Find Academic Supervisors

• Numerical Analysis
• Geometric Numerical Integration
• Structure-Preserving Algorithms
• +3 more

Elena Celledoni is a Professor of Mathematics at the Department of Mathematical Sciences, Norwegian University of Science and Technology (NTNU), where she has been employed since 2004. She leads the research group on differential equations and numerical analysis. Her academic background includes a Master’s degree (1993) and Ph.D. (1997) in mathematics from the Universities of Trieste and Padua, Italy, respectively. She has held postdoctoral positions at the University of Cambridge (UK), the Mathematical Sciences Research Institute (MSRI, Berkeley, CA), and NTNU. Her research focuses on numerical analysis, particularly structure-preserving algorithms for differential equations and geometric numerical integration. Recent work includes applications of neural networks in computational mechanics and data-driven modeling. She has co-authored over 100 peer-reviewed articles in journals such as Journal of Computational Physics , SIAM Journal on Scientific Computing , and Physica D . Her research interests span computational methods for dynamical systems, machine learning integration with numerical analysis, and geometric algorithms for shape analysis. She actively collaborates with international researchers, including contributions to conferences like NeurIPS and workshops on theoretical aspects of computational dynamics. Elena is a member of the editorial boards of Journal of Computational Dynamics and has organized workshops on structure-preserving integrators. Her work emphasizes preserving geometric properties in numerical methods, with applications in fluid dynamics, mechanical systems, and image processing.

• Immigration Policy
• Citizenship and Legal Status
• Social Inequality
• +4 more

Asad L. Asad is an Assistant Professor of Sociology at Stanford University and a faculty affiliate at the Center for Comparative Studies in Race and Ethnicity (CCSRE). His research agenda examines how institutional categories like citizenship and legal status shape inequality through immigration enforcement, health outcomes, and social control mechanisms. B.A. in Political Science and Spanish, University of Wisconsin A.M. and Ph.D. in Sociology, Harvard University His work bridges multiple subfields, including: Immigration Policy: Analysis of deportation systems and their societal impacts Social Determinants: Linking legal status to health disparities Urban Sociology: Residential strategies under surveillance Legal Sociology: Judicial decision-making in immigration courts Population Studies: Longitudinal analysis of Latino communities Recent publications (2024-2025) expand on temporal trends in deportation fears, spatial dimensions of immigration policing, and advocacy perspectives reshaping policy frameworks. Earlier empirical work (2018-2019) established foundational connections between undocumented status and health outcomes, while his 2023 book Engage and Evade received multiple academic awards. Scientific recognition includes awards from: American Political Science Association American Sociological Association Order of the Coif Mellon Mays Faculty Mentor Award Stanford Dean’s Teaching Award Research funding has been secured through the National Science Foundation and Russell Sage Foundation. He teaches courses on race, ethnicity, immigration, and research methodology.

Vasilis SarhosisView profile

Professor

• Structural Engineering
• Masonry Structures
• Structural Health Monitoring
• +7 more

Professor Vasilis Sarhosis is a Professor of Resilient Structures and Infrastructure at the School of Civil Engineering, University of Leeds, within the Faculty of Engineering and Physical Sciences. He also serves as a visiting Professor at Southeast University, Nanjing, China, and is a CDRI (Coalition for Disaster Resilience Infrastructure) Fellow. His academic credentials include multiple degrees from the University of Leeds: a Ph.D. in Computational modelling of low bond strength masonry (2012), an MSc in Sustainable Waste Management (2006), an MSc in Infrastructure Asset Maintenance and Management (2004), and a BEng in Civil Engineering (2003). Professor Sarhosis's research focuses on understanding the long-term behaviour of existing masonry infrastructure and historic structures. His work encompasses both 'blue skies' research and 'near-to-market' development, with a strong translational focus. His research group investigates inspection, monitoring and condition appraisal of masonry infrastructure; structural assessment; and maintenance, repair and rehabilitation of masonry infrastructure. His expertise spans machine learning, artificial intelligence, structural health monitoring, sensor technology, digital twins, cultural heritage preservation, and masonry structures. Analysis of his recent publications (2021-2023) reveals a strong focus on computational modeling of masonry structures, particularly using discrete element methods. His work integrates artificial intelligence and machine learning techniques for structural health monitoring and assessment. Key research areas include seismic performance of masonry structures, digital twin technology for infrastructure assessment, and the development of smart materials for structural monitoring and rehabilitation. His work frequently addresses heritage conservation challenges and disaster resilience for masonry infrastructure. Scientific Awards: International Partnership Award, University of Leeds (2021) Queen's Anniversary Prize for Higher and Further Education (2013) First price award for Commercialisation of Research: Project sDNA (2014) Professor Sarhosis has successfully secured significant research funding including EPSRC grants, UKRI HEIF funding, MSCA-IF projects, and British Academy GCRF funding. He serves as Subject Editor for Engineering Failure Analysis (Elsevier) and Associate Editor for the International Journal of Masonry Research and Innovation. He has examined numerous PhD theses at institutions worldwide including Heriot-Watt University, Newcastle University, Politecnico di Milano, and ETH-Zurich. His professional memberships include Fellow of the Institution of Civil Engineers (FICE), Fellow of the Institute of Mechanical Engineers (FIMEchE), and Chartered Engineer (CEng).

