جست‌وجوی استاد و پژوهشگر

Richard Douglas Canaryمشاهده پروفایل

استاد

• Hyperbolic 3-manifolds
• Higher Teichmüller theory
• Geometric group theory
• +۳ مورد دیگر

Richard Douglas Canary is a Professor in the Department of Mathematics at the University of Michigan , affiliated with the College of Literature, Science, and the Arts. His research focuses on hyperbolic 3-manifolds, Higher Teichmüller theory, geometric group theory, and low-dimensional topology. He holds a Ph.D. from Princeton University (1989) and has been at the University of Michigan since 1991, advancing from Assistant (1991–1996) to Associate (1996–2001) and full Professor (2001–present). Research Interests Canary's work explores geometric structures on low-dimensional manifolds, particularly hyperbolic 3-manifolds and Anosov representations. He has contributed to the Ending Lamination Conjecture, deformation spaces of Kleinian groups, and the development of pressure metrics in Higher Teichmüller theory. His collaborations have led to advancements in understanding geometric finiteness, convex cores, and Patterson-Sullivan measures. Awards and Recognition - Sloan Research Fellow (1993–1997) - Fellow of the American Mathematical Society (2015) - Simons Fellow (2020–2021, 2025–2026) - Sigma Xi Distinguished Lecturer (2015–2017) Recent Work Recent projects include studies on Patterson-Sullivan measures for Anosov groups, entropy rigidity in Hitchin representations, and bi-Lipschitz rigidity of discrete subgroups. His work often bridges geometric analysis, topology, and dynamics. Professional Activities Canary has held visiting positions at institutions like the Institut Henri Poincaré (Paris), MSRI (Berkeley), and Yale University. He contributed to the EMS Surveys in Mathematical Sciences and organizes lectures on geometric structures. His research frequently involves collaborative efforts with topologists and geometers worldwide.

Elsa Prada Nuñezمشاهده پروفایل

پژوهشگر

• Condensed Matter Theory
• Quantum Materials
• Topological Insulators
• +۱۴ مورد دیگر

Elsa Prada Nuñez is a Senior Researcher at the Institute of Materials Science of Madrid (ICMM) under the Spanish National Research Council (CSIC) . She leads the Quantum Dynamics of Materials (QUDYMA) group and currently serves as Head of the Theory Department. Her academic career spans multiple institutions, including the Universidad Autónoma de Madrid (UAM), Karlsruhe University, and Lancaster University, with a focus on condensed matter theory and quantum materials. PhD in Physics from UAM (2006) Tenured Scientist at ICMM-CSIC (2020-2025) Senior Researcher at ICMM-CSIC (2025-present) Her research explores quantum phenomena in low-dimensional materials and nanostructures, particularly topological insulators, Majorana zero modes in hybrid nanowires, graphene and 2D crystals, disorder effects, magnetotransport, spintronics, quantum pumping, straintronics, and exciton dynamics. She has directed over 20 students across PhD, Master's, and undergraduate levels, including notable projects on full-shell hybrid nanowires and twisted bilayer graphene. Recent publications highlight advancements in Josephson junctions, Majorana detection, and topological superconductivity in full-shell nanowires. Awards include the Young Female Scientist 2021 from the Royal Academy of Sciences of Spain and Mastercard, and the 2022 Certamen Universitario 'Arquímedes' First Award as a tutor. She has secured significant grants from the Spanish government and European collaborations for projects on quantum materials and topological superconductivity. Principal Investigator for €139,150 Spanish government grant (PID2021-125343NB-I00) Lead on €5,000 ICMM-CSIC grant (2020-2021) Participant in €3.48M EU AndQC project (2019-2023)

Charles Rougéمشاهده پروفایل

مدرس ارشد

• Water Resource Systems
• Climate Change Adaptation
• Energy Transition
• +۹ مورد دیگر

