Find Academic Supervisors

• Optimal Transport
• Metric Measure Spaces
• Partial Differential Equations
• +4 more

Luca Tamanini is a Tenure-Track Assistant Professor (RTDb) at Università Cattolica del Sacro Cuore in Brescia, Italy. He holds the Italian Habilitation (Abilitazione Scientifica Nazionale) as Associate Professor in sector 01/A3 (Mathematical Analysis, Probability and Statistics). His research focuses on optimal transport theory, metric measure spaces (especially RCD spaces), and their applications to PDEs, stochastic analysis, and functional inequalities. Research interests include: Entropic optimal transport and Sinkhorn algorithms Geometric and analytic properties of RCD spaces Hamilton-Jacobi equations in non-smooth settings Functional inequalities and Markov semigroups Large deviations and stochastic processes His recent work explores stability of entropic plans, Hessian estimates for Sinkhorn potentials, and geometric interpretations of optimal transport divergences. Key contributions include advancements in semiconcavity theory and applications to algorithm convergence rates. Awards: Italian Habilitation for Associate Professorship (2023). Future activities include research visits to Université Paris Saclay (July 2025) and Universität Bonn (July 2025), and participation in specialized conferences.

• Geometric Measure Theory
• Calculus of Variations
• Differential Geometry
• +3 more

Silvano Delladio is an Associate Professor at the Department of Mathematics, Università di Trento. His research focuses on geometric measure theory, calculus of variations, and differential geometry, with a particular emphasis on rectifiability, real analysis, and integral curvature bounds. He has published extensively on topics such as rectifiability criteria for sets and graphs, properties of Lipschitz maps, and applications of geometric measure theory to variational problems. His work often addresses questions related to smoothness conditions, functional spaces, and curvature energy. Notable contributions include studies on C^2 and C^3 rectifiability, non-homogeneous blow-up analysis, and the properties of integral currents. Delladio has presented seminars on rectifiability topics and participated in workshops like the ERC-Workshop on Geometric Measure Theory and Analysis in Metric Spaces.

Patrik KnopfView profile

Lecturer

• Partial Differential Equations
• Mathematical Physics
• Optimal Control Theory
• +3 more

Dr. Patrik Knopf is a Lecturer at the University of Regensburg, Faculty for Mathematics. He holds a Dr. rer. nat. habil. (Habilitation) from the University of Regensburg (2024) and a PhD (Dr. rer. nat.) from the University of Bayreuth (2017). His research focuses on partial differential equations, optimal control theory, and mathematical physics, with applications to materials science and fluid dynamics. Notable achievements include the 2024 Richard von Mises Prize from the GAMM. He has conducted research visits at the Illinois Institute of Technology (2019) and Fudan University (2025). Knopf leads a research team and oversees a DFG-funded doctoral position. His work spans topics such as Cahn-Hilliard equations with dynamic boundary conditions, phase-field methods, and plasma control via Particle-In-Cell methods. Education: Habilitation (2024): University of Regensburg PhD (2017): University of Bayreuth M.Sc. (2013), B.Sc. (2011): University of Bayreuth Awards: Richard von Mises Prize (2024) Grants: DFG grant for a doctoral student DAAD-funded visit for Dr. Sema Yayla (2024) Research Interests: Phase separation dynamics, optimal control of PDEs, fluid-structure interactions, and numerical methods for kinetic equations.

• Medical Imaging
• Image Restoration
• Machine Learning
• +3 more

Elena Morotti is an Assistant Professor at the Department of Political and Social Sciences, University of Bologna since 2021. She holds a Master's Degree in Mathematics from Bologna and a PhD in Applied Mathematics from the University of Padova (2018). Previously, she was a research fellow at the Department of Computer Science and Engineering, Bologna. Her research focuses on algorithms for medical image restoration/reconstruction using regularized inverse problem formulations, variational tools, and neural networks. She also explored Virtual Reality technologies (2018–2020). She co-founded the Learning and Optimization for Imaging in Bologna (LOIBO) group and is affiliated with the Virtual and Augmented Reality Laboratory (VARLAB) and Computational Social Science Center (CssC). In 2022, she collaborated via the Academy of Excellence’s Networks, Information and Digital Society initiative with Luca Calatroni (I3S) and R.M. Dessi (CEPAM) on the Imag’In CNRS PRIME project, restoring medieval Alpine Arc chapels’ murals. She presented her work in a 2022 Forum Numerica seminar.