Terry SooView profile

Associate Professor

• Probability Theory
• Ergodic Theory
• Statistical Science

Terry Soo is an Associate Professor in the Department of Statistical Science at University College London (UCL), a position he has held since 2020. His academic background includes postdoctoral roles at the University of Warwick and the University of Victoria, followed by an Associate Professorship at the University of Kansas. He holds degrees from Simon Fraser University (undergraduate) and the University of British Columbia (PhD). His research focuses on probability theory and ergodic theory , with a particular emphasis on topics such as nonsingular systems, Bernoulli shifts, and stochastic processes. His work often explores structural properties of dynamical systems and their isomorphisms, with applications to measure-preserving transformations and entropy theory. Soo teaches advanced courses such as Stat 0009 (Probability and Statistics) and LTCC Stochastic Processes . His research has been published in prestigious journals like Annals of Probability and Ergodic Theory and Dynamical Systems , and he maintains an active presence in the academic community through external profiles on arXiv, ZbMATH, and AMS.

Benjamin RossmanView profile

Associate Professor

• Computational Complexity
• Finite Model Theory
• Circuit Complexity
• +3 more

Benjamin Rossman is an Associate Professor in the Computer Science and Mathematics Departments at Duke University , affiliated with the Theory Group. His research focuses on computational complexity, particularly circuit complexity and finite model theory, with notable contributions to lower bounds for subgraph isomorphism problems and logical definability. Rossman earned his Ph.D. from MIT under Madhu Sudan's supervision. He has held faculty positions at the University of Toronto and postdoctoral roles at the Tokyo Institute of Technology and National Institute of Informatics in Japan. He has received prestigious awards including the Alfred P. Sloan Fellowship and NSERC grants. His teaching includes courses on computational complexity, mathematical logic, and discrete mathematics. Recent publications explore homomorphism preservation theorems, formula complexity, and treedepth in subgraph isomorphism. Rossman advises graduate students in theoretical computer science and has led research on circuit lower bounds, algorithmic logic, and combinatorial complexity. His work bridges foundational theory with practical algorithmic challenges, contributing to the understanding of computational limits in combinatorial problems.

Åsa MelinView profile

Professor

• History of Education
• Swedish Social History
• Welfare State Development
• +3 more

Åsa Melin is a Professor of History at Karlstad University, specializing in the history of education and social policy in 20th-century Sweden. Her work focuses on the interplay between local governance, national policies, and educational practices, particularly regarding democratic ideals and welfare state development. She holds a PhD and has been actively publishing since at least 2018. Research interests include rural education systems, teacher working conditions, industrial community dynamics, and the historical implementation of progressive pedagogy. Her studies often analyze how national educational reforms were adapted (or resisted) at municipal and school levels. Recent publications examine topics like women's roles in mining communities ( Det är en manlig historia ), teacher narratives of 1940s progressive teaching, and the tension between local and state control in school establishment processes. She frequently collaborates with historians like Stefan Backius and Johan Samuelsson. No scientific awards are listed, but her extensive publication record indicates significant academic contribution. Her office is located in room 3A 530 at Karlstad University, and she can be reached at asa.melin@kau.se.

