Find Academic Supervisors

• Cochlear Modeling
• Hearing Impairment
• Acoustics
• +5 more

Jont Allen is a Professor at the University of Illinois at Urbana-Champaign, holding joint appointments in the Electrical and Computer Engineering , Nuclear, Plasma, and Radiological Engineering , Speech and Hearing Science departments, and the Coordinated Science Lab . He is an IEEE Fellow (1985) and has contributed extensively to cochlear modeling, hearing science, and mathematical physics. Allen’s research spans auditory mechanics, signal processing, and interdisciplinary applications in biomedical and environmental engineering. His research interests include cochlear amplification , hearing impairment , acoustic signal analysis , and mathematical pedagogy . Recent work focuses on cochlear function from the canal to the cortex, chaotic systems in numerical methods, and historical perspectives in mathematical physics. Key contributions include the Chaotic Convergence of Newton’s method (2024) and a 50-year retrospective on cochlear modeling. His publications bridge theoretical frameworks with practical applications in audiology, engineering, and education. Allen is affiliated with the Coordinated Science Lab, emphasizing collaborative, interdisciplinary research.

Tristan van LeeuwenView profile

Professor

• Imaging Reconstruction
• Inverse Problems
• Scientific Computing
• +4 more

Tristan van Leeuwen is a Professor of Computational Inverse Problems at Utrecht University's Faculty of Science, within the Mathematical Institute's Department of Mathematical Modeling. He holds a MSc in Computational Science (2006) and a PhD in Geophysics (2010). His career includes postdoctoral roles at the University of British Columbia and Centrum Wiskunde & Informatica (CWI), followed by faculty positions at Utrecht University and group leadership at CWI. His research focuses on inverse problems, scientific computing, imaging reconstruction, and computational methods for geophysics and medical imaging. Key areas include wave-equation inversion, tomographic reconstruction, and uncertainty quantification. Notable contributions span seismic inversion techniques, convex optimization frameworks for tomography, and deep learning applications in imaging. His publications emphasize methodologies like wavefield reconstruction inversion, convex programming for shape sensing, and Bayesian approaches for uncertainty analysis. He collaborates with institutions like CWI and the University of British Columbia, contributing to open-source tools like Tomosipo for tomography. His work bridges theoretical mathematics with practical applications in geophysics, medical diagnostics, and industrial inspection.

• Structural Health Monitoring (SHM)
• Nondestructive Evaluation (NDE)
• Smart Sensing Technologies
• +7 more

Professor Alex Ching-Tai Ng is a faculty member at the University of Adelaide, serving as a Professor in the School of Architecture and Civil Engineering within the Faculty of Sciences, Engineering and Technology. He joined the university in 2011 as a Lecturer and was promoted to Professor, holding administrative roles such as Associate Dean of Graduate Studies and Director of Graduate Studies (2018–2022). Education: B.Eng. (First-class Honours, City University of Hong Kong), M.Phil. (City University of Hong Kong), Ph.D. (University of Queensland) His research interests span Structural Health Monitoring (SHM), Nondestructive Evaluation (NDE), smart sensing technologies, and vibration testing. He focuses on developing advanced SHM/NDE techniques for structural integrity assessment, with applications in engineering reliability and decarbonization of construction. His publications highlight innovations in guided wave-based damage detection, nonlinear ultrasonic methods for composite materials, and machine learning integration in structural diagnostics. Key trends include FRP-strengthened structures, graphene composites, and real-time hybrid simulation for wind response analysis. Scientific awards include: The Nishino Prize (EASEC, 2016) Australian Research Council Discovery Early Career Researcher Award (2013) He actively supervises Masters and PhD candidates and has served as an assessor for international grants (ARC, RGC, ERC, SNSF, NCN, CONICYT). Professional leadership includes Co-Editor-in-Chief of Engineering Structures and roles in technical committees like ISHMII and ANSHM.

• Nonlinear PDEs
• Mathematical Physics
• Integrable Systems
• +2 more

Jonatan Lenells is Professor in the Department of Mathematics at KTH Royal Institute of Technology, currently on parental leave until August 2025. His research focuses on nonlinear partial differential equations and mathematical physics. Key research areas include integrable systems, soliton equations, and geometric methods in PDE analysis. He employs techniques from Riemann-Hilbert problems, asymptotic analysis, and differential geometry. Lenells has supervised multiple PhD students and postdocs working on analytical and numerical aspects of integrable PDEs.

