Find Academic Supervisors

Howard A. StoneView profile

Professor

• Fluid Dynamics
• Microfluidics
• Complex Fluids
• +7 more

Howard A. Stone is the Donald R. Dixon '69 and Elizabeth W. Dixon Professor and Neil A. Omenn '68 University Professor in the Department of Mechanical and Aerospace Engineering at Princeton University's School of Engineering and Applied Science. He leads the Complex Fluids Group, conducting interdisciplinary research at the intersection of engineering, physics, chemistry, and biology. Dr. Stone received his B.S. in Chemical Engineering from UC Davis (1982) and Ph.D. from Caltech (1988). After a postdoctoral year at Cambridge University, he joined Harvard University's faculty in 1989, where he became the Vicky Joseph Professor of Engineering and Applied Mathematics before moving to Princeton in 2009. His research focuses on fluid dynamics phenomena across multiple scales, with particular emphasis on microfluidics, complex fluids, and biomechanics . His group investigates multiphase flows, colloidal systems, bio-inspired fluid phenomena, and physicochemical hydrodynamics. Recent work spans from fundamental studies of thin film drainage and droplet dynamics to applications in biological systems including blood flow, bacterial transport, and biomolecular condensates. The Complex Fluids Group employs experimental, theoretical, and computational approaches, often collaborating with industry partners on applications from medical devices to industrial processes. Analysis of his recent publications reveals a continued expansion into biological applications of fluid dynamics, with increasing focus on cellular mechanics, biomolecular condensates, and pathological hemodynamics, while maintaining strong contributions to fundamental fluid mechanics in complex systems. His work consistently bridges theoretical insights with practical applications across multiple disciplines. Major honors include: Election to the National Academy of Engineering (2009) Election to the National Academy of Sciences (2014) APS Fluid Dynamics Prize (2016) G.K. Batchelor Prize in Fluid Dynamics (2008) NSF Presidential Young Investigator Award Professor Stone has advised numerous PhD students through their Final Public Oral examinations, with recent graduates working on topics spanning microfluidics, bacterial transport, and complex fluid phenomena. His research has been supported by diverse funding sources including NSF, NIH, and industry partnerships. The Complex Fluids Group maintains state-of-the-art experimental facilities in the Engineering Quadrangle, featuring specialized equipment for microfluidics, rheology, and interfacial phenomena investigations. The group actively collaborates with researchers across Princeton and globally, maintaining strong connections to both academic and industrial partners working on fluid-related challenges.

John OakeyView profile

Professor

• Microfluidics
• Microscale transport phenomena
• Tissue engineering and regenerative medicine
• +4 more

John Oakey is a Professor and Graduate Coordinator in the Department of Chemical and Biomedical Engineering at the University of Wyoming, with additional affiliations to the INBRE Program, Molecular and Cellular Life Sciences Program, and Materials Science and Engineering Program. Education Postdoctoral Fellow, Center for Engineering in Medicine, Massachusetts General Hospital & Harvard Medical School (2007–2010) Ph.D. Chemical Engineering, Colorado School of Mines (2003) M.S. Chemical Engineering, Colorado School of Mines (1999) B.S. Chemical Engineering, Penn State University (1997) Research Interests Oakey’s laboratory integrates fluid dynamics, colloidal science and materials science to understand how biological systems behave under flow, on surfaces and within complex 3-D geometries. A unifying theme is the use of microfabrication and microfluidics to create new diagnostic, prognostic and therapeutic platforms. Current thrusts include: Heterogeneous biomaterials: self-assembled particulate tissue scaffolds whose mechanical and transport properties can be temporally programmed. Inertial microfluidics: exploiting lift forces for membrane-free particle sorting, enrichment and diagnostics. Multi-temporal analysis by flow cytometry: development of closed-loop, high-throughput microfluidic cytometers for longitudinal single-cell studies. Publication Trends From 2025 back to 2010, Oakey’s articles reveal a consistent trajectory that marries fundamental physics (microtubule mechanics, inertial focusing) with translational applications (cell encapsulation, tissue scaffolds, drug delivery). Recent work (2023-2025) increasingly targets injectable granular hydrogels, single-cell therapeutic delivery and sustainable carbon-sequestering living materials, demonstrating an evolution from microscale transport phenomena to macroscopic biomedical and environmental impact. Scientific Awards No named awards are listed in the supplied text. Advising & Coordination Roles As Graduate Coordinator for the Department of Chemical and Biomedical Engineering, Professor Oakey oversees graduate program development and student mentoring. While no individual students are named, his role implies active supervision of M.S. and Ph.D. advisees in chemical and biomedical engineering. Laboratory & Teams The Oakey Research Group operates from the Energy and Environmental Research Building (EERB 435A) at the University of Wyoming. The lab enjoys R1-level research infrastructure and collaborates broadly with the Wyoming INBRE network, the Molecular and Cellular Life Sciences Program, and the Materials Science and Engineering Program.

