Find Academic Supervisors

Zamir KoshuriyanView profile

Lecturer

• Asymptotic Analysis
• Aero-acoustics
• Computational Fluid Dynamics (CFD)
• +7 more

Zamir Koshuriyan is a Lecturer in Industry-Facing Applied Mathematics at the University of York, holding a PhD from Cambridge University (2008). His career includes postdoctoral fellowships at institutions such as DAMTP Cambridge, Stanford University, NASA Glenn Research Center, Imperial College London, and the University of Strathclyde. He leads research integrating asymptotic analysis with computational fluid dynamics (CFD) to address industrial fluid mechanics problems, focusing on aero-acoustics of free jet flows, turbulence modeling, and wind turbine noise prediction. His work also extends to asymptotic methods for heat/mass transfer in seawater desalination. Education: BSc from University of Bristol, PhD from University of Cambridge (2004-2008). Research Groups: Applied Research Group. Funding: EPSRC New Investigator Award (2022) supporting a PDRA and 1-2 PhD students. Research Interests: Asymptotic analysis for acoustic wave propagation Non-homogeneous turbulence modeling Rapid-distortion theory applications Jet noise prediction in air/water environments CFD-based turbulence validation Awards: EPSRC New Investigator Award (2022). Supervision: Currently advising Jack Patrick and Fay Oglethorpe. Offers PhD projects in aero-acoustics, turbulence theory, and transition modeling.

• Colloidal Science
• Interfacial Phenomena
• Polymer Brushes
• +3 more

Grant Webber is a Professor in the School of Engineering at the University of Newcastle, specializing in Chemical Engineering. His research integrates chemical engineering and physical chemistry to study colloidal and interfacial phenomena with applications in personal care products, pharmaceuticals, minerals processing, and biomedical devices. Research interests include stimulus-responsive polymer coatings that alter structure in response to pH, temperature, or salt concentration; specific ion effects in electrolyte solutions; electrostatic formation of liquid marbles for applications in micro-reactors and sensors; and mineral processing technologies. His work employs neutron scattering, atomic force microscopy, and computational modeling to link nanoscale behaviors to macroscale properties. His recent publications demonstrate a strong focus on polymer brush systems (15 articles since 2023), with emerging themes in telecommunications network optimization and mineral processing. The work shows consistent application of fundamental principles to solve industrial problems, particularly in sustainable resource processing and advanced materials design.

Laura ClarkView profile

Research Fellow

• Transmission Electron Microscopy
• Ptychography
• Differential Phase Contrast imaging
• +3 more

Dr. Laura Clark is a Royal Society University Research Fellow at the University of York's School of Physics, Engineering and Technology. Her research focuses on advancing electron microscopy techniques for higher-resolution imaging and quantitative analysis of sensitive materials. She holds visiting researcher positions at the University of Oxford, University of Leeds, and the Electron Physical Science Imaging Centre (ePSIC) at Diamond Light Source. Dr. Clark's expertise includes transmission electron microscopy (TEM), ptychography, differential phase contrast imaging, and beam-shaping methodologies. Her research group develops theoretical models, computational simulations, and experimental protocols to overcome current limitations in nanoscale characterization, particularly for beam-sensitive materials like solar cell components and pharmaceuticals. She received her undergraduate and MSc degrees from the University of York and completed her PhD at the University of Antwerp. Her postdoctoral work included positions at Monash University and Oxford University before joining York in 2022. Dr. Clark has received multiple scientific honors including the European Microscopy Society Outstanding Paper Award (2020) and has served on committees of the Institute of Physics and Royal Microscopical Society. Her publication record demonstrates sustained contributions across electron microscopy techniques, with recent work exploring dose-efficient imaging, phase retrieval algorithms, and materials characterization for renewable energy applications. Dr. Clark leads a research group focused on pushing the boundaries of electron microscopy capabilities.

Harry VarvoglisView profile

Professor

• Non-linear Dynamical Systems
• Asteroidal dynamics
• Three-body Coulomb problem
• +3 more

Harry Varvoglis is a Professor in the Department of Physics at Aristotle University of Thessaloniki, specializing in astrophysics and celestial mechanics. His work bridges theoretical and applied physics, focusing on the dynamics of planetary systems and complex Hamiltonian systems. Non-linear Dynamical Systems Asteroidal Transport Mechanisms Three-Body Coulomb Interactions Two-Fixed-Centers Problem His research reveals fundamental properties of phase space structure, chaotic behavior, and diffusion processes in celestial and atomic systems. Collaborators include prominent scientists like Menios Tsiganis and Karl Wodnar. Recent publications analyze free-floating planet scattering, asteroid belt dynamics, and orbital resonance stability. His work demonstrates interdisciplinary applications of celestial mechanics to astrophysical and plasma physics problems. Contact: varvogli@shift_2.physics.auth.gr varvogli@astro.auth.gr