Dr. Charles Rougé is a Senior Lecturer in Water Resilience at the Department of Civil and Structural Engineering, School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. He holds an MSc and PhD, and his career spans top institutions in France, the US, Canada, and the UK. 2018–present: University of Sheffield (Lecturer → Senior Lecturer) 2023–2026: Principal Investigator, EPSRC-funded project on water-energy systems under climate change and energy transition Research Focus: Modelling complex water resource systems to enhance resilience against climate change, with a growing emphasis on water-energy nexus challenges. His work integrates hydrology, power systems engineering, economics, and decision theory. Key Trends: 15 most recent articles span climate-perturbed hydrological models, water-energy system coupling, socio-hydrology applications, and transboundary water governance. Many showcase interdisciplinary approaches to water infrastructure flexibility and uncertainty quantification. Scientific Awards: 2019 Quentin Martin Best Practice Award (JWRPM) 2015 Editor's Citation for Excellence (WRR) Grants: EPSRC grant (UKRI) for 'Flexible design and operation of water resource systems' (2023–2026) Team Leadership: Leads the 'Water resilience' research group at Sheffield, mentoring early-career researchers in water system sustainability and low-carbon energy transition.

• Functional Analysis
• Quantum Systems with Boundary
• Quantum Control on Infinite Dimensional Systems
• +۵ مورد دیگر

Juan Manuel Pérez Pardo is an Associate Professor in the Department of Mathematics at Universidad Carlos III de Madrid, where he has been a faculty member since 2019, progressing from Assistant Professor to his current position as Associate Professor since December 2022. His academic journey includes postdoctoral research at prestigious institutions including the Istituto Nazionale di Fisica Nucleare in Naples, Italy, and the Instituto de Ciencias Matemáticas in Madrid. Dr. Pérez Pardo earned his PhD in Mathematics from Universidad Carlos III de Madrid in 2013, following a Master's degree in Mathematical Engineering from the same institution and a Master's degree in Theoretical Physics from Universidad Complutense de Madrid. His undergraduate studies were in Physics at Universidad Complutense de Madrid. His research focuses on the intersection of functional analysis and quantum physics, particularly in three main areas: Functional Analysis : Applying functional analytical tools to quantum systems, with emphasis on quadratic forms associated with differential operators and evolution equations in Hilbert spaces. Quantum Systems with Boundary : Studying quantum dynamics when boundaries are present, combining operator theory, spectral theory, and differential geometry. Quantum Control on Infinite Dimensional Systems : Developing mathematical theory for controlling quantum systems that are infinite dimensional in nature, relevant to quantum computation technologies. His publication record shows a strong focus on quantum control theory, self-adjoint extensions of differential operators, and the mathematical foundations of quantum mechanics. Recent work (2022-2025) has concentrated on stability of non-autonomous Schrödinger equations, quantum controllability, and relativistic quantum systems. Dr. Pérez Pardo has received several prestigious awards including the Juan de la Cierva Fellowship and the QUITEMAD+ Postdoctoral Fellowship. His work on boundary dynamics driven entanglement was highlighted in Europhysics News and tagged as IOPselect by the Institute of Physics. He actively mentors students at all levels, currently supervising PhD candidate Ángel Aitor Balmaseda Martín on "Quantum Control at the Boundary." He has also supervised numerous Master's and Bachelor's students on topics ranging from numerical solutions of quantum control problems to modeling Josephson junctions. Dr. Pérez Pardo is a key member of the Q-Math Research Group at UC3M and has organized multiple international workshops on Information Geometry, Quantum Mechanics, and Applications. He also serves on the editorial board of the International Journal of Geometric Methods in Modern Physics.

