Find Academic Supervisors

• Computational Fluid Dynamics
• Aeronautical Systems
• High-Order Numerical Methods
• +5 more

Dr. Antonios Antoniadis is a Lecturer in Computational Engineering Science and Director of the Computational Fluid Dynamics (CFD) Masters program at Cranfield University. He leads the VR/AR Laboratory within the Aircraft Integration Research Center and a research group focused on computational methods for fluid dynamics. His expertise spans aeronautical systems, turbulence modeling, and renewable energy technologies. Education: BEng in Automotive Engineering, University of Sussex MSc in Mechanical Engineering, University College London PhD in Aerospace CFD, Cranfield University (2013) Research Interests: Dr. Antoniadis develops cutting-edge computational frameworks for engineering challenges. His work includes high-order numerical methods on unstructured grids, data-driven turbulence models, and multi-physics simulations. Applications range from helicopter aerodynamics and wind-farm optimization to supersonic flow analysis and fluid-structure interactions in morphing UAVs. He integrates AI/ML techniques for turbulence modeling and design automation, advancing sustainable aerospace solutions. Publication Trends: Recent articles highlight advancements in rotorcraft CFD, shock absorber fluid dynamics, and high-performance solver development. Predominant themes include validation of high-order schemes for transonic flows, vortex dynamics in hovering rotors, and scalable algorithms for renewable energy systems. His work consistently bridges theoretical computational methods with industrial aerospace applications. Awards: Fellowship of the Higher Education Academy (FHEA) Labs & Teams: Dr. Antoniadis directs a VR/AR laboratory pioneering human-computer interaction for CAE applications. His research group collaborates with industry partners (e.g., BAE Systems, Airbus, Red Bull Racing) on projects involving aerodynamic prediction, multi-phase flows, and HPC parallelization.

Jan H.M. ten Thije BoonkkampView profile

Associate Professor

• Numerical Analysis
• Partial Differential Equations (PDEs)
• Finite Volume Methods
• +10 more

Jan H.M. ten Thije Boonkkamp is an Associate Professor at Eindhoven University of Technology (TU/e), affiliated with the Intelligent Lighting Institute and the Department of Mathematics and Computer Science. His work bridges mathematical theory and applied computational sciences. Academic Background: MSc in Applied Mathematics (University of Twente, 1984) Current Roles: Associate Professor, Project Manager for EU-funded initiatives Key Collaborations: IIT Kanpur (2015 Visiting Professor), Philips Research Laboratories His research focuses on numerical methods for partial differential equations (PDEs) with applications in computational illumination optics and conservation laws . He develops: Freeform optical systems using optimal transport theory Complete flux schemes for hyperbolic systems Nonlinear PDE models for refracting surfaces Least-squares solvers for complex geometrical optics Recent publications (2025) highlight his interdisciplinary contributions to: Novel optical design frameworks combining Hamiltonian theory and optimal transport Advanced flux approximation schemes for fluid dynamics Computational optics solutions for energy-efficient lighting He leads projects like: MALIOD (Machine Learning for Illumination Optics Design, 2021-2026) PhotoLitho (Aberration compensation, 2020-2027) Intelligent Lighting (3rd tier, 2020-2025) His work contributes to UN Sustainable Development Goals through energy-efficient optical technologies.

Andrea ReichenbergerView profile

Visiting Professor

• Women and Gender Studies in STEM (MINT)
• History and Philosophy of Computer Science and AI
• History and Philosophy of Mathematics and Physics