• Electromagnetism
• Wave Propagation
• Computational Physics
• +2 more

Chun Li is a Professor of Population and Public Health Sciences at the University of Southern California. His research focuses on computational physics, electromagnetism, and nanophotonics, with expertise in inverse design, wave propagation, and material interactions in disordered media. Dr. Li's research interests span electromagnetic device design, wave scattering simulations, and quantum material phenomena. His work leverages advanced computational methods to solve complex problems in photonics and condensed matter physics, particularly in optimizing light-matter interactions and developing efficient algorithms for large-scale simulations. Analysis of Dr. Li's recent publications reveals dominant themes in nanophotonics, quantum materials, and computational electromagnetics. His research consistently pushes boundaries in light manipulation techniques, scattering matrix solvers, and graphene physics, with significant contributions to optimization algorithms and high-performance computing applications in physics.

Martijn C. van BeurdenView profile

Professor

• Computational Electromagnetics
• Inverse Scattering
• Antenna Design
• +2 more

Martijn van Beurden is a Full Professor in the Electromagnetics group at Eindhoven University of Technology's Department of Electrical Engineering. His research focuses on computational electromagnetics for high-tech systems, specializing in inverse scattering and antenna design. He holds a cum laude MSc (1997) and PhD (2003) from TU/e, where he received the C.I.V.I. Prize and ASML Prize for his thesis work. His research interests center on developing advanced numerical methods for electromagnetic modeling, with applications in wave behavior analysis, inverse scattering problems, and antenna optimization. Current projects include electromagnetic field modeling in stochastic environments and periodic structures. Recent publications demonstrate strong focus on computational efficiency in electromagnetic simulations, with innovations in Green's function discretization and FFT-accelerated integral equations applied to biomedical and scattering problems. Awards: C.I.V.I. Prize for Electrical Engineering (MSc thesis) ASML Prize for Best PhD Thesis in Applied Research He leads multiple projects including INNOSTAR and MAX META-XT, focusing on meta-lens design and electromagnetic scattering analysis. Manages the Electromagnetics research group and Center for Wireless Technology Eindhoven.

Sergey LitvinovView profile

Researcher

• Computational Mechanics
• Biomedical Engineering
• Industrial Applications
• +6 more

Sergey Litvinov is a Researcher at ETH Zürich, affiliated with the Department of Structural Mechanics and Monitoring within the College of Civil, Environmental and Geomatic Engineering. His work focuses on computational and statistical models for biomedical and industrial applications, leveraging tools like C++, PyTorch, and cloud computing. He contributes to hierarchical Bayesian analysis on big data and probabilistic programming, emphasizing data-driven methodologies. Current projects include the DCoMEX initiative (Data-Driven Computational Mechanics at Exascale), aiming to advance large-scale computational frameworks for structural mechanics and monitoring. His research interests span computational mechanics, fluid dynamics, and machine learning applications, with a strong emphasis on hybrid numerical methods and high-performance computing for multiphase systems. He has no listed scientific awards or advisees. His contributions are centered on software development (e.g., Aphros and Mirheo ) for multiphase flow simulations and novel optimization techniques for inverse problems, particularly in biomedical and engineering contexts. Recent articles highlight his work on discrete loss optimization, reinforcement learning for flow control, and data-driven methods for tumor growth modeling and drug delivery systems. He is part of interdisciplinary teams addressing challenges in microfluidics, turbulence modeling, and biomedical applications, with a focus on scalable solutions for complex systems. His projects often involve collaboration with industrial and academic partners on computational models for real-world applications.

• Geophysics
• Computational Geophysics
• Inverse Theory
• +6 more

Dr. Fabrizio Magrini is a Research Fellow/Lecturer at the Research School of Earth Sciences (RSES), Australian National University (ANU). He holds a Ph.D. in Earth Sciences (Geophysics) from Università degli Studi Roma Tre, Italy, and completed his M.Sc. and B.Sc. in Earth Sciences at Università degli Studi di Milano. His research focuses on observational, theoretical, and computational geophysics, particularly in seismic imaging techniques, inverse theory, optimization, and machine learning applications. He has supervised multiple students in geophysics projects and contributed to advancements in seismic methodologies through publications in high-impact journals. Education: Ph.D. (2017–2020): Improved seismic methodologies in lithospheric imaging (Università degli Studi Roma Tre) M.Sc. (2015–2017): Crystal-chemical characterization of minerals (Università degli Studi di Milano) B.Sc. (2011–2014): High-pressure mineral behavior (Università degli Studi di Milano) His research interests integrate mathematical methods and computational tools to advance subsurface imaging. Key areas include Bayesian inversion, optimal transport theory, and seismic tomography. He has developed Python frameworks like BayesBay and contributed to studies on urban seismic imaging, Alpine geology, and Mediterranean tectonics. Dr. Magrini’s work bridges geophysical theory and practical applications, emphasizing interdisciplinary approaches to solve complex Earth science problems.