Endre Süliمشاهده پروفایل

استاد

• Numerical Analysis of Partial Differential Equations
• Finite Element Methods
• Computational Modeling of Fracture
• +۴ مورد دیگر

Endre Süli is Professor of Numerical Analysis at the University of Oxford, where he has maintained a distinguished academic career since 1985. He currently serves as Fellow and Tutor in Mathematics at Worcester College and Supernumerary Fellow at Linacre College. His progression at Oxford includes University Lecturer in Numerical Analysis (1985-1996), Reader in Numerical Analysis (1996-1999), and Professor of Numerical Analysis (1999-present). Süli completed his B.Sc. in Mathematics at the University of Belgrade (1974-1978), followed by an M.Sc. in Mathematics (1978-1980). As a British Council Visiting Student, he studied at Reading University and Oxford University in 1983/84, earned his Ph.D. from the University of Belgrade in 1985, and received his M.A. from Oxford University in the same year. Professor Süli's research centers on numerical analysis of nonlinear partial differential equations with applications across multiple scientific domains. His work spans free-discontinuity problems and computational modeling of fracture; finite element methods; Navier-Stokes-Fokker-Planck systems; adaptive algorithms with a-posteriori error control; implicitly constituted material models; and discontinuous finite element methods. His research bridges theoretical mathematics with practical computational approaches for complex physical phenomena. Recent publications (2024-2025) demonstrate Süli's continued leadership in numerical analysis, with focus areas including fractional calculus, stochastic PDEs, and advanced finite element techniques. His work shows strong interdisciplinary connections between mathematical analysis, fluid dynamics, and materials science, addressing challenging problems in polymeric fluids, porous media, and capillary flow modeling. Professor Süli's distinguished career has been recognized with numerous prestigious honors: Invited Speaker at the International Congress of Mathematicians, Madrid (2006) Fellow of the Institute of Mathematics and its Applications (2007) Foreign Member of the Serbian National Academy of Sciences and Arts (2009) Fellow of the European Academy of Sciences (2010) IMA Service Award (2011) SIAM Fellow (2016) Member of the Academia Europaea (2020) London Mathematical Society Naylor Prize and Lectureship (2021) Fellow of the Royal Society (2021) As an educator, Süli has received the Oxford University Teaching Excellence Award (2009) and the Mathematical Institute Teaching Award (2013). He has supervised numerous PhD students and postdoctoral researchers throughout his career, though specific names aren't documented in the available materials. His research has been supported by various grants enabling work on computational methods for partial differential equations. Süli maintains active service to the mathematical community through editorial boards and professional organizations. Professor Süli is affiliated with the Numerical Analysis research group and the Oxford Centre for Nonlinear PDE at the Mathematical Institute. These research centers provide a collaborative environment for theoretical and applied work on partial differential equations. His research often involves interdisciplinary collaborations with physicists, engineers, and computational scientists to develop and analyze numerical methods for complex physical phenomena.

Simon Rowlandمشاهده پروفایل

استاد

• Electrical Insulation Materials
• Polymeric Insulation Systems
• Asset Management for Power Systems
• +۴ مورد دیگر

Simon Rowland is a Professor of Electrical Materials at the University of Manchester's Department of Electrical and Electronic Engineering, affiliated with the High Voltage Group. He previously served as Head of School (2015-2019) and transitioned from industrial R&D roles at STC, BICC, and Corning Cables to academia in 2003. His expertise centers on electrical insulation materials, polymeric systems, and asset management for power systems. He leads research in the UK’s largest HV laboratory, focusing on solid insulation interfaces and funded by National Grid and EPSRC. He holds 13 patents, primarily in overhead line technology, and is a Fellow of the IEEE and IET. Education: BSc, PhD, FHEA, FIET, FIEEE. Research interests include dielectric reliability, overhead line design, and low-current arcs. Collaborations span materials science and engineering disciplines. Recent awards include the 2025 IEEE Eric O. Forster Distinguished Service Award and 2022 Bhattacharyya Award Finalist. Professional roles include Treasurer of the IEEE Dielectrics and Electrical Insulation Society (2020–present).