Andrea Reichenberger is a visiting professor in the history of technology at the Department of Science, Technology and Society (STS) at the Technical University of Munich (TUM). She holds a PhD in philosophy of technology from the University of Paderborn and has held roles including research group leader at the University of Siegen and visiting professor at TUM. Her research focuses on women and gender in STEM, history and philosophy of mathematics/physics/CS/AI, and ethical dimensions of science. Currently, she leads a DFG project on women in quantum physics history and another on visual-spatial communication (ViCom SPP 2329). Her awards include a Best Paper Award (2009) and certificates from mathematical logic institutions. She actively organizes events like the 2025 workshop on ethics and computer science at the Deutsches Museum. She has authored a monograph on Émilie du Châtelet (Springer 2016) and over 50 articles, including peer-reviewed contributions to journals like *Physics Today* and *History and Philosophy of Logic*. Education: PhD in Philosophy of Technology (University of Paderborn) Grants: DFG projects (2022-2025; 2025-2028) Publications: 50+ articles, 2 books, edited volumes on women in science Teaching: Develops digital methods for HPS education, leads courses on technology history and gender studies Her work bridges history of science with contemporary ethical challenges, emphasizing sustainability through historical inquiry.

Wolfgang A. WallView profile

Professor

• Computational Mechanics
• Fluid-Structure Interaction
• Multi-Field and Multi-Scale Problems
• +5 more

Prof. Wolfgang A. Wall is a Professor of Numerical Mechanics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design. He leads the Chair of Computational Mechanics, established in 2003, and serves as Rector of CISM (International Centre for Mechanical Sciences) in Udine, Italy. His research focuses on computational mechanics, including fluid-structure interaction, multi-field and multi-scale problems, and applications in biophysics and biomedicine. He has pioneered numerical methods for complex simulations, integrating modeling, algorithm development, and high-performance computing. Key achievements include ERC Advanced Grants, EUROMECH Fellow status, and membership in the Bavarian and Austrian Academies of Sciences. Educational background: Studied at the University of Innsbruck, earned his doctorate from the University of Stuttgart after a research stay at Princeton University. His work spans engineering disciplines, emphasizing uncertainty quantification and machine learning in computational frameworks. He has contributed to lung mechanics modeling, cardiovascular simulations, and tumor growth analysis, with over 300 publications. Current projects address additive manufacturing, solid-state batteries, and patient-specific medical modeling. Awards: ERC Advanced Grant (2021), Prandtl Medal (2016), Bavarian Academy Membership (2017) Grants: Extensive funding for computational mechanics and biomedical engineering projects Labs: Chair of Computational Mechanics lab at TUM, collaborating with CISM and international partners

• Numerical Methods
• Semiconductor Devices
• Perovskite Photovoltaics
• +7 more

Patricio Farrell is a Senior Lecturer and Research Group Leader in Applied Mathematics at the Weierstrass Institute Berlin (WIAS). His work bridges mathematical theory and engineering applications, focusing on numerical methods for semiconductor devices, perovskite solar cells, and neuromorphic materials. He leads the 'Methods for Innovative Semiconductor Devices' group at WIAS and serves as Vice Chair of the Committee for Mathematical Modeling, Simulation, and Optimization (KOMSO). Affiliations: WIAS Berlin, Freie Universität Berlin (Privatdozent), Berlin Mathematical School (Mentor) Educations: PhD in Applied Mathematics (University of Oxford), Diplom (University of Hamburg/University of Bath) His research emphasizes structure-preserving numerical methods for drift-diffusion systems, with applications ranging from next-generation semiconductors to photonic crystal lasers. He develops simulation tools like ChargeTransport.jl and contributes to open-source numerical libraries such as VoronoiFVM.jl. Key projects include the ARISE initiative for semiconductor solvers (€1M), Excellence in Photonic Crystal Surface Emitting Lasers (PCSELence), and MATH+ projects on perovskite devices and semiconductor mechanics. Farrell is a scientific ambassador for Brain City Berlin and actively publishes in top journals, emphasizing computational methods for energy transition and material science challenges.