• Applied Mathematics
• Computational Methods
• Control Theory
• +5 more

Sara Grundel is a leading researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. Her work focuses on computational methods in systems and control theory, particularly in model order reduction, gas network simulation, and optimization of energy systems. Education: Diplom in Mathematics, ETH Zurich (2005) PhD in Mathematics, Courant Institute of Mathematical Sciences, New York University (2011) Research Interests: Sara’s research encompasses mathematical control theory, stability analysis, and numerical methods for differential-algebraic equations. She applies these techniques to gas and energy networks, epidemic modeling, and multi-agent systems. Her interdisciplinary work bridges computational mathematics with real-world engineering and public health challenges. Recent Publications: Her 15 most recent articles (2024–2012) demonstrate expertise in parametrized PDEs, model reduction for coupled systems, and control strategies for SARS-CoV-2 containment. Key subtopics include adaptive meshing, stability-preserving algorithms, and optimization of nonlinear network dynamics. Scientific Contributions: Developed clustering-based model reduction techniques for networked systems Investigated hyperbolic discretization methods using Riemann invariants Advanced polynomial root radius optimization with affine constraints Collaborations: Sara frequently collaborates with researchers like Peter Benner and Martin Gersen on energy grid simulations and control theory. She participates in international conferences (GAMM, IEEE CDC, MTNS) and contributes to edited volumes in applied mathematics.

Pooran MemariView profile

Researcher

• Geometric Modeling
• Computer Graphics
• Computational Geometry
• +5 more

Pooran Memari is a CNRS Researcher at the Laboratoire d'Informatique de l'École Polytechnique (LIX), UMR CNRS 7161, Institut Polytechnique de Paris, and an Affiliate Professor (part-time) at École Polytechnique. She leads research in geometric modeling within the GeomeriX team at LIX-Inria, focusing on theoretical foundations and applications in accessibility and neurocognition. Her academic journey includes: HDR (Habilitation à diriger des recherches), Institut Polytechnique de Paris, 2024 Ph.D. in Geometric Modeling, INRIA Sophia-Antipolis, 2010 Master in Image and Geometry, University of Nice-Sophia Antipolis, 2006 Engineering Degree, École Polytechnique, 2005 Bachelor in Mathematics, Sharif University of Technology, 2002 Dr. Memari's research bridges geometric modeling, computational geometry, and computer graphics with real-world impact. She pioneers techniques in shape representation, point pattern synthesis, and surface reconstruction, advancing proximity encoding and clustering algorithms. Her work extends to accessibility applications—developing geometric models for visually impaired navigation through multisensory perception—and neurocognition validation via tactile interfaces. This interdisciplinary approach integrates theoretical rigor with practical tools like the CGAL library. Recent publications (2024-2019) reveal a cohesive trajectory in geometric processing: advancing point pattern synthesis through image-based editing (Patternshop), stability-incorporated neighborhood graphs (SING), and multi-class disk distributions; innovating surface reconstruction via Voronoi-based methods (BallMerge); and expanding applications to virtual worlds simulation and neurocognitive accessibility. Key themes include bridging discrete geometry operators with high-dimensional data analysis and translating theoretical insights into tools for visual computing. Dr. Memari actively mentors the next generation of researchers, advising eight PhD students on topics ranging from generalized Voronoi diagrams to neurocognition-driven tactile navigation. She coordinates Computer Science Projects for École Polytechnique's Bachelor program since 2019 and co-leads the Interaction, Graphics & Design master's program at IP-Paris. Her leadership extends to editorial roles at Computer Graphics Forum and Graphical Models Journal, alongside prominent conference positions including SGP Program Co-Chair (2023) and Eurographics STARs Co-Chair (2025). As a core GeomeriX team member, she drives collaborative projects in geometric modeling and virtual environments. She coordinates the LIX Seminar since May 2025 and serves on the French Eurographics Chapter board, fostering community engagement through initiatives like the IGD master's program and Eurographics symposia.

• International Human Rights Law
• Minority Rights
• Freedom of Religion or Belief
• +5 more

Stephanie Berry is a Senior Lecturer in International Human Rights Law at the School of Law, Politics and Sociology, University of Sussex. She is Co-Director of the Sussex Centre for Human Rights Research and Convenor of the Human Rights Law Clinic and LLM in International Human Rights Law. Her research focuses on the human rights of religious and new minorities in Europe, integrating multiculturalism, interculturalism, and social psychology into legal analysis. Stephanie holds a PhD from Brunel University (2013), an LLM in International Human Rights Law from Lund University/Raoul Wallenberg Institute (2008), and an LLB from the University of Manchester (2003). She has contributed to the OSCE Office of Democratic Institutions and Human Rights and Minority Rights Group International. Her recent publications include analyses of the EU migration pact, the securitization of Islam in the European Court of Human Rights, and the cultural rights of minority-refugees. Her work emphasizes interdisciplinary approaches to international human rights law, with a focus on the intersection of legal frameworks and societal dynamics. Stephanie supervises PhD research in minority rights, migration, and freedom of religion. She has taught advanced legal research, human rights law, and civil rights modules at the University of Sussex, serving as an external examiner at the London School of Economics and the University of Oxford. She is actively involved in the Sussex Centre for Human Rights Research, the Sussex Rights and Justice Research Centre, and the FoRB & Foreign Policy Initiative. Her current projects explore the impact of securitization on human rights protections and the categorization of minority-refugees under international law.