Yura MalitskyView profile

Researcher

• Convex Optimization
• Variational Inequalities
• Nonlinear Analysis
• +5 more

Yura Malitsky is a postdoctoral researcher at Graz University of Technology's Institute of Computer Graphics and Vision, working under the supervision of Prof. Thomas Pock. He earned his Master's in Applied Mathematics from Kyiv National University in 2012 and completed his PhD in 2015 on projection methods for variational inequalities and composite optimization problems. Education: MS in Applied Mathematics (Kyiv National University, 2012), PhD in Optimization (2015) Affiliation: Graz University of Technology, Institute of Computer Graphics and Vision Academic Rank: Researcher His research focuses on convex optimization, variational inequalities, and nonlinear analysis, with applications to machine learning and signal processing. His work includes developing adaptive gradient methods, distributed optimization algorithms for ring networks, and novel approaches to stochastic variance reduction. Recent publications explore entropic mirror descent, Riemannian optimization, over-the-air computation for distributed systems, and improvements to primal-dual methods. He has contributed to advancements in resolvent splitting techniques and forward-reflected-backward methods for monotone operators. Malitsky's research bridges theoretical optimization frameworks with practical implementations in decentralized systems and high-dimensional learning problems. His work demonstrates significant technical contributions to algorithm design and convergence analysis.

• Optimization
• Statistics
• Data Science
• +3 more

Tyler Maunu is an Assistant Professor of Mathematics at Brandeis University, affiliated with the Department of Mathematics and the Benjamin and Mae Volen National Center for Complex Systems. His research focuses on statistical methodologies, optimization algorithms, machine learning, and their applications to computer vision and data science. He holds a Ph.D. in Mathematics from the University of Minnesota-Twin Cities, alongside multiple advanced degrees from the same institution. Maunu's research advances robust subspace recovery and optimal transport, emphasizing scalable and privacy-aware techniques. His work bridges theoretical foundations (e.g., non-convex optimization landscapes) with practical applications in data recovery and generative modeling. Notable areas include Bures-Wasserstein geometry, stochastic gradient methods, and adversarial robustness in high-dimensional data analysis. His articles span topics like preconditioned Langevin Monte Carlo, optimal transport barycenters, and scalable graph matching algorithms. While no explicit awards are cited, his contributions reflect ongoing innovation in computational statistics and optimization. His affiliation with the Volen Center underscores interdisciplinary engagements in complex systems research.

Anna TriandafyllidouView profile

Professor

• Migration Governance
• Migrant Integration
• Nationalism Studies
• +3 more

Dr. Anna Triandafyllidou is a Professor and Canada Excellence Research Chair in Migration and Integration at Toronto Metropolitan University's Sociology Department. Her research focuses on migration governance, integration, nationalism, and cultural diversity. She leads over 30 projects addressing migrant agency, global migration drivers, and governance frameworks. Notable initiatives include the Migrant Integration in the Mid-21st Century program, exploring technological impacts on integration. She serves as Editor-in-Chief of Journal of Immigrant and Refugee Studies and chairs the IMISCOE Editorial Committee. Educated at Panteion University (BA) and the European University Institute (PhD), she has held visiting roles at the College of Europe (2002–2018). Her recent work examines digital nomadism, coerced return policies, and pandemic-driven nationalism. She advises on regularization programs in Canada, drawing insights from European precedents. Key contributions include Handbook of Migration and Globalisation (2024), analyzing migration’s intersection with globalization. Her research bridges theoretical inquiry with practical policy, emphasizing migrant agency and socio-technological transformation.

Florin ISAIAView profile

Associate Professor

• Nonlinear Analysis
• Partial Differential Equations
• Sobolev Spaces
• +3 more

Florin ISAIA is an Associate Professor at the Department of Mathematics and Computer Science within the Faculty of Mathematics and Computer Science at the Technical University of Braşov. His research focuses on nonlinear analysis, elliptic partial differential equations, integral equations, and Sobolev spaces. He holds an office in Building P, Room PP11, and can be reached via email at florin.isaia@unitbv.ro . His academic work emphasizes theoretical contributions to functional analysis, particularly in the context of superposition operators between Sobolev spaces. Key research topics include the p-Laplacian equations, Faà di Bruno formulas in supercritical and subcritical cases, and generalized Pohožaev identities. He has also explored applications in thermoelasticity and nonlinear dynamical systems, such as the study of cylindrical tubes under torsion and hybrid oscillator models. Florin ISAIA's publications span reputable journals like Nonlinear Analysis , Houston Journal of Mathematics , and Advanced Nonlinear Studies . His work often bridges abstract mathematical analysis with applied problems in structural mechanics and control systems. Leveraging advanced analytical methods, his research addresses critical questions in operator continuity, nonexistence results for certain PDEs, and the interplay between thermal and mechanical stresses in composite materials. He maintains an active profile in the academic community, contributing to the theoretical foundations of nonlinear dynamics and functional spaces.