• Riemannian Geometry
• Inverse Spectral Problems
• Geometry of Lie Groups
• +2 more

Carolyn S. Gordon is a Professor of Mathematics at Dartmouth College, holding the Benjamin Cheney Professorship in Mathematics. She is affiliated with the Department of Mathematics, where her research focuses on Riemannian Geometry, inverse spectral problems, and the geometry of Lie groups. Education: B.S., Purdue University M.S., Purdue University Ph.D., Washington University Research Interests: Her work explores the spectral properties of geometric structures, including isospectral manifolds, transplantation techniques, and symplectic rigidity in nilmanifolds. She investigates how geometric features influence spectral invariants and vice versa, with applications to global analysis and geometric flows. Works in Progress: Current projects include asymptotic expansions of heat kernels on orbifolds, inverse spectral results on even-dimensional tori, isoscattering obstacles and potentials, and spectral analysis of normal homogeneous metrics. Grants & Advising: No grants or student advisees are explicitly listed in the provided materials. She contributes to the Mathematics Department’s research initiatives and collaborates with international scholars. Labs/Teams: Active in collaborative research groups within differential geometry and spectral theory, but no specific lab or team names are mentioned.

Boris VainbergView profile

Professor

• Mathematical Physics
• Scattering Theory
• Spectral Theory of Differential Operators
• +3 more

Boris Vainberg is a Professor of Mathematics at the University of North Carolina at Charlotte (UNC Charlotte), where he has been since 1993. He holds a Doctor of Physical and Mathematical Sciences from Moscow State University (1987) and has held previous academic positions, including Professor at Moscow State University (1963–1991) and visiting roles at UNC Charlotte and the University of Delaware. Education: Masters Degree in Mathematics, Moscow State University, 1960 Candidate of Physical and Mathematics Sciences (Ph.D. equivalent), Moscow State University, 1963 Doctor of Physical and Mathematical Sciences, Moscow State University, 1987 Research Interests: Vainberg's work focuses on mathematical physics, scattering theory, spectral theory of differential operators, acoustic and electromagnetic waves, free surface hydrodynamics, and population dynamics. His research explores wave propagation in periodic media, spectral properties of operators, and asymptotic methods. Publications: Recent work includes studies on acoustic wave propagation in 3D periodic media, spectral analysis of Schrödinger-type operators, and the behavior of polymers near critical temperatures. These contributions highlight advancements in understanding wave dynamics, spectral transitions, and critical phenomena. Awards & Grants: No specific awards or grants are listed in the provided materials. Teaching & Advising: While no student advisees are explicitly mentioned, his role as a Professor involves teaching and mentoring at UNC Charlotte.

Xingjie LiView profile

Associate Professor

• Numerical Analysis
• Partial Differential Equations
• Mathematical Physics
• +3 more

Xingjie (Helen) Li is an Associate Professor in the Mathematics & Statistics Department at the University of North Carolina at Charlotte. Her research focuses on numerical analysis, partial differential equations, and mathematical physics with an emphasis on nonlocal models, multiscale methods, and computational mechanics. She develops advanced numerical schemes for stochastic systems and explores applications in materials science, image processing, and epidemiological modeling. Her work bridges theoretical analysis and practical computation, addressing challenges in coarse-graining stochastic dynamics, atomistic-to-continuum coupling, and probabilistic collocation methods for heterogeneous materials. Recent studies include innovative approaches to nonlocal diffusion problems, peridynamic fracture modeling, and data-driven time-stepping algorithms for ergodic systems. She has also applied mathematical techniques to analyze real-world scenarios such as pandemic dynamics in Singapore and Japan. Key contributions include energy-preserving finite difference schemes, feature-oriented imaging compression frameworks, and inference-based adaptive methods. Her research portfolio reflects interdisciplinary collaboration spanning computational physics, applied mathematics, and data science.

Filipe Serra De OliveiraView profile

Professor

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Dispersive Equations
• +3 more

Prof. Filipe Serra de Oliveira is a Mathematics Professor at ISEG (Lisbon School of Economics and Management) within the University of Lisbon. He holds an Aggregation in Mathematics from the University of Lisbon and a Doctorat in Mathematics from Université Paris Sud. His research focuses on nonlinear partial differential equations, mathematical physics, and dispersive systems. He has served as course coordinator, research group member (REM/CEMAPRE), and master's program coordinator. His work includes studies on Schrödinger systems, kinetic models, and fluid dynamics, with over 40 publications in top journals like SIAM and Nonlinearity. He actively participates in academic governance roles and has supervised at least one master’s thesis in optimal control theory. Research interests: His work spans dispersive equations (e.g., Schrödinger, Boussinesq systems), soliton dynamics, and nonlinear optics. He explores theoretical aspects like well-posedness, stability, and scattering behavior while addressing applied problems in fluid dynamics and chemical reaction modeling. Recent trends include analyzing critical cases and coupled systems. Teaching contributions include leading courses like Mathematical Analysis I and Calculus for economics and management programs. His pedagogical materials emphasize practical problem-solving in calculus and differential equations.