• Architectural Education
• Spatial Cognition
• Informatics
• +10 more

Leman Figen Gül is a Professor at the Department of Architecture , Istanbul Technical University 's Faculty of Architecture. She also serves as Head of the Game and Interaction Technologies Program and Coordinator of the Graduate Informatics in Architectural Design Program. Her academic career spans institutions like Newcastle University, University of Sydney, International University of Sarajevo, TOBB University of Economics and Technology, and MacQuarie University. PhD (2007) - University of Sydney, thesis: "Understanding Collaborative Design in Different Environments: Comparing Face-to-Face Sketching to Remote Sketching and 3D Virtual Worlds" Master's (2003) - University of Sydney, Digital Media Program Master's (1996) - Mimar Sinan University, Urban Conservation Program Licence (1993) - Mimar Sinan Fine Arts University, Department of Architecture Her research explores intersections between architecture, technology, and cognition, focusing on collaborative design , virtual/augmented reality , and AI integration in architectural education . Current projects investigate AI-driven co-design interfaces, gamification of cultural heritage, and material innovation in design pedagogy. Recent publications highlight trends in design technology and empathy in architecture . Her work combines theoretical inquiry with practical implementations in digital fabrication and immersive environments. Scientific Awards Academic Performance Award (ITU, 2024) Academic Performance Award (ITU, 2022) QHT Prize 3rd & People's Prize 2nd (University of Westminster, 2017) As principal investigator, she directs projects funded by TÜBİTAK and BAP , including AI collaboration systems and mixed reality heritage interpretation. She leads the Kumio Lab and participates in EU Horizon Project evaluations.

• Urban Sociology
• Housing Policy
• Public Policy
• +4 more

Brian J. McCabe is the Provost's Distinguished Associate Professor in the Department of Sociology at Georgetown University and Director of Undergraduate Studies. His research focuses on housing policy, urban inequality, and the intersection of democracy with electoral systems. McCabe holds a B.S. from Georgetown University's School of Foreign Service (2002), an M.A. in Urban Geography from the London School of Economics (2004), and a Ph.D. in Sociology from New York University (2011). He previously served as Deputy Assistant Secretary for Policy Development at the U.S. Department of Housing and Urban Development (2022–2024). McCabe's expertise includes campaign finance reform, global cities, and urban planning. He authored No Place Like Home: Wealth, Community and the Politics of Homeownership (Oxford UP, 2016) and co-edited The Sociology of Housing (Chicago UP, 2023). His current research examines rental assistance scarcity, Seattle's Democracy Voucher program, and eviction dynamics. He is incoming editor-in-chief of City & Community and serves on the editorial board of Housing Policy Debate . His work has appeared in American Sociological Review , Social Forces , and Journal of Urban Economics , among others. McCabe teaches courses on urban studies, inequality, and policy analysis. His research highlights the structural inequities in housing markets and the role of policy in shaping social outcomes.

Jason SmithView profile

Senior Lecturer

• Combinatorics
• Topology
• Topological Data Analysis
• +12 more

Jason Smith is a Senior Lecturer in Mathematics at the Department of Physics and Mathematics, Nottingham Trent University. His work bridges pure mathematics and neuroscience, focusing on combinatorial and topological methods for analyzing brain networks and functional data. His educational background includes: PhD in Computer and Information Science, University of Strathclyde (2015) MMath, University of Bath (2012) His research lies at the intersection of combinatorics, topology, and neuroscience. He applies tools from graph theory, topological data analysis (TDA), and algebraic topology to study the structure and function of neural systems. Key areas include the analysis of connectomes (such as C. Elegans and Drosophila), modeling brain network dynamics, and developing theoretical frameworks for understanding neural coding through combinatorial and topological lenses. His work often involves collaborations with neuroscientists and computational biologists. His recent publications demonstrate a strong trend toward interdisciplinary research, combining deep mathematical theory with applications in neuroscience. The articles span topics from the topology of directed flag complexes and tournaplexes to the combinatorics of permutation patterns and the Abelian sandpile model, all unified by their relevance to understanding complex biological networks. There is a clear progression from theoretical combinatorics toward computational and applied neurotopology. He has collaborated extensively with researchers from the University of Aberdeen, EPFL (including the Laboratory for Topology and Neuroscience and the Blue Brain Project), and other institutions. He has developed several open-source software tools such as Flagser-count, Tournser, and Deltser for computing persistent homology in directed networks, reflecting his commitment to computational reproducibility and tool development. He has presented his work in various venues, with talks and posters on topics including permutation posets, tournaplexes, and functional brain data classification. His research is supported by collaborative projects focusing on the topological analysis of neural systems and the mathematical foundations of pattern posets.