Auggie MarignierView profile

Research Fellow

• Geophysics
• Seismology
• Crustal Dynamics
• +4 more

Auggie Marignier is a Postdoctoral Fellow in the Department of Geophysics at the Research School of Earth Sciences, The Australian National University. His research integrates geophysical and cosmological methodologies, with a focus on seismic imaging, crustal dynamics, and theoretical astrophysics. He holds a Doctoral thesis from ANU (2023) and has contributed to interdisciplinary studies linking Earth's deep interior with cosmological phenomena. Education: PhD in Geophysics, Australian National University, 2023 Research interests include the application of wavelet analysis to study crustal structure and sediment thickness in Australia, tectonic investigations in the western U.S., and cosmological modeling of anisotropies induced by cosmic strings. His work bridges seismology and astrophysics, leveraging advanced computational techniques for inverse imaging problems in both fields. Publications demonstrate a dual focus on geophysical studies (e.g., seismic methods, mantle plumes) and cosmological research (e.g., cosmic microwave background anisotropies). No scientific awards are explicitly mentioned. Grants and advising: No grants or advisees are listed in the provided text. His postdoctoral role suggests involvement in research projects without formal student supervision. Labs/teams: Not specified in the text.

• Computational Mathematics
• Numerical Analysis
• Scientific Computing
• +4 more

Colin Cotter is a Professor of Computational Mathematics in the Department of Mathematics at Imperial College London , part of the Faculty of Natural Sciences . His research focuses on numerical analysis, scientific computing, and geophysical fluid dynamics, with applications in weather forecasting, ocean modeling, and climate simulation. He is Head of the Applied Mathematics and Mathematical Physics Section and an Associate Editor for the SIAM Journal of Scientific Computing and Foundations of Data Science. Education : PhD in Mathematics, Imperial College London (2000–2004) BA and Part III in Mathematics, Cambridge University (1996–2000) Research Interests : Dr. Cotter develops compatible finite element methods and time-parallel algorithms for geoscientific models. His work includes: Design of geometric variational numerical methods for fluid equations Probabilistic forecasting and Bayesian data assimilation techniques Parallel-in-time algorithms using ParaDiag methods Awards & Roles : EPSRC Peer Review College member Co-author of "Probabilistic Forecasting and Bayesian Data Assimilation" Grants & Labs : Involved in projects funded by EPSRC, NERC, and ExCALIBUR. Active in the EPSRC Centre for Maths of Precision Healthcare and the Mathematics of Planet Earth initiative.

• High-performance Computing
• Parallel Algorithms
• Scientific Computing

Professor Tobias Weinzierl heads the Scientific Computing research group at Durham University's Department of Computer Science. He is Co-director of the Institute for Data Science (IDAS) with responsibility for Large-Scale Computing initiatives and serves as inaugural director of the Master in Scientific Computing and Data Analysis (MISCADA). Professor Weinzierl is a reviewer for the EuroHPC JU and principal investigator on multiple ExCALIBUR projects. His research focuses on parallel algorithms, high-performance computing, and scientific computing methodologies. Key areas include adaptive mesh refinement, task-based parallelism, and exascale computing frameworks. Professor Weinzierl develops the Peano software framework for parallel grid traversals and contributes to the ExaHyPE engine for hyperbolic PDEs. His publications span parallel computing paradigms, performance optimization, and applications in computational geophysics. Research trends include GPU offloading, fault tolerance in HPC, and SYCL programming models. Professor Weinzierl has authored books including Principles of Parallel Scientific Computing and edited volumes such as Advanced Computing . He regularly presents at major HPC conferences and workshops worldwide. He advises postgraduate students working on parallel algorithms, GPU acceleration, and computational science applications. Research groups include the Scientific Computing and Data Analysis initiatives at Durham.

Greg GburView profile

Professor

• Classical Optics
• Inverse Problems
• Coherence Theory
• +5 more

Greg Gbur is a Professor in the Department of Physics and Optical Science at the University of North Carolina at Charlotte. He holds a Ph.D. in Theoretical Physics from the University of Rochester (2001). His research focuses on classical optics, including inverse problems, coherence theory, singular optics, and nanoscale light interactions. Notably, he has authored books on invisibility science and falling cats' physics. His work explores invisibility cloaking, plasmonics, and medical imaging techniques involving scattering effects. Dr. Gbur runs two blogs, Skulls in the Stars and Science Chamber of Horrors , and has contributed to peer-reviewed journals in optics and physics. His research also involves coherence vortices, superresolution imaging via superoscillations, and the application of singular optics in turbulence and quantum systems. Education: Ph.D. Theoretical Physics, University of Rochester (2001). Research interests span four core areas: Inverse Problems: Medical imaging techniques and non-unique solutions in scattering experiments. Light Interaction on the Nanoscale: Plasmons, surface plasmon-enhanced transmission, and supercompact disc systems. Coherence Theory: Partially coherent beam propagation, atmospheric turbulence effects, and speckle reduction. Singular Optics: Optical vortices, phase singularities, and their applications in vortex beam engineering. His publications highlight advancements in coherence-orbital angular momentum matrices, directional invisibility cloaks, and experimental validations of theoretical models. Collaborations include work with researchers on coherence-engineered trapping and turbulence-resistant beams. His blogs integrate historical perspectives with cutting-edge optics research.