Christoph PflaumView profile

Professor

• Numerical Analysis
• Optics
• Laser Engineering
• +5 more

Prof. Dr. Christoph Pflaum holds the Professorship for Numerical Simulation and High-Performance Computing at the Department of Computer Science, Friedrich-Alexander University Erlangen-Nürnberg. His research spans computational optics, solid-state laser simulation, and sustainable energy systems. Key Research Areas: Numerical methods for PDEs, thermal lensing in lasers, polarization effects, and solar energy harvesting technologies. Recent Work: Focus on adaptive sparse grids for high-dimensional PDEs, 3D laser pulse amplification models, and optimization of solar-integrated airships. Scientific Trends: His publications emphasize computational modeling of optical phenomena (thermal lensing, Kerr effects) and renewable energy innovations (thin-film solar cells, flexible solar arrays). Collaborative projects include SiSoFlex and LightWave, integrating simulations with industrial applications. Collaborations: Works with institutions in Germany and internationally, including teams in Erlangen, Strasbourg, and Lisbon. Current projects align with sustainable aviation and laser engineering.

• Quantum Chromodynamics (QCD)
• Dark Matter Detection
• Particle Physics
• +3 more

Xiangdong Ji is a Distinguished University Professor at the University of Maryland's Department of Physics. His research focuses on theoretical studies of nucleon structure within Quantum Chromodynamics (QCD) and experimental dark matter detection via liquid xenon technology. He holds a B.S. from Tongji University and a Ph.D. from Drexel University (1987). Professor Ji is a Fellow of the American Physical Society and recipient of the 2003 Outstanding Overseas Young Chinese Scientist Award. His experimental collaborations include leading roles in the PandaX-4T dark matter experiment, which explores dark matter particles, neutrino interactions, and nuclear decay processes. Research interests span QCD dynamics, parton distributions, gravitational form factors of hadrons, and precision measurements in particle astrophysics. He teaches advanced physics courses such as Physics 851 (Advanced Quantum Field Theory) and contributes to detector development for low-background experiments. Over 15+ publications in 2025 alone highlight his work on PandaX-4T's capabilities for dark matter detection, neutrino physics, and lattice QCD calculations of nucleon structure. Awards include recognition for his contributions to theoretical and experimental particle physics. His lab and team collaborate internationally on PandaX-xT, a next-generation liquid xenon observatory targeting breakthroughs in dark matter and neutrino physics. Grants and funding support his research into QCD's foundational questions and experimental infrastructure for high-sensitivity particle detectors.

• Inverse problems
• Wave propagation
• Diffraction theory
• +4 more

Dr Anna Kirpichnikova is a Lecturer in Mathematics at the University of Stirling's Computing Science and Mathematics Department within the Faculty of Natural Sciences. She holds a PhD from Loughborough University and has held academic positions at the University of Edinburgh, University of Glasgow, and Liverpool Hope University. Her research focuses on inverse problems, wave propagation in complex media, cardiac modeling, and optimization of mobile networks. Education: BSc/MSc from St-Petersburg State University (2000), PhD from Loughborough University (2005), and a Master's in Academic Teaching from the University of Glasgow (2010). Awards include the EPSRC Postdoctoral Fellowship (2006) and Fellowship of the Higher Education Academy. Research interests span mathematical modeling in wave dynamics, including diffraction, focusing waves in unknown media, and applications in medicine (cardiac variability) and engineering (MANET optimization). She collaborates internationally, including with the Steklov Mathematical Institute and institutions in Japan, Finland, and Canada. Teaching includes courses on medical modeling, discrete structures, stochastic processes, and numerical analysis. Active in conference organizing and editorial roles for 'Days on Diffraction' proceedings. Her work integrates interdisciplinary approaches with industry partners in pharma and engineering.