• Machine Learning
• Computational Fluid Dynamics
• Environmental Engineering
• +6 more

Stelios Rigopoulos is a Professor (Reader in Thermofluids) at Imperial College London's Department of Mechanical Engineering, part of the Faculty of Engineering. He holds a PhD in Chemical Engineering from UCL and has held academic positions at the University of Manchester and Imperial College London since 2010. His research focuses on advanced computational methods, including population balance, machine learning, and CFD, applied to environmental and engineering challenges like aerosols, nanoparticles, and net-zero energy systems. Education: MEng (Chemical Engineering, Aristotle University of Thessaloniki, 1997), MSc (Environmental Technology, UMIST, 1999), PhD (Chemical Engineering, UCL, 2003). Research interests include machine learning for sustainable energy, contrail climate impacts, volcanic ash dynamics, and CFD-PBE modelling. His group developed CPMOD, an open-source population balance solver, and authored the monograph 'Population Balance of Particles in Flows.' Awards include the Royal Society University Research Fellowship (2007 Hinshelwood Prize). His work addresses net-zero fuels, aerosol dynamics, and nanoparticle synthesis for battery materials.

• Nuclear Engineering
• Materials Science
• Nuclear Materials
• +3 more

Lorenzo Vergari is an Assistant Professor in the Department of Nuclear, Plasma & Radiological Engineering at the University of Illinois. His research focuses on nuclear materials, particularly graphite in high-temperature environments, molten salts, and tritium management. He holds a B.S. from Politecnico di Milano (2016), M.S. degrees from Politecnico di Milano (2018) and Politecnico di Torino (2019), and a Ph.D. from UC Berkeley (2023). He is affiliated with the Advanced Blankets & Coolants Laboratory. His professional roles include membership in the ANS (2020–2024), ASME Task Group on Graphite Issues in MSRs (2022–present), and IAEA Working Party on Raman Characterization of Graphite (2023–present). He is a licensed Professional Engineer in Italy (2020). Research interests emphasize corrosion mechanisms, hydrogen behavior in graphite, and computational modeling for nuclear systems. His work addresses challenges in molten salt reactors, waste disposal, and fusion-relevant materials. Recent studies investigate surface fluorination effects, neutron activation impacts, and tritium desorption dynamics. Key achievements include the Young Researcher Award (2020), Berkeley Graduate Fellowship (2019), and recognition as an excellent teacher at UIUC (2024–2025). He teaches NPRE 330 and NPRE 498 NC3/NC4 courses, focusing on materials in nuclear engineering and nuclear chemical engineering.

Martine BaelmansView profile

Professor

• Plasma Physics
• Nuclear Fusion
• Thermal Engineering
• +6 more

Martine Baelmans is a Full Professor at the Faculty of Engineering Sciences at KU Leuven, where she leads the Applied Mechanics and Energy Conversion (TME) research group. She serves as the subdivision head of the EnergyVille TME - Baelmans Subdivision and is an active member of the EnergyVille Division, KIEM – KU Leuven Institute for Energy and Society, and Leuven.AM – KU Leuven Institute for Additive Manufacturing. Her extensive academic service includes roles on the Faculty Council of Engineering Sciences, Department Council of Mechanical Engineering, and as a vice-rector member of the Education Quality Assurance Committee and KU Leuven LERU Curriculum Vitae Coordination. Professor Baelmans' research spans multiple areas of energy conversion, thermal engineering, and nuclear fusion. Her work focuses on plasma edge simulations for nuclear fusion reactors, thermal-hydraulics of liquid metal systems, optimization of heat transfer devices, and district heating network design. She employs advanced computational methods including finite-volume, Monte Carlo, and topology optimization techniques to address complex engineering challenges in energy systems. Her recent publications demonstrate expertise across a broad spectrum of energy-related research. The articles reveal a strong focus on nuclear fusion plasma edge modeling, thermal management systems, and optimization of energy infrastructure. The work spans from fundamental plasma physics to practical engineering applications in district heating networks and compact heat exchangers, showing both theoretical depth and practical relevance to energy system design. Professor Baelmans has received significant research funding for multiple projects including 'Modeling and optimization of transport phenomena in electrochemical processes' (2024-2028), 'Optimization of balanced compact heat exchangers' (2024-2028), and several projects related to plasma edge simulations for nuclear fusion reactors. Her research group actively contributes to advancing the scientific understanding of plasma physics for fusion energy and developing innovative thermal engineering solutions.

