Find Academic Supervisors

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.

John EvansView profile

Associate Professor

• Computational Mechanics
• Fluid Dynamics
• Fluid-Structure Interaction
• +3 more

John Evans is an Associate Professor and Jack Rominger Faculty Fellow in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, affiliated with the Applied Mathematics program. He serves as Associate Chair for Undergraduate Curriculum and is part of the Aerospace Mechanics Research Center (AMREC). His research focuses on computational mechanics, particularly fluid dynamics, fluid-structure interaction, and turbulence modeling using high-order and structure-preserving methods. Evans holds a PhD (2011) and MS (2008) in Computational and Applied Mathematics from the University of Texas at Austin, and dual BS/MS degrees in Mathematics and Applied Mathematics from Rensselaer Polytechnic Institute (2006). Before joining CU Boulder, he was a postdoctoral fellow at the Institute for Computational Engineering and Sciences (ICES). His research interests include isogeometric analysis, immersed methods, and data-driven turbulence modeling. Notable contributions include development of divergence-conforming discretizations for incompressible flows, stabilized collocation methods, and invariant subgrid stress models. He leads the AMREC lab and collaborates on plasma-fueled propulsion systems and geometrically sensitive simulations. Key Awards: 2021: Rocky Mountain AIAA Educator of the Year 2021: Gallagher Young Investigator Medal 2019-2021: Clarivate Highly Cited Researcher Professional Activities: Editor of Engineering Computations, Senior AIAA Member, Simons Visiting Professor (2019) Evans' work bridges advanced numerical methods with real-world engineering challenges. His lab develops open-source tools like XIGA for multi-material problems and focuses on immersive simulation environments. Current projects explore turbulence closure models, plasma propulsion, and topology optimization with B-spline-based approaches.

• Applied Mathematics
• Mathematical Physics
• Neurosciences
• +4 more

Professor Paul C. Bressloff holds the Chair in Applied Mathematics and Stochastic Processes at Imperial College London's Department of Mathematics within the Faculty of Natural Sciences. His research focuses on stochastic and non-equilibrium processes, particularly in molecular and cell biology, utilizing tools from probability theory, statistical physics, and dynamical systems. He authored a seminal textbook Stochastic Processes in Cell Biology (Springer), with a 2nd edition published in 2022. Previously, he led the graduate program in mathematical biology at the University of Utah from 2001 to 2023. Research interests include stochastic multi-particle systems, active particles, phase separation, and diffusion across semi-permeable interfaces. His work spans applications in neural field theory, cytoneme-mediated morphogenesis, and protein trafficking. He is affiliated with the Biomathematics Group and Mathematical Physics Group at Imperial. Recent articles explore stochastic resetting in search processes, narrow-capture problems, and hybrid models of switching diffusions. His advising includes over 20 graduate students, many now faculty in mathematical biology. His contributions bridge applied mathematics and biological systems, emphasizing interdisciplinary approaches to complex stochastic phenomena.

• Numerical analysis
• Partial differential equations
• Fluid mechanics
• +5 more

Dr. Jean-Christophe Nave is an Associate Professor in the Department of Mathematics and Statistics at McGill University. He holds a PhD from the University of California, Santa Barbara (2004), under advisors Xu-Dong Liu and Sanjoy Banerjee. Prior to McGill, he served as a Lecturer and Instructor at MIT's Mathematics Department (2005-2010). His research focuses on numerical analysis, partial differential equations, fluid mechanics, and computational methods for interface problems. He has led research groups involving postdocs, PhD, and undergraduate students, collaborating on projects like the Correction Function Method for PDEs and the Characteristic Mapping Method for advection problems. Education: Ph.D. in Applied Mathematics from UCSB (2004). Affiliations include the Institut des Sciences Mathematiques Steering Committee, Centre de Recherches Mathematiques Applied Math Lab, and CNRS-UMI. Active in teaching courses like Numerical Analysis I/II and Non-Linear Dynamics at McGill, with sabbatical periods noted in recent years. Research interests span numerical methods for PDEs, fluid-structure interaction, and multi-phase flows. His work integrates computational geometry and invariant numerical techniques, addressing challenges in complex fluid dynamics and interface-driven phenomena. Over 40 peer-reviewed publications and continuous