Son-Young YiView profile

Professor

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +4 more

Son-Young Yi is a Professor in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP), specializing in Computational Science. Her research focuses on numerical methods for partial differential equations, particularly finite element methods applied to solid mechanics, flow in deformable porous media, fluid-solid interactions, and multiscale analysis. She develops physics-preserving numerical schemes and contributes to the study of locally-conservative discretizations and reduced-order modeling. Her research interests span numerical analysis, scientific computing, and computational mechanics. Notable areas include enriched Galerkin methods for coupled thermo-poroelasticity systems, locking-free formulations for poroelasticity and linear elasticity, and numerical studies of financial models like European option pricing with non-Lévy jumps. Recent advancements in her work include projection-based reduced order modeling for iterative coupling schemes and immersed interface methods for interface problems. These contributions address challenges in accurately simulating complex physical phenomena across multiple scales and coupled processes. Dr. Yi's work has been supported by significant grants, including a $5 million award from UTEP for climate change mitigation research. Her publications reflect interdisciplinary collaborations in computational fluid dynamics, solid mechanics, and geophysical modeling.

Xiaozhe HuView profile

Professor

• Scientific Computing
• Numerical Analysis
• Multigrid Methods
• +7 more

Xiaozhe Hu is a full-time Professor in the Department of Mathematics at Tufts University since July 2024. Previously held positions include Associate Professor (2019-2024) and Assistant Professor (2014-2019) at Tufts, and Adjunct Associate Professor (2020-2022) at the University of Bergen, Norway. Education : PhD in Computational Mathematics (Zhejiang University, 2009); BS in Information and Computer Science (Zhejiang University, 2004) His research focuses on scientific computing and numerical analysis , particularly: Development of adaptive and parallel numerical methods for PDEs and graph problems Multigrid/multilevel solvers for large-scale coupled systems Quantum algorithms and spectral graph theory Applications in poromechanics , reservoir simulation , and bioinformatics Recent publications demonstrate expertise in preconditioning techniques for Biot’s model, meshless methods for fluid-structure interaction, and data-driven discretization approaches . Awards include the Reimann-Louville Award (2016) and outstanding PhD graduate recognition (Zhejiang Province, 2009). PhD Students : Junyuan Lin (Loyola Marymount), Peter Ohm (RIKEN), Casey Cavanaugh (LSU), Kaiyi Wu, Eoghan O'Keefe Master Students : Charles Colley (Purdue PhD), Yue Shen (Florida State PhD), Samuel Rabinowitz, Phong Huang, Samuel Hocking Co-organizer of the Computational and Applied Mathematics Seminar and contributor to open-source HAZmath finite element library.

Seung Jae LeeView profile

Associate Professor

• Civil Engineering
• Geotechnical Engineering
• Computational Modeling
• +6 more

Seung Jae Lee is an Associate Professor and Undergraduate Program Director in the Department of Civil and Environmental Engineering at Florida International University (FIU). He holds a Ph.D. in Civil Engineering from the University of Illinois at Urbana-Champaign (2014). His research focuses on advanced computational modeling of granular materials, structural dynamics, and disaster-resilient infrastructure. Key areas include particle geometry characterization, soil-water interaction analysis, and wind engineering for building systems. He leads efforts in integrating 3D imaging and simulation techniques to enhance material understanding and infrastructure performance. Education: Ph.D., Civil Engineering, University of Illinois at Urbana-Champaign, 2014 Research interests span particle morphology analysis, computational mechanics, and sustainable construction materials. His work emphasizes practical applications such as improving cement-based materials through aggregate morphology optimization and enhancing building envelope systems against extreme winds. Lee's methodologies often combine experimental testing with advanced numerical simulations, such as discrete element modeling (DEM) and finite element analysis (FEA). His articles highlight trends in 3D particle characterization, wind-induced structural behavior, and biotechnology-driven soil improvement. These studies aim to bridge microscopic material properties with macroscopic engineering performance, contributing to safer and more durable infrastructure systems. Notable projects include full-scale testing of curtain wall systems and development of predictive models for material degradation under cyclic loading. His lab focuses on disaster preparedness through computational frameworks integrating imaging and simulation for construction projects.