• Singular Stochastic Optimal Control
• Optimal Stopping and Free-Boundary Problems
• Stochastic Games
• +۶ مورد دیگر

Giorgio Ferrari is a Full Professor for Mathematical Finance at the Institute for Mathematical Economics (IMW), Faculty of Economics, Bielefeld University. His research bridges stochastic control theory with applications in economics, finance, actuarial science, and epidemiology. Education: B.Sc. and M.Sc. in Physics and Mathematical Physics from the University of Rome La Sapienza, Ph.D. in Mathematics for Economic-Financial Applications (2012). Academic Appointments: Post-Doctoral Researcher (2012–2015), Substitute Full Professor (2015), Junior Professor (W1) (2016–2017), Associate Professor (2017–2023), and Full Professor (2023–present) at Bielefeld University. Research Interests focus on Singular Stochastic Control , Optimal Stopping , and Stochastic Games , with applications to economic policy, financial markets, and epidemic modeling. His work extends to Mean-Field Games for large-scale strategic interactions and Free-Boundary Problems for investment decision-making under uncertainty. Scientific Contributions include groundbreaking publications in Stochastic Processes and their Applications , Mathematical Finance , and SIAM Journal on Control and Optimization . His research projects, such as the DFG SFB 1283 subproject C4 and the Research Training Group 2865 , address uncertainty in dynamic economies through game-theoretic and stochastic frameworks. Notable Awards: AMASES Best Young Researcher Paper (2014), YITP Research Prize (2017), and multiple research fellowships from the University of Padova. Leadership: Director of the Bielefeld Graduate School in Theoretical Sciences (2023–present) and Principal Investigator in major DFG-funded initiatives.

Olga Barreraمشاهده پروفایل

مدرس ارشد

• Mechanical Engineering
• Computational Mechanics
• Biomechanics
• +۱۲ مورد دیگر

Dr. Olga Barrera is a Reader in Mechanical Engineering at Oxford Brookes University, School of Engineering, Computing and Mathematics. She serves as a year tutor for undergraduate engineering programs and has previously held a Research Fellow position at the Department of Engineering Science, University of Oxford (2008–2017), and a consultancy role at China Medical University Hospital, Taiwan. Her academic work spans teaching, supervision, and leading a research lab focused on image-based multi-physics modeling of multi-phase materials. Reader in Mechanical Engineering, Oxford Brookes University (2018–present) Research Fellow, Department of Engineering Science, University of Oxford (2008–2017) Consultant, Department of Medical Research, China Medical University Hospital, Taiwan Her research interests lie at the intersection of computational mechanics, biomechanics, and materials science, with a focus on soft load-bearing tissues such as the knee meniscus. She integrates advanced imaging (micro-CT), experimental testing, and fractional calculus-based modeling to study tissue behavior and bio-inspired materials. Her work also extends to hydrogen embrittlement in metals and innovative finite element methods. Her recent publications (2023–2025) reveal a strong trend in image-driven modeling of biological tissues, fractional viscoelasticity, and bioinspired engineering solutions. Key themes include the mechanical behavior of meniscal tissue, fluid-structure interaction, anomalous transport in porous media, and deep learning applications in tissue mimicry. These works are published in high-impact journals such as Philosophical Transactions of the Royal Society A , Materials & Design , and Acta Biomaterialia . Scientific awards and grants highlight her international recognition and research leadership: Marie Skłodowska-Curie Individual Fellowship (€190K, 2018–2020) EPSRC HemS grant (Co-I, £340K, 2014–2017) Research Excellence Award, Oxford Brookes (2021–2022, £20K) Visiting Professor Scholarship, France (2023, €4K) FNR Luxembourg Crucible Grant (€8K, 2021–2022) She has supervised numerous postgraduate students including PhD and MSc researchers, and has advised over 30 undergraduate final-year projects across Oxford and Oxford Brookes. She has led or co-led significant research grants from EPSRC, FNR, Rolls-Royce, and the Oxford Orthopaedic Engineering Centre. Her lab, the Oxford image-based multi-physics modelling of multi-phase materials, collaborates with institutions in Italy, Luxembourg, and France. She is an active member of the Materials Processing and Modelling (MPM) research group.