Petros KoumoutsakosView profile

Professor

• Machine Learning
• Computational Fluid Dynamics
• Turbulence Modeling
• +3 more

Petros Koumoutsakos is the Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering at Harvard University's School of Engineering and Applied Sciences (SEAS), where he also serves as Area Chair for Applied Mathematics. His research integrates machine learning with computational science to advance understanding of complex systems, including fluid dynamics, turbulence modeling, and biomedical applications. He leads the CSE Lab, focusing on high-performance computing and interdisciplinary collaborations such as a recent study with Citadel Securities and Google Cloud to simulate heart disease in cloud environments. Key research interests include reinforcement learning for turbulence closures, generative models for PDE solutions, and physics-informed AI for biomedical imaging and wildfire prediction. He was awarded the PRACE HPC Excellence Award (2023) for contributions to high-performance computing. His work bridges computational methods with real-world applications, emphasizing interpretability and scalability in multiscale systems. Grants & Collaborations: Leadership in multi-institutional projects, including turbulence modeling via reinforcement learning and cloud-based HPC studies. Labs/Teams: Director of the CSE Lab, advancing AI, computational fluid dynamics, and biomedical simulations.

Jurgen BecqueView profile

Associate Professor

• Cold-formed steel structures
• Stainless steel structural behavior
• Local and overall buckling interaction
• +3 more

Dr. Jurgen Becque is an Associate Professor in Structural Engineering at the University of Cambridge's Department of Engineering. He specializes in cold-formed steel structures, stainless steel structural behavior, and stability analysis, with a focus on local-overall buckling interaction and innovative design methodologies. His work bridges experimental investigations with computational modeling and machine learning applications. Research Interests: Cold-formed steel structural systems Stainless steel column stability Local and overall buckling interaction Mechanics-based design optimization Machine learning for structural behavior prediction Recent publications demonstrate expertise in cross-sectional stability, connection mechanics, and composite systems like UHPC-confined stainless steel columns. His work addresses both monotonic and cyclic loading scenarios, contributing to Eurocode 3 design standards.

Hrvoje JasakView profile

Professor

• Computational Fluid Dynamics (CFD)
• Continuum Mechanics
• Numerical Simulation Methods
• +5 more

Hrvoje Jasak is a Professor of Continuum Physics at the Department of Physics (Cavendish Laboratory), University of Cambridge. He holds a fellowship at Christ’s College. His academic journey includes a BSc in Mechanical Engineering from the University of Zagreb (1992) and a PhD in CFD from Imperial College London (1996). Prior to academia, he held engineering roles at CD-adapco (now Siemens PLM), Nabla Ltd, and Ansys-Fluent Inc., contributing to CFD software development. His research focuses on numerical simulation methods, continuum physics, multiphase flows, naval hydrodynamics, and software development. He co-created OpenFOAM, chairs its Numerics Technical Committee, and leads the Computational Continuum Mechanics (CCM) research group within the Laboratory for Scientific Computing. His work integrates advanced numerical techniques like the partially rotating grid method, finite volume algorithms, and multiphysics coupling frameworks. Jasak is a seasoned developer with 25+ years of C++ expertise, having authored ~1 million lines of code. His group’s projects include the Naval Hydro Pack , fluid-structure interaction solvers, and the Eulerian multi-fluid model for dense sprays. He actively collaborates on international initiatives like the NUMAP-FOAM Summer School and the OpenFOAM community. His teaching spans MPhil programs, PhD supervision, and specialized CFD courses. Current research explores wave-ice interaction, lubricated contact modeling, and open-source software innovation. The CCM group’s work bridges academia and industry, addressing challenges in marine engineering, energy systems, and computational mechanics.