Thomas PockView profile

Professor

• Computer Vision
• Image Processing
• Mathematical Optimization
• +7 more

Thomas Pock is a Professor of Computer Science at Graz University of Technology, holding the AIT Stiftungsprofessur for Mobile Computer Vision. He is affiliated with the Institute for Computer Graphics and Vision (ICG) within the Faculty of Computer Science and serves as a principal scientist at the Austrian Institute of Technology (AIT), Center for Vision, Automation & Control. He leads the Vision, Learning and Optimization (VLO) research group, which focuses on mathematical modeling and optimization in computer vision. His research interests lie at the intersection of computer vision, image processing, and mathematical optimization. Specifically, he develops mathematical models for computer vision and efficient convex and non-smooth optimization algorithms , particularly for mobile scenarios. His recent work increasingly integrates variational methods with deep learning, especially in solving inverse problems in imaging such as medical reconstruction and deblurring. The trends in his recent publications show a strong emphasis on deep learning for inverse problems , variational networks , and learned optimization . His group explores how to combine classical mathematical models with data-driven deep learning approaches to achieve stable, interpretable, and high-performance solutions in image reconstruction and processing. His scientific achievements have been recognized with several prestigious awards: START Prize, Austrian Science Fund (FWF), 2013 German Pattern Recognition Award, DAGM, 2013 ERC Starting Grant, European Research Council, 2014 Thomas Pock actively mentors students and leads a research group of 10 PhD students and 2 postdocs. He has secured significant research grants, including the ERC Starting Grant, which supports his foundational work. He is also engaged in scientific communication, giving invited talks at international venues such as SIAM and co-organizing the IMAGINE One World seminar series to foster global collaboration in imaging and inverse problems. He leads the Vision, Learning and Optimization (VLO) group at the Institute for Computer Graphics and Vision. The group develops mathematical models and efficient algorithms for computer vision and image processing, with a focus on mobile applications. The team includes multiple PhD students and postdoctoral researchers and has produced notable software and publications in top venues.

Sung-Jin OhView profile

Associate Professor

• Geometric Partial Differential Equations (PDEs)
• Mathematical Physics
• Harmonic Analysis
• +7 more

Sung-Jin Oh is an Associate Professor in the Department of Mathematics at the University of California Berkeley. His research focuses on geometric partial differential equations (PDEs) arising from physics, combining harmonic analysis, differential geometry, and mathematical physics. University of California Berkeley (Current: Associate Professor) Korea Institute for Advanced Study (Former: CMC Research Professor) PhD: Princeton University (Advisor: Sergiu Klainerman) Undergraduate: KAIST His work addresses singularity formation and long-term dynamics in nonlinear PDEs, including Yang-Mills equations, Einstein equations, Chern-Simons theories, wave maps, and incompressible fluid models. He has contributed to the global well-posedness of the Einstein-scalar-field system, stability of geometric wave maps, and illposedness in magnetohydrodynamic equations. Recent publications analyze blow-up profiles in Chern-Simons-Schrödinger equations, stability of catenoid solutions for hyperbolic mean curvature equations, and illposedness in fluid dynamics models. His research often bridges general relativity, dispersive PDEs, and geometric analysis. Scientific awards include: Miller Research Fellow CMC Research Professor He organizes seminars on PDEs and relativity and teaches graduate courses on partial differential equations at UC Berkeley.

AmirEhsan KhorashadizadehView profile

Research Fellow

• Machine Learning
• Computational Imaging
• Inverse Problems
• +7 more

AmirEhsan Khorashadizadeh is a postdoctoral researcher affiliated with the Paul Scherrer Institute (PSI) and École Polytechnique Fédérale de Lausanne (EPFL) , working in the Computational X-ray Imaging group under Prof. Manuel Guizar Sicairos. His research integrates deep learning and computational imaging , focusing on physics-informed neural networks for applications in tomography , inverse scattering , and cosmological imaging . He collaborates with the Swiss Data Science Center (SDSC) on the CHIP project 'Machine-Learning-assisted Ptychographic nanotomography.' His work spans multiple domains, including medical imaging , Bayesian imaging , and astrophysical signal processing . Publications highlight advancements in scalable image reconstruction , injective flow-based models , and implicit neural representations , with applications in X-ray and cosmological imaging . Scientific Awards Promotion of Young Talent grant from University of Basel for 9-month visiting scholar at University College London (UCL) Top 25 most downloaded paper in IEEE Transactions on Computational Imaging (TCI) from Sept. 2022–Sept.2023

• Quantum Physics
• Condensed Matter Physics
• Quantum Simulations
• +7 more

Prof. Andreas Läuchli is a faculty member at the University of Innsbruck in the Department of Theoretical Physics . His research spans quantum physics, condensed matter physics, and quantum simulations, focusing on strongly correlated systems, topological order, and critical phenomena. Specializes in quantum spin systems, Chern insulators, and quantum entanglement Active in developing numerical algorithms for quantum many-body problems Investigates quantum phase transitions using tensor networks and exact diagonalization His recent publications (2023-2025) highlight work on: Emergent conformal field theory in matrix product states Field-induced quantum criticality in frustrated magnets Topological density wave order in moiré systems Quantum Monte Carlo simulations of Chern bands Dipolar cavity quantum electrodynamics He leads the Läuchli Lab at the University of Innsbruck, which develops open-source quantum simulation software packages and contributes to tensor network algorithms for entanglement studies.