• Geometric Analysis
• Partial Differential Equations (PDEs)
• Optimal Transport
• +4 more

Elia Bruè is a researcher at the Scuola Normale Superiore, specializing in geometric analysis, partial differential equations (PDEs), and optimal transport. His work bridges differential geometry, metric measure spaces, and fluid dynamics, with a focus on Ricci curvature, stability, and non-uniqueness in PDE solutions. He has contributed to resolving conjectures like the Milnor Conjecture and advancing understanding of Euler/Navier-Stokes equations. Education: Completed his Ph.D. in Mathematics at Scuola Normale Superiore (2020) with a thesis on 'Regularity of Lagrangian Flows over RCD*(K,N) Spaces.' Research Interests: Explores geometric structures in non-smooth spaces, fluid dynamics instabilities, and optimal transport applications. Key areas include RCD(K,N) spaces, Ricci curvature bounds, and transport equations with Sobolev velocity fields. Recent Work Trends: His 2023–2025 articles address topological stability in spaces with Ricci curvature bounds, non-uniqueness in fluid dynamics, and counterexamples to geometric conjectures. Collaborations with A. Naber, M. Colombo, and D. Semola highlight interdisciplinary research. Grants/Advising: No explicit grants listed, but his involvement in workshops (e.g., 'Perspectives in Geometric Analysis,' 'Boundary Analysis for Dispersive Fluids') indicates active participation in academic networks. No advisees listed. Labs/Teams: Engaged in research groups focused on geometric analysis and PDEs at Scuola Normale Superiore and international collaborations.

Aldo PratelliView profile

Professor

• Calculus of Variations
• Geometric Measure Theory
• Mathematical Analysis
• +3 more

Aldo Pratelli is a Full Professor at the University of Pisa, affiliated with the Department of Mathematics. His research focuses on Calculus of Variations, Geometric Measure Theory, and Optimal Transport, with applications to isoperimetric problems, functional inequalities, and non-local energy minimization. He has contributed to foundational work on the quantitative isoperimetric inequality, Steiner properties of clusters, and regularity theory in geometric analysis. Pratelli has taught courses in Mathematical Analysis, Advanced Analysis, and Calculus of Variations at both undergraduate and graduate levels. His teaching spans topics such as BV functions, Fourier analysis, and functional spaces, with a focus on rigorous theoretical foundations. Recent courses include 'Analisi Matematica 2' for Mathematics students and 'Calcolo delle Variazioni B' for master's students. His research output includes over 77 publications, many addressing variational problems, geometric inequalities, and optimal transport. Notable contributions include studies on Cheeger constants, minimal clusters in Riemannian manifolds, and quantitative stability estimates for isoperimetric inequalities. He has participated in numerous international conferences and organized events on calculus of variations and geometric measure theory. Pratelli's work bridges pure and applied mathematics, with theoretical results often applied to problems in physics and engineering. His current interests include non-local interaction energies and the approximation of BV homeomorphisms by diffeomorphisms.

Valentino MagnaniView profile

Associate Professor

• Differential Geometry
• Geometric Analysis
• Sub-Riemannian Geometry
• +5 more

Valentino Magnani is an Associate Professor in the Department of Mathematics at the University of Pisa, Italy. His research focuses on geometric analysis, sub-Riemannian geometry, and geometric measure theory, with an emphasis on topics such as area formulas, rectifiability, and the properties of measures in homogeneous groups. He has authored over 50 publications in prestigious journals like the Journal of Geometric Analysis, Advances in Mathematics, and Calculus of Variations and Partial Differential Equations. His work explores the interplay between differential geometry and analysis in non-Euclidean settings, including studies on submanifolds, Sobolev spaces, and coarea formulas. Magnani has organized and spoken at numerous international conferences, such as the 'Three Days in Sub-Riemannian Geometry' and 'Geometric Measure Theory in Trento.' He also contributes to academic activities through teaching advanced courses on geometric analysis and metric spaces, including PhD-level lectures on topics like area theory in homogeneous groups. Key research interests include the Michor-Mumford conjecture, symmetry properties in geometric structures, and the application of rough calculus to level sets in Heisenberg groups. His contributions have advanced understanding of measure-theoretic principles and geometric properties in stratified Lie groups and sub-Riemannian manifolds.