Wengong JinView profile

Assistant Professor

• AI for drug discovery
• Generative AI models
• Geometric deep learning
• +5 more

Wengong Jin is an Assistant Professor at the Khoury College of Computer Sciences, Northeastern University, and a visiting research scientist at the Eric and Wendy Schmidt Center at the Broad Institute. He holds a PhD from MIT CSAIL, advised by Prof. Regina Barzilay and Prof. Tommi Jaakkola. Research Interests: His work focuses on geometric and generative AI models for drug discovery, biology, and chemical engineering. Key areas include equivariant neural networks (e.g., FAFormer), diffusion models for binding energy prediction, antibody/enzyme design (RefineGNN, SurfPro), and molecular design through graph neural networks (Junction Tree VAE). He also explores domain generalization and systems for autonomous molecular discovery. Publications: His research has been published in top venues like NeurIPS, ICLR, ICML, Nature, Science, and Cell. Recent breakthroughs include discovering novel antibiotics using explainable AI and designing synergistic drug combinations for cancer treatment. Awards: He has received the BroadIgnite Award, Dimitris N. Chorafas Prize, and MIT EECS Outstanding Thesis Award for his contributions to computational biology and AI-driven drug discovery. Teaching: Currently teaches a PhD seminar on AI for Science, focusing on integrating machine learning into scientific discovery processes.

Ian FrigaardView profile

Professor

• Non-Newtonian Fluid Mechanics
• Visco-plastic Fluids
• Petroleum Engineering
• +3 more

Ian Frigaard is a Professor in the Department of Mechanical Engineering at the University of British Columbia (UBC), affiliated with the Faculty of Applied Science. He also holds an appointment in the Department of Mathematics. His research group operates in UBC's Complex Fluids Lab, focusing on interdisciplinary studies combining mathematical, experimental, and computational approaches. Education: B.Sc. (University of Wales) M.Sc. (University of Oxford) D.Phil. (University of Oxford) C.Math. (Certificate in Mathematics) Research Interests: Professor Frigaard specializes in non-Newtonian fluid mechanics, particularly the mechanics of visco-plastic (yield stress) fluids. His work addresses industrial challenges in petroleum engineering, including well cementing, leakage prevention, and abandonment techniques related to GHG emission control and environmental protection. Research methodologies span theoretical modeling, experimental validation, and computational simulations. Publication Trends: Recent work (2021–2023) emphasizes bubble dynamics in complex fluids, displacement flows in annular geometries, wellbore integrity modeling, and stochastic risk assessment for oil/gas operations. Publications frequently appear in top-tier journals like the Journal of Fluid Mechanics and Journal of Non-Newtonian Fluid Mechanics . Awards & Honors: CSME Fluid Mechanics Medal (2024) Stanley G. Mason Award, Canadian Society of Rheology (2022) Killam Research Prize, UBC (2019) Academic Leadership: Leads a research group of 10+ graduate students and postdocs. Provides summer internships and collaborates extensively with the petroleum industry. Research is supported by industrial partnerships and institutional grants. Facilities: Conducts experiments in UBC's Complex Fluids Lab, equipped for advanced rheological measurements and flow visualization.

Maarten de HoopView profile

Professor

• Seismic Wave Analysis
• Inverse Problems
• Deep Learning
• +5 more

Maarten de Hoop is the Simons Chair and Professor of Computational and Applied Mathematics at Rice University, part of the George R. Brown School of Engineering. He holds visiting roles at MIT and the Chinese Academy of Sciences. His research spans seismic wave analysis, inverse problems, deep learning, and planetary seismology. He earned his Ph.D. in Technical Sciences from Delft University of Technology (1992), and earlier degrees from Utrecht University. Notable awards include the 1996 J. Clarence Karcher Award and 2001 Fellowship from the Institute of Physics. His work integrates computational mathematics with geophysics, focusing on extracting signal information from large datasets, developing novel inverse scattering methods, and applying deep learning to geoscience challenges. Recent studies include transformer models for in-context learning, semialgebraic neural networks, and seismic waveform foundation models like SeisLM. He leads the Geo-Mathematical Imaging Group, fostering interdisciplinary projects in planetary missions and data-driven discovery.