• Clinical biomechanics of the shoulder
• Computational shoulder models
• Finite element analysis
• +7 more

Eva C. Herbst is a Postdoctoral Researcher in Shoulder Biomechanics at ETH Zurich's Institute for Biomechanics, Department of Health Sciences and Technology. She works in close collaboration with Prof. Dr. Stephen Ferguson at ETH and Prof. Dr. med. Philipp Moroder at the Schulthess Clinic, developing computational models to investigate dynamic joint loading in patients and maximize clinical impact. Her research integrates multi-body dynamics and finite element modeling to create shoulder biomechanics models for implant development and patient analysis. With a background in comparative biomechanics and paleontology, she maintains a strong interest in the link between form and function across biological contexts, applying evolutionary perspectives to clinical problems. Clinical biomechanics of the shoulder Computational modeling for implant development Finite element analysis and multibody dynamics Biomechanical analysis of patient-specific scenarios Comparative biomechanics across evolutionary time scales Dr. Herbst has developed several important computational tools that have gained recognition in the biomechanics community, including Spherical Frame Projections for visualizing joint range of motion, Trabecular Segmentation techniques for bone analysis, and MyoGenerator, a Blender add-on for 3D muscle modeling. She founded Finite Element Zurich to make finite element modeling more accessible by sharing resources, code, and workflows. Her publication record shows a clear progression from evolutionary biomechanics toward clinical applications, with recent work focusing on shoulder arthroplasty, osseous shoulder morphology, and patient-specific computational modeling. Her earlier research examined paleopathology in early tetrapods, cervical morphology in sloths, and salamander locomotion. She actively shares her research tools through GitHub, FigShare, and Morphosource, demonstrating a strong commitment to open science practices.

• Composite materials
• Structural fracture and failure
• Structural dynamics
• +5 more

Zhenmin Zou is a Lecturer in Mechanical and Aerospace Engineering at Nanjing University of Aeronautics & Astronautics (NUAA), China. He holds a BEng, MEng, and PhD from NUAA. His career includes roles as a Research Associate and Research Fellow at UMIST and the University of Manchester. His research focuses on composite materials, structural fracture mechanics, thermomechanical behavior of hybrid composites, and biomechanical systems. Key areas include fiber hybrid composites, microstructural analysis, and advanced manufacturing techniques for biomedical applications. Education: BEng (Aircraft Engineering, NUAA), MEng (Solid Mechanics, NUAA), PhD (Aircraft Engineering, NUAA). Research Interests: Composite materials and structures Structural dynamics and fracture High strain rate material response Biomechanics and bioinspired designs Finite element modeling Thermomechanical behavior of composites Recent work emphasizes fiber hybridization effects, micro-stress fields in composites, and fatigue characterization of joints. His contributions to the Manchester Biomanufacturing Centre and Structural and Fire Engineering themes align with UN Sustainable Development Goals. Collaborations include international institutions and industry partners in materials science and biomedical engineering.