• Calculus of Variations
• Geometric Measure Theory
• Partial Differential Equations
• +3 more

Michael Novack is an Assistant Professor at Louisiana State University. His research focuses on calculus of variations, geometric measure theory, and partial differential equations. He previously held postdoctoral positions at Carnegie Mellon University, the University of Texas at Austin, and the University of Connecticut. He earned his Ph.D. from Indiana University. His work addresses problems in geometric analysis, including free boundary regularity, isoperimetric inequalities, and liquid crystal models. Key topics include phase transitions in nematics, smectic liquid crystal configurations, and capillarity theory. Recent contributions involve rigorous analysis of Plateau’s laws via Allen-Cahn equations and infinite double bubble theorems. Notable publications explore energy minimization in liquid crystals, regularity criteria for hypersurfaces, and Wasserstein distance optimizations. His research bridges pure and applied mathematics, with applications in materials science and geometric modeling. He has delivered specialized lectures on Γ-convergence and contributed to workshops at Oberwolfach.

Leonid V. KovalevView profile

Professor

• Geometric Mapping Theory
• Metric Geometry
• Functional Analysis
• +6 more

Leonid V. Kovalev is a Professor and Associate Chair of the Department of Mathematics at Syracuse University, within the College of Arts and Sciences. His research focuses on geometric mapping theory, metric space analysis, complex analysis, and potential theory. He holds leadership roles in undergraduate mathematics education and has contributed to the field through numerous NSF-funded projects. Education details are not explicitly listed, but his academic trajectory is evident through his extensive research output and faculty position. His work bridges pure mathematics disciplines such as geometric analysis, functional analysis, and complex variables, with applications to variational problems and harmonic mappings. Recent research emphasizes topics like Lipschitz properties in metric spaces, trigonometric polynomials, and geometric variational problems. His articles explore theoretical foundations and computational aspects of these areas, often intersecting with Fourier analysis and operator theory. Grants: NSF-funded projects include 'Lipschitz Analysis in Normed and Metric Spaces' (2018–2022) and 'NEAM 2019: The 4th Northeastern Analysis Meeting' (2019–2020). Teaching: Courses include Functional Analysis, Numerical Methods, and Calculus for Business and Life Sciences. Service: Serves as Associate Chair for Undergraduate Studies and advises Mathematics majors/minors. Administers WeBWorK course platforms. Labs/Teams: Collaborates on projects involving geometric analysis and metric space theory through his research group and conference organizing activities.

• Time Series Analysis
• Extreme Value Theory
• Financial Modelling
• +5 more

Thomas Fung is a Senior Lecturer in Statistics at Macquarie University's School of Mathematical and Physical Sciences, serving as Director of Education and Deputy Course Director for the BSc program. He holds a PhD and B.Sc (Advanced Mathematics) from the University of Sydney. His research focuses on integer-valued time series analysis, extreme value theory, and financial modelling, addressing complex data issues like zero-inflation and heavy-tailedness. He teaches courses such as STAT1378 (Coding & Communication in Statistics) and actively supervises postgraduate students on projects like semiparametric models and climate data analysis. Key research projects include flexible models for count time series and improving financial time series analysis via Variance-Gamma processes. His work has been published in journals like Statistics and Probability Letters and Earth and Space Science . Awards include the 2023 Faculty of Science and Engineering Excellent Award for Educational Leadership and multiple Teaching Development Grants. He serves on editorial boards for the Australian and New Zealand Journal of Statistics and R Journal , and holds leadership roles in professional societies like the Statistical Society of Australia NSW Branch. His interdisciplinary collaborations span environmental science, public health, and criminology, reflecting his broad statistical expertise.

Francesco D'AngeloView profile

Researcher

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +3 more

Francesco D'Angelo is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences (IC) and the Institute of Computer Science and Communications Systems (IINFCOM). He is part of the Theory of Machine Learning Laboratory (TML) and enrolled in the Doctoral program in computer and communication sciences (EDIC) under the EPFL Doctoral School (EDOC). His research focuses on foundational aspects of machine learning, including sparse attention mechanisms, Bayesian neural networks, uncertainty estimation, and continual learning. He holds the position of Doctoral Assistant at the TML lab, where he contributes to advancing theoretical and practical applications of machine learning algorithms. Research Interests: Francesco's work bridges theoretical computer science with applied machine learning. His key areas include developing robust models for uncertainty quantification, improving generalization in overparameterized networks through regularization techniques like weight decay, and exploring the interplay between transformer architectures and causal structure induction. He also investigates methods to mitigate catastrophic forgetting in continual learning scenarios and applies Bayesian approaches to enhance out-of-distribution detection capabilities. Publications: His recent work explores topics such as sparse attention mechanisms in transformers, the necessity of weight decay in deep learning optimization, and Bayesian methods for uncertainty estimation. These contributions highlight his expertise in both foundational theory and practical algorithm design within the machine learning domain. Labs & Teams: As part of the TML lab, he collaborates on interdisciplinary projects at the intersection of machine learning theory and applications, contributing to advancements in neural network architectures and probabilistic modeling techniques.