Habib AmmariView profile

Professor

• Applied Mathematics
• Mathematical Physics
• Medical Imaging
• +6 more

Habib Ammari is a Professor of Applied Mathematics at ETH Zurich, leading research in wave propagation, mathematical imaging, and metamaterials. He previously served as Director of Research at École Normale Supérieure in Paris. His academic journey includes a Bachelor's, Master's, and PhD from École Polytechnique (1992–1995), followed by a Habilitation from Université Pierre & Marie Curie (1998). Research Interests: Mathematics of subwavelength physics and metamaterials Bio-inspired imaging and neural natural intelligence Multiscale biomedical imaging and super-resolution techniques Publications: His work spans over 300 papers and 9 books, including seminal contributions to inverse problems, plasmonics, and imaging modalities. Recent research focuses on non-Hermitian skin effects, quantum integrable systems, and Anderson localization in subwavelength regimes. Awards and Fellowships: European Research Council Advanced Grant (2010) Kuwait Prize in Basic Sciences (2013) Khwarizmi International Award (2015) Fellowships: American Mathematical Society (2022), Academia Europaea (2021), European Academy of Sciences (2018) Advising: Supervised 40+ PhD students and 27 postdocs, many recipients of prestigious awards like the ETH Medal and ECCOMAS PhD Award. Labs and Collaborations: Active in international initiatives including CISM courses, NSF-CBMS conferences, and collaborations with institutions like Hong Kong Institute for Advanced Study and MSRI.

Martin VossiekView profile

Professor

• Microwave Engineering
• Radar Systems
• Wireless Sensor Networks
• +6 more

Prof. Dr.-Ing. Martin Vossiek is Chair of the Institute of Microwaves and Photonics (LHFT) at FAU, a world-leading center in microwave research. He holds a PhD from Ruhr-University Bochum and has extensive industry experience at Siemens. His roles include Prodekan für Elektrotechnik at FAU, spokesperson of DFG RTG 2680 KoRaTo, and leader of SFB 1483 EmpkinS. He has authored 350+ papers, holds 100+ patents, and co-founded five tech startups. Research focuses on radar systems, microwave theory, machine learning in sensing, biomedical monitoring, and automotive applications. Awards include IEEE Fellow, 2019 Microwave Application Award, and acatech membership. He leads global initiatives like ICMIM conference and chairs IEEE committees. Recent work includes radar data compression, SAR imaging in automotive systems, and non-invasive biomedical imaging. Key projects involve fusion of radar with optical sensors, UAV-based glacier exploration, and AI-driven tremor analysis for Parkinson’s care. Awards: IEEE Fellow, 2019 Microwave Award, DFG Review Board Member, acatech membership Grants: DFG RTG 2680, SFB 1483, industry collaborations Labs/Teams: LHFT, Embedded Systems Institute (ESI), ZIMT (Medical Engineering)

Martin BluntView profile

Professor

• Multiphase Flow in Porous Media
• Geological Carbon Storage
• Contaminant Transport
• +4 more

Professor Martin Blunt holds the Chair in Flow in Porous Media at Imperial College London's Department of Earth Science & Engineering within the Faculty of Engineering. He has held leadership roles, including Head of the Department (2006–2011) and Head of the Petroleum Engineering and Rock Mechanics (PERM) Group (1999–2006). His expertise spans multiphase flow in porous media, with applications in carbon storage, contaminant transport, and reservoir engineering. Blunt is an Editor-in-Chief of Transport in Porous Media and directs iRock Technologies in China. Education: - PhD in Theoretical Physics (1988), Cambridge University - MA in Theoretical Physics (1985), Cambridge University Research Interests: Blunt's work focuses on pore-scale imaging and modeling of displacement processes in porous systems, including CO2 storage, hydrogen storage, and surfactant flooding. His interdisciplinary approach combines experimental, theoretical, and numerical methods. Key themes include wettability effects, Ostwald ripening, and pore network modeling. Awards & Honors: - Fellow of the Royal Society (2024) - Fellow of the Royal Academy of Engineering (2019) - Darcy Award (2012) - Lester U. Uren Award (2011) Advising & Grants: Blunt has advised numerous projects and serves on editorial boards. He leads research teams at Imperial and collaborates with industry partners like Streamsim Technologies and iRock. Labs & Teams: He oversees the PERM Group and the Grantham Institute's energy transition initiatives. His work integrates computational models with experimental data to address global energy challenges.