Stephan SimonisView profile

Research Fellow

• Applied Mathematics
• Computational Mathematics
• Numerical Analysis
• +7 more

Dr. Stephan Simonis is a Research Fellow at the Karlsruhe Institute of Technology (KIT), working within the Department of Mathematics and specifically with the Institute for Applied and Numerical Mathematics (IANM2). He leads the LBRG Mathematical Modeling and Numerics Lab since 2023 and serves as an associate editor for the Elsevier journal Examples and Counterexamples since 2024. He is also a member of the steering committee for the EU-funded FALCON project (doi: 10.3030/101138305). Dr. Simonis completed his education as follows: BSc and MSc in Mathematics at KIT, Germany and KTH, Sweden (2011-2018) PhD in Mathematics at KIT (2023), with research visits at UFRGS, Brazil and ETH Zürich, Switzerland Dr. Simonis's research focuses on Applied and Computational Mathematics, particularly in developing and analyzing numerical methods for partial differential equations. His work centers on lattice Boltzmann methods for multi-physics simulations, including applications to fluid flow, blood flow, and solid mechanics. He integrates robust numerical schemes with uncertainty quantification and machine learning, leveraging high-performance computing to explore complex parameter spaces. His research has significant applications in engineering and scientific computing. His publication record demonstrates a strong focus on numerical analysis of lattice Boltzmann methods, with recent work expanding into uncertainty quantification, machine learning integration, and applications to complex fluid dynamics problems. The breadth of his work spans theoretical analysis, algorithm development, and practical implementation in the OpenLB library, with publications in top journals across mathematics, physics, and engineering disciplines. Dr. Simonis has received numerous accolades for his work: ERASMUS+ EQF7 scholarship (2016-2017) DAAD PPP mobility funding (2019) KIT Faculty Teaching Award (2021) KHYS Networking Grant (2022) KHYS ConYS Grant (2024) Oberwolfach Leibniz Graduate Student (2024) NHR Starter project (2024) DAAD PRIME fellowship (2025) Dr. Simonis actively mentors students through various thesis projects in mathematics, fluid dynamics, and high-performance computing. His current open thesis topics focus on lattice Boltzmann methods, relaxation schemes, and stability analysis. He has secured significant research funding including the DAAD PRIME fellowship and NHR Starter project, demonstrating strong support for his research program. His teaching portfolio includes Computational Fluid Dynamics and Simulation Lab, Parallel Computing, and Project-centered Software Lab across multiple semesters. As leader of the LBRG Mathematical Modeling and Numerics Lab since 2023, Dr. Simonis oversees a research group focused on developing advanced numerical methods. His involvement in the EU-funded FALCON project and as associate editor for Examples and Counterexamples further demonstrates his growing leadership in the computational mathematics community.

Florentina ToneView profile

Professor

• Numerical Analysis
• Partial Differential Equations
• Convergence Analysis
• +4 more

Dr. Florentina Tone is a Professor in the Department of Mathematics and Statistics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. She has been a faculty member since 2006, contributing to both undergraduate and graduate education through classroom and online instruction. Her academic background includes a Ph.D. in Mathematics from Indiana University and both a Master’s and Bachelor’s degree in Mathematics from the University of Bucharest, Romania. Dr. Tone's research is centered on numerical analysis of partial differential equations , with a focus on convergence, stability, and error estimation of numerical schemes. Her work applies to fluid dynamics, phase field models, and coupled physical systems. She has published in leading journals such as SIAM Journal on Numerical Analysis and Numerische Mathematik , and has presented at numerous national and international conferences. The analysis of her recent publications reveals a consistent focus on rigorous mathematical validation of numerical methods, particularly finite element and finite difference schemes for time-dependent PDEs. Her work spans applications in fluid mechanics, heat transfer, chemotaxis, and electromagnetics, demonstrating strong interdisciplinary reach within applied mathematics. She has been recognized for her contributions with the Distinguished Research and Creative Activities Award from UWF. This honor reflects her sustained excellence in scholarly output. Dr. Tone actively supervises student research projects and teaches courses such as Complex Analysis, Numerical Analysis, Linear Algebra, and Calculus. While specific grant details are not listed, her sustained publication record and award suggest active research funding. She has mentored students through research advising, contributing to academic development within the department. She is affiliated with the Department of Mathematics and Statistics, which supports research through seminars, colloquia, and student associations such as the Math Association. The department also hosts technical reports and research labs, including the CSDA Lab, which may support data-intensive computational work.

Jia LiuView profile

Professor

• Computational Mathematics
• Numerical Linear Algebra
• Sparse Matrix Computations
• +9 more

