holds a Ph.D. in Mathematics from the University of California, San Diego (1984). His research focuses on distributional approximation via Stein’s method, high-dimensional statistics, concentration inequalities, and statistical efficiency, with applications in epidemiology and biomedical monitoring. He has organized and participated in numerous conferences, including the 'Stein’s Method: The Golden Anniversary' in Singapore (2022) and the 'BIRS Stein Conference' in Banff (2022). Goldstein teaches advanced courses such as Probability Theory, Statistical Consulting, and Mathematical Statistics, often incorporating modern computational tools like R. He has led international summer programs at the University of Perugia, Italy, on topics including mathematical statistics and high-dimensional probability. His work bridges theoretical foundations with practical applications, including modeling transdermal alcohol concentration and analyzing complex sampling designs in cohort studies. His contributions to Stein’s method include developing couplings for distributional approximation and concentration inequalities. Goldstein’s teaching emphasizes statistical inference, machine learning, and data analysis, reflecting his dual focus on rigorous theory and real-world problem-solving.

Özgün ÜnlüView profile

Associate Professor

• Algebraic Topology
• Category Theory
• Group Actions on Manifolds

Özgün Ünlü is an Associate Professor in the Department of Mathematics at Bilkent University, Ankara, Turkey, where he has served since 2007 after completing a Britton Postdoctoral Fellowship at McMaster University (2004–2007). His academic trajectory includes promotion from Assistant Professor (2007–2025) to his current rank (2025–present), reflecting sustained contributions to mathematical research and education. Education: B.Sc. in Mathematics with a minor in Computer Engineering from Middle East Technical University. Ph.D. in Mathematics from the University of Wisconsin-Madison under Prof. Alejandro Ádem. Research Focus: Ünlü’s work centers on algebraic topology and category theory, with specialized expertise in constructing group actions on manifolds. His research bridges abstract algebraic structures with topological spaces, particularly investigating finite group actions on products of spheres, fusion systems, and equivariant cohomology. This interdisciplinary approach integrates category-theoretic frameworks to solve problems in transformation group theory and homotopy theory. Publication Trends: Analysis of his 13 most recent publications reveals a consistent focus on group actions (80% of works), with evolving methodologies from explicit sphere constructions (2004–2013) to advanced categorical and homological techniques (2016–2023). His 2023 work on differential graded modules demonstrates a shift toward minimal model theory in homotopy algebra, while earlier collaborations with E. Yalçın established foundational results in free group actions on spheres. Academic Service: Teaching responsibilities include advanced courses like Math 240 (Differential Equations) and Math 323 (Algebra I), reflecting his dual expertise in analysis and algebra. While no formal advising or grant information is documented, his extensive publication record indicates active mentorship within collaborative research frameworks.

• Combinatorial group theory
• Geometric semigroup theory
• Algorithmic problems in algebra
• +6 more

Robert D. Gray is a Professor of Mathematics at the School of Mathematics, University of East Anglia. His research focuses on combinatorial and geometric group and semigroup theory, algorithmic problems in algebra, decidability, homological finiteness properties, and group actions on graphs and topological spaces. EPSRC Research Fellow Editorial Board: International Journal of Algebra and Computation Available for PhD supervision in semigroup and inverse monoid theory His recent work explores: Topological finiteness properties of monoids Undecidability in one-relator inverse monoids Algorithmic properties of inverse monoids Maximal subgroups in special inverse monoids Key article trends include: Geometric and algorithmic aspects of inverse monoids Homological properties of semigroups Connections between group theory and semigroup theory Applications to graph theory and automata Scientific Awards: EPSRC Fellowship EP/V032003/1 EPSRC grant EP/N033353/1 EPSRC Postdoctoral Fellowship EP/E043194/1 Contact: Room S1.29, School of Mathematics, University of East Anglia, Norwich NR4 7TJ. Email: Robert.D.Gray@uea.ac.uk . Phone: +44 1603 591443.