• Representation Theory
• Lie Groups
• p-adic Groups
• +۵ مورد دیگر

Dan Ciubotaru is Professor of Mathematics at the University of Oxford's Mathematical Institute and Diana Brown Fellow and Tutor in Pure Mathematics at Somerville College. He completed his PhD at Cornell University in 2004 and maintains active research and teaching roles within the university's Mathematical, Physical and Life Sciences Division. His educational background includes: PhD in Mathematics, Cornell University (2004) Ciubotaru specializes in representation theory of reductive Lie groups and p-adic groups, with core focus areas including the unitary dual, local Langlands correspondence, affine Hecke algebras, Coxeter groups, and Dirac operators. His work bridges algebraic structures with harmonic analysis and number theory, particularly through the study of wavefront sets and unipotent representations. This research contributes significantly to understanding automorphic forms and geometric aspects of the Langlands program. Analysis of his 2022-2025 publications reveals concentrated advancement in wavefront set theory for p-adic groups, with recurring themes in unipotent representations, Langlands parameters, and symplectic Dirac operators. His work consistently connects representation-theoretic structures with geometric and arithmetic properties, demonstrating strong collaboration networks across international mathematics communities. His scientific recognition includes: Diana Brown Fellowship (Somerville College) MPLS Teaching Award (2017) Ciubotaru has secured significant research funding as Principal Investigator for EPSRC grants including "New Horizons" EP/V046713/1 (2021-2023) and EP/N033922/1 (2016-2020). He serves on editorial boards for Documenta Mathematica (2015-2024) and Quarterly Journal of Mathematics (2017-present), and teaches advanced courses including "Representations of semisimple Lie algebras" (C2.3). While no dedicated research labs are specified, his extensive co-authorship with scholars like Mason-Brown, Okada, and Barbasch indicates active participation in global representation theory networks, particularly through collaborations on p-adic group representations and Langlands program applications.

Chandrika Sadanandمشاهده پروفایل

استادیار

• Low Dimensional Topology
• Geometry
• Hyperbolic Geometry
• +۳ مورد دیگر

Chandrika Sadanand is an Assistant Professor in the Department of Mathematics at Bowdoin College. She holds a PhD from Stony Brook University and a BS from the University of Toronto. Her research focuses on low-dimensional topology and geometry, specifically exploring curves on surfaces, hyperbolic geometry, billiards, translation surfaces, and 3-manifolds. She has held postdoctoral positions at the University of Illinois Urbana Champaign, Technion, and Hebrew University of Jerusalem. Dr. Sadanand teaches courses in mathematical reasoning, geometry, and topology. Her recent courses include MATH 2020 (Introduction to Mathematical Reasoning), MATH 2404 (Geometry), and MATH 3402 (Topology). She has also mentored undergraduate research projects on flat surfaces and participated in outreach activities through programs like the Stony Brook Math Summer Camp and WISE. Her research contributions include studies on translation surfaces of infinite type, billiards dynamics, and geometric structures. She has contributed to innovative conferences like the Nearly Carbon Neutral Geometry and Topology Conferences through video presentations. Her work bridges pure mathematics with computational methods, addressing questions in geometric topology and dynamical systems.