Dr. Jia Liu is a Professor and Chair of the Department of Mathematics and Statistics at the University of West Florida, within the Hal Marcus College of Science and Engineering. She has been a key academic figure at UWF since 2006, leading both research and departmental initiatives in computational and applied mathematics. Her educational background includes a Ph.D. in Mathematics from Emory University, funded by the National Science Foundation, focusing on preconditioned Krylov subspace methods for incompressible flow problems. She earned her M.S. and B.A. in Mathematics from Central China Normal University, where her bachelor's thesis received the highest honor. Dr. Liu's research lies at the intersection of numerical linear algebra, scientific computing, and interdisciplinary applications. Her primary interests include: Numerical solvers for large sparse linear systems Krylov subspace iterative methods Preconditioning techniques Applications to Navier-Stokes and optimization problems Geometric and topological analysis of ellipsoids Complex networks and community detection via spectral clustering Machine learning for disease prediction and biological modeling The trends in her publications reflect a consistent focus on robust numerical algorithms with applications across fluid dynamics, network science, and biomedical modeling. Her work emphasizes both theoretical development and practical implementation in high-performance computing environments. Dr. Liu has served as an editor and editorial board member for several peer-reviewed journals and regularly reviews submissions. While specific awards are not listed, her sustained publication record in prestigious venues such as SIAM Journal on Scientific Computing and Journal of Biological Dynamics underscores her scholarly impact. As department chair and professor, she plays a central role in academic advising, curriculum development, and research mentorship. She teaches core courses including Differential Equations, Numerical Analysis, and Real Analysis, contributing significantly to both undergraduate and graduate education. Her leadership extends to managing research grants and fostering collaborations across disciplines. Though no formal lab name is mentioned, her research activities suggest involvement with computational modeling groups, likely associated with applied mathematics and data science initiatives at UWF. Her ongoing work continues to advance numerical methods for complex systems in science and engineering.

Dinesh K. PaiView profile

Professor

• Sensorimotor Computation
• Computer Graphics
• Robotics
• +5 more

Dinesh K. Pai is a Professor and Tier 1 Canada Research Chair in the Department of Computer Science at the University of British Columbia, where he directs the Sensorimotor Systems Laboratory. He holds cross-appointments at UBC’s Institute for Computing, Information and Cognitive Systems (ICICS), Institute of Applied Mathematics, Graduate Program in Neuroscience, ICORD International Collaboration on Repair Discoveries, and Brain Research Centre. His educational background includes a Ph.D. from Cornell University and a B.Tech. from the Indian Institute of Technology, Madras. His research spans sensorimotor computation with applications in computer graphics, robotics, biomechanics, haptics, and neurobiology. Recent work focuses on human body modeling, garment simulation, soft tissue dynamics, and friction measurement, leveraging machine learning and physics-based simulation techniques. Pai’s publication trends reveal a strong interdisciplinary focus on human-centered computational models, with increasing integration of machine learning for 3D pattern adjustment, body shape generation, and cloth simulation. His work bridges computer graphics with biomechanics and neuroscience through sensorimotor computation. UBC’s 2012 Killam Research Prize CHCCS 2020 Achievement Award Tier 1 Canada Research Chair His research has been supported by significant grants including NSERC Discovery and Idea-to-Innovation grants, a Major Thematic Grant from the Peter Wall Institute for Advanced Studies, and a Human Frontier Science Program grant for studying CNS modularity. As leader of ICICS’ Human Sensorimotor Systems theme, he directs a multidisciplinary team exploring computational models of human sensorimotor function. The Sensorimotor Systems Laboratory operates state-of-the-art facilities featuring a Vicon MX motion capture system, LMI HDI body scanner, eye trackers, skin measurement instruments, EMG systems, haptic interfaces, and robotic platforms for advancing human-computer interaction research.

• Multi-compartment modeling
• Cerebral arterial circulation
• Electrical conductivity
• +5 more

Maryamolsadat Samavaki is a Researcher affiliated with the Computing Sciences Mathematics Research Centre , focusing on computational modeling of cerebrovascular dynamics and neuroelectromagnetism. Her work bridges biomedical engineering and applied mathematics through advanced numerical methods. Key research areas include EEG source localization , transcranial stimulation , and multi-compartment head modeling . Develops spatiotemporal hemodynamic models to analyze microcirculation and blood volume fractions. Applies L1-norm optimization and metaheuristic algorithms for neurostimulation montage design. Recent publications explore cerebral circulation's impact on electrical conductivity and in silico imaging techniques using anatomical atlases . Collaborations emphasize boundary-fitted meshing for subcortical structures in EEG modeling.