Daria FrankView profile

Senior Lecturer

• Fluid Mechanics
• Computational Mathematics
• Environmental Fluid Dynamics
• +3 more

Daria Frank is a Senior Teaching Associate in Computational Mathematics at the Department of Applied Mathematics and Theoretical Physics (DAMTP), University of Cambridge, a position held since 2023. Previously, she served as Sultan Qaboos Early-Career Research Fellow and College Lecturer in Mathematics at Corpus Christi College (2020-2023), Director of Studies in Mathematics at Selwyn College (2019-2020), and Research Associate in Fluid Mechanics at DAMTP (2015-2019). Her academic foundation includes a PhD from DAMTP, University of Cambridge (2012-2015), Part III Mathematical Tripos at Cambridge (2009-2010), Diploma in Mathematics from Friedrich-Alexander-University of Erlangen-Nuremberg (2010-2011), and undergraduate studies in Mathematics and Physics at the same institution (2006-2009). Dr. Frank's research centers on complex fluid phenomena with emphasis on buoyancy-driven environmental flows , rotating plume dynamics , and practical engineering applications . Her work investigates pollution dispersal mechanisms, tornado formation processes, and energy-efficient building systems through rigorous theoretical and experimental frameworks. Key contributions address multiphase interactions in stratified environments and vortex behavior under rotational forces, bridging fundamental fluid dynamics with real-world environmental challenges. Publication trends reveal consistent focus on geophysical and environmental fluid mechanics, with recurring themes of density stratification effects, multiphase plume behavior, and rotational influences across atmospheric, oceanic, and built environments. Her work demonstrates strong interdisciplinary connections between theoretical modeling and practical engineering solutions. Dr. Frank held the prestigious Sultan Qaboos Early-Career Research Fellowship, supporting her investigations into fluid mechanics phenomena. Her academic service includes significant teaching responsibilities as Director of Studies in Mathematics at Corpus Christi College. As Director of Studies, she oversees undergraduate mathematics education while conducting research within DAMTP's fluid dynamics community. Her Sultan Qaboos Fellowship provided dedicated research time for fluid mechanics investigations, complementing her teaching role through integration of cutting-edge research into pedagogy. Current work continues to explore environmental fluid dynamics with potential applications in climate modeling and sustainable engineering.

• Stochastic Differential Equations
• Financial Mathematics
• Partial Differential Equations
• +5 more

Professor Ben Goldys is a distinguished academic at The University of Sydney's School of Mathematics and Statistics, where he conducts research at the intersection of pure mathematics and applied sciences. His work spans multiple disciplines including stochastic analysis, partial differential equations, and financial mathematics, with significant contributions to both theoretical frameworks and practical applications in science and finance. Goldys' research interests center on stochastic (ordinary and partial) differential equations and their applications. His specific focus areas include stochastic partial differential equations, stochastic geometric PDEs, stochastic boundary value problems, stochastic fluid dynamics, ergodic theory of infinite-dimensional diffusions, and applications in financial mathematics such as interest rate derivatives, credit risk, and stochastic volatility. His work bridges pure mathematical theory (Functional Analysis, PDEs, Ergodic Theory) with complex real-world problems across multiple domains. His research aligns with the University of Sydney Faculty of Science Research Strengths including Understanding the Universe, Fundamental Laws of Nature, Complex Systems, and Next Generation Materials. Professor Goldys has secured multiple significant research grants from the Australian Research Council, including recent projects such as 'Mathematics for future magnetic devices' (2024), 'Mathematics for breaking limits of speed and density in magnetic memories' (2019), and 'Novel Approaches for Problems with Uncertainties' (2015). His current research projects focus on geometric stochastic partial differential equations and applications in micromagnetism, mean field games in finance, stochastic boundary value problems, and stochastic Navier-Stokes equations on the rotating sphere. He maintains extensive international collaborations with institutions in Germany (University of Tuebingen), Italy (LUISS University), Poland (Institute of Mathematics Polish Academy of Sciences), and the United Kingdom (University of York), working on projects involving optimal control, stochastic systems with memory, and geometric stochastic PDEs. Goldys is an active member of the Applied Mathematics Research Group and The University of Sydney Nano Institute, contributing to interdisciplinary research initiatives that connect mathematical theory with cutting-edge technological applications.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +5 more