Juanita Duque-Roseroمشاهده پروفایل

عضو هیئت علمی

• Computational Number Theory
• Arithmetic Geometry
• Modular Curves
• +۴ مورد دیگر

Juanita Duque-Rosero is a Research Assistant Professor at Boston University, specializing in computational number theory and arithmetic geometry. She collaborates with Jennifer Balakrishnan on explicit Chabauty methods and triangular modular curves. Her research focuses on rational points on curves, modular curves, and p-adic heights. Education: PhD from Dartmouth College (2023, advised by John Voight), Masters from Colorado State University (2019, advised by Rachel Pries), and undergraduate degree from Universidad de los Andes. Research interests include arithmetic properties of curves, geometric quadratic Chabauty, and computational aspects of modular forms. She has contributed to databases of Hilbert modular surfaces and studies of Artin-Schreier curves. Her recent articles explore invariants of curves, p-adic heights, and geometric methods in number theory. Talks include presentations at CIRM, IPAM, and Texas A&M. Teaching includes courses like Modern Algebra and Graph Theory at Boston University, and calculus courses at Dartmouth and Colorado State. She mentors students in algebraic geometry and number theory through directed reading programs. She advocates for equitable mathematics education through Federico Ardila’s axioms and participates in outreach activities. A creative hobby is mathematical origami, leading a club at Colorado State University.

Emily J. Kingمشاهده پروفایل

دانشیار

• Frame Theory
• Harmonic Analysis
• Algebraic Combinatorics
• +۷ مورد دیگر

Emily J. King is a tenured Associate Professor in the Department of Mathematics at Colorado State University (CSU), College of Natural Sciences. She previously held a faculty position at the University of Bremen and has been actively contributing to the mathematical community through research, mentorship, and academic leadership. Her primary research interests include Frame Theory , Harmonic Analysis , Algebraic and Geometric Combinatorics , and Data Science , with applications in signal and image processing, Earth science, and artificial intelligence. She integrates deep mathematical theory with practical data analysis challenges. Her recent scholarly output reflects a strong focus on equiangular tight frames, combinatorial structures in frames, mathematical models for attention mechanisms, and applications to satellite imagery and cloud processes. Her work often bridges pure and applied mathematics, with a growing emphasis on interpretable AI and data science foundations. Dr. King has supervised several doctoral and master’s students, including Lander ver Hoef, Sören Schulze, Harley Meade, and Kristina Moen. She is a co-PI on an NSF grant focused on cloud processes and has been recognized for mentoring excellence, as evidenced by her student Emma Slack receiving the inaugural Outstanding Undergraduate in Mathematics award. NSF Grant Co-PI (2024) Outstanding Undergraduate in Mathematics award (mentored student, 2023) She is a founding co-organizer of the international Codes and Expansions (CodEx) Seminar and has organized sessions at major conferences such as SIAM AG and the Joint Mathematics Meetings. She frequently delivers invited talks at universities and research institutes worldwide, including upcoming presentations at the Air Force Institute of Technology, SIAM AG25, and TU Clausthal. Dr. King’s academic lineage includes John Benedetto as her mathematical advisor and Chandler Davis as her mathematical grandfather. She is actively involved in interdisciplinary research, particularly in marine data science, having co-spoken for the Helmholtz School for Marine Data Science (MarDATA).