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

Anne E. WhiteView profile

Professor

• Magnetic fusion energy
• Plasma diagnostics
• Turbulent transport in plasmas
• +3 more

Anne E. White is the School of Engineering Distinguished Professor of Engineering and associate vice president for research administration at the Massachusetts Institute of Technology (MIT). She serves in the Department of Nuclear Science and Engineering within MIT's School of Engineering and is a key researcher at the Plasma Science and Fusion Center (PSFC). White has held significant leadership roles including NSE department head from 2019 to 2023 and co-chair of the MIT Climate Nucleus from 2021 to 2024. She currently chairs the Fusion Energy Sciences Advisory Committee (FESAC), providing federal advisory input to the U.S. Department of Energy Office of Science. White received her PhD in physics from UCLA, where she conducted research at the Electric Tokamak. Her early career included research positions at the National Spherical Torus Experiment at Princeton Plasma Physics Laboratory and the DIII-D National Fusion Facility at General Atomics before joining MIT as a faculty member. Her educational background laid the foundation for her expertise in plasma physics and fusion energy research. Professor White's research focuses on magnetic fusion energy, specifically on understanding turbulent transport in magnetically confined fusion plasmas. Her work spans diagnostic development, novel experimentation, and validation of nonlinear gyrokinetic codes. She aims to demonstrate nuclear fusion as a practical part of the world's sustainable energy future. Her group develops and uses radiometers, reflectometers, and interferometers to measure fluctuations in plasma density, temperature, and flows in tokamaks. This research is critical for improving predictive capabilities of turbulent transport models, which is essential for developing viable fusion reactors. Analysis of Professor White's recent publications reveals a strong focus on plasma diagnostics and turbulence measurements across multiple tokamak facilities. Her work spans experimental measurements on ASDEX Upgrade, Alcator C-Mod, NSTX, and DIII-D tokamaks, with particular emphasis on electron temperature fluctuations, turbulence characterization, and transport model validation. A significant theme is the development and application of novel diagnostic techniques for simultaneous measurements of multiple plasma parameters. Her research increasingly incorporates computational approaches, including gyrokinetic simulations and machine learning methods, to interpret experimental data and advance predictive capabilities in fusion plasma physics. Professor White has received numerous prestigious awards throughout her career: Fellow, American Physical Society Division of Plasma Physics (2019) Cecil and Ida Green Career Development Professor, MIT (2014) American Physical Society Katherine E. Weimer Award (2014) Fusion Power Associates Excellence in Fusion Engineering Award (2014) Junior Bose Award for Excellence in Teaching, MIT (2014) PAI Outstanding Faculty Award from MIT student chapter of the American Nuclear Society (2013) Norman C. Rosenbluth Career Development Professor, MIT (2012-2014) Department of Energy Early Career Award (2011-2016) Marshall N. Rosenbluth Outstanding Doctoral Thesis Award (2009) As an educator and mentor, Professor White has advised numerous students through MIT's Department of Nuclear Science and Engineering. She has taught courses including Principles of Plasma Diagnostics, Seminar in Fusion & Plasma Physics, and Introduction to Plasma Physics. Her leadership extends to developing educational resources, notably leading a team in 2018 to create a free MITx MOOC focused on nuclear science and engineering for global high school learners. Professor White has secured significant research funding through Department of Energy awards, including the Early Career Award (2011-2016) and various fusion energy fellowships throughout her career. Her research group at MIT's Plasma Science and Fusion Center has contributed to multiple major fusion facilities and has been instrumental in advancing understanding of plasma turbulence and transport. Professor White leads the Fusion and Plasmas Lab at MIT, which focuses on diagnostic development and turbulence measurements in fusion plasmas. Her team has made significant contributions to research on four major tokamaks: Alcator C-Mod, ASDEX Upgrade, DIII-D, and National Spherical Torus Experiment Upgrade. At MIT's Plasma Science and Fusion Center, she previously served as assistant division head for magnetic fusion energy collaborations and ran the Gyrokinetic Simulation Working Group and the Alcator C-Mod Transport Group. Her lab maintains close collaboration between experimental work, theoretical modeling, and computational simulation to advance the understanding of plasma turbulence and transport phenomena critical for fusion energy development.

Michael J PekrisView profile

Senior Lecturer

• Environmental Technologies
• Sustainable Aviation
• Fluid Dynamics
• +7 more

Dr. Michael J Pekris is a Senior Lecturer in Mechanical Engineering Sciences at the University of Surrey, serving as Director of Employability within the School of Engineering. He holds a MEng and DPhil from the University of Oxford (2004), with a thesis on liquid crystal heat transfer in turbine blade cooling. His career includes R&D roles at Rolls-Royce, focusing on advanced seal technology and engine efficiency. He is a Chartered Engineer (CEng), Fellow of the IMechE (2023), and Fellow of the Higher Education Academy (FHEA). His research spans sustainable aviation, fluid dynamics, and heat transfer, with a focus on brush seals, hydrogen-fueled aircraft, and transcritical CO2 systems. He leads the Surrey Aerothermal Test Facility (SATF) and collaborates on projects like the Surrey Hydrogen Aircraft Performance Evaluator (SHAPE). He also serves as IMechE Academic Liaison Officer and Royal Academy of Engineering Visiting Professor Scheme Champion. Research interests include environmental technologies for aero-engine seals, sustainable aviation (electric/hydrogen), fluid dynamics, thermodynamic cycles, and rotating machinery. His work addresses energy efficiency, waste heat recovery, and low-emission propulsion systems. Notable contributions include Rolls-Royce Innovation Award (2013) and patents on seal technology. He actively engages in professional development initiatives and industry-academia partnerships. Publications emphasize seal dynamics, CFD modeling, and thermal management. Recent work explores hydrogen-fueled aircraft viability and CO2-based power systems. Collaborations involve Rolls-Royce, ASME Turbo Expo, and Surrey’s interdisciplinary engineering teams. His academic roles include teaching Structural Vibrations and Engineering Management, and advising the Professional Training Year module.

Leonardo ChamorroView profile

Professor

• Aero/Hydrodynamics
• Wind and Hydrokinetic Energy
• Advanced Flow Diagnostics
• +5 more

Leonardo Chamorro is a Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in Earth Science and Environmental Change, Aerospace Engineering, and Civil and Environmental Engineering. His research focuses on fluid dynamics, renewable energy systems, and turbulence modeling. He holds a Ph.D. in Civil Engineering from the University of Minnesota (2010) and has held academic positions at UIUC since 2013, advancing to Full Professor in 2024. Chamorro's work spans experimental and theoretical investigations of wind and hydrokinetic energy, geophysical flows, and particle dynamics. His research group, the Renewable Energy & Turbulent Environment Group (RE-TE-G), explores topics like tidal flow multifractality, vortex dynamics, and bio-inspired robotics. Key achievements include Nature and Lab on a Chip cover articles, and contributions to turbulence modeling for tidal energy systems. He has received awards such as the Best Paper Award in Energies (2018) and recognition for pandemic-related research (2021). His editorial roles include associate editorships at journals like Journal of Renewable and Sustainable Energy and Frontiers in Energy Research . Chamorro has supervised numerous graduate students and postdocs, contributing to over 150 peer-reviewed publications since 2009.

Stefan LutherView profile

Professor

• Biomedical Engineering
• Cardiac Physiology
• Nonlinear Dynamics
• +3 more

Prof. Dr. Stefan Luther is a Max Planck Research Group leader (W2, tenured since 2013) at the Max Planck Institute for Dynamics and Self-Organization, Göttingen, and an Honorarprofessor at the Faculty of Physics, University of Göttingen. He holds adjunct roles as Adjunct Associate Professor at Cornell University (2009–2012) and Northeastern University (2016–2018), and serves as DZHK-Professor at the Institute of Pharmacology and Toxicology, University Medical Center Göttingen. His research focuses on nonlinear spatiotemporal dynamics in excitable biological media, particularly cardiac arrhythmias. He pioneered 4D imaging of heart function and developed algorithms for optogenetic and electrical control of arrhythmias. Translational efforts span basic research to preclinical and clinical studies. Education includes a Diplom in Physics (1997) and PhD (2000) from Georg-August-University, Göttingen. Postdoctoral training followed at the University of Twente (2001–2004) and Cornell University’s LASSP (2004–2006). His lab, the Biomedical Physics group, explores electromechanical coupling in cardiac systems and develops novel therapeutic approaches. Collaborations include work on computational modeling, uncertainty quantification in dynamical systems, and fluid dynamics of multiphase flows.