• Machine Learning
• Artificial Intelligence
• Data Science
• +۵ مورد دیگر

Pan Xu is a tenure-track assistant professor with joint appointments in the Department of Biostatistics & Bioinformatics, Department of Computer Science, and Department of Electrical & Computer Engineering at Duke University's Pratt School of Engineering. Prior to joining Duke, he was a Postdoctoral Scholar Research Associate at the California Institute of Technology, and he earned his Ph.D. in Computer Science from UCLA. His research bridges theoretical foundations with practical applications in machine learning and artificial intelligence. Dr. Xu's research focuses on developing computationally- and data-efficient machine learning algorithms with strong theoretical guarantees, particularly in reinforcement learning, optimization, and high-dimensional statistics. His work addresses two fundamental challenges in sequential decision-making: efficient exploration with minimal interactions and robustness against distributional shifts. His research spans theoretical algorithm design, practical implementation, and real-world applications in bioinformatics and healthcare. His publication record demonstrates consistent high-impact contributions to top-tier conferences including ICML, NeurIPS, ICLR, AAAI, and AISTATS. The research trends show a progression from foundational work in non-convex optimization and multi-armed bandits toward increasingly sophisticated frameworks for robust reinforcement learning, with particular emphasis on distributional robustness, efficient exploration strategies, and practical applications. His work often bridges theoretical guarantees with empirical validation. NSF award on approximate sampling based exploration for sequential decision making Whitehead Scholar award from Duke University School of Medicine PIMCO Postdoctoral Fellowship in Data Science UCLA Outstanding Graduate Student Research Award Rising Stars in Data Science by University of Chicago Best Paper Award for Queer In AI: A Case Study in Community-Led Participatory AI at FAccT 2023 Featured Certification for Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits at TMLR Oral Presentation award at AAAI 2024 Dr. Xu actively mentors students and researchers, seeking highly motivated individuals with strong mathematical backgrounds for Ph.D. programs in Biostatistics & Bioinformatics, Computer Science, and Electrical & Computer Engineering at Duke. He has received multiple research grants including an NSF award on approximate sampling based exploration for sequential decision making. His service to the academic community includes roles as area chair for NeurIPS, ICML, ICLR, and AISTATS, as well as action editor for Transactions on Machine Learning Research. His research group develops algorithms that address fundamental challenges in sequential decision-making, with applications spanning healthcare, bioinformatics, and multi-agent systems. Current research directions include distributionally robust reinforcement learning, efficient exploration strategies, and applications of graph neural networks to biological problems.

• Model Theory
• Mathematical Logic
• Algebra
• +۴ مورد دیگر

David M Evans holds the position of Chair in Pure Mathematics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His academic career spans several decades with continuous research contributions in mathematical logic and its interdisciplinary applications. Professor Evans' research focuses on the theoretical foundations and practical applications of Model Theory, with particular emphasis on: Stability theory and its generalizations within model-theoretic frameworks Hrushovski constructions and their geometric properties Interactions between model theory, algebra, and combinatorics Automorphism groups of infinite structures Ramsey properties in sparse graphs and metric spaces His publication record demonstrates consistent innovation in geometric model theory, with recent work exploring amalgamation properties in measured structures, simplicity of automorphism groups, and EPPA (Extension Property for Partial Automorphisms) in various mathematical structures. His research bridges abstract model-theoretic concepts with concrete combinatorial and algebraic applications, particularly in the study of homogeneous structures and their automorphism groups. Professor Evans has supervised numerous doctoral students including D. G. D. Gray, Reinhold Konnerth, Herwig Nuebling, Marco Antonio Semana Ferreira, Yibei Li, and Robert Sullivan. His research has been supported by grants such as 'Model theory of generic structures and simple theories' and the 'Workshop on Pure Model Theory,' reflecting the significance of his contributions to the field.

• Geometric Calculus of Variations
• Quantitative Aspects of Manifold Topology
• Global Riemannian Geometry

Alexander Nabutovsky is a Professor in the Department of Mathematics at the University of Toronto. His research focuses on the intersection of Geometric Calculus of Variations and Quantitative Aspects of Manifold Topology , with particular emphasis on Global Riemannian Geometry . He works on problems involving geodesics, minimal surfaces, and algorithmic methods in topology. His publications explore topics such as curvature-free bounds for minimal surfaces, complexity of Riemannian structures, and logic phenomena in geometric functionals. Key themes in his work include the study of geodesic nets, quantitative Morse theory, and the interplay between metric geometry and topological invariants. He has collaborated extensively with Regina Rotman and Shmuel Weinberger, producing foundational results in metric geometry and computational topology. Dr. Nabutovsky's work often bridges pure mathematics with applications in quantum gravity and algorithmic unsolvability problems. He has contributed to understanding the fractal nature of moduli spaces of Riemannian metrics and developed methods for estimating geodesic lengths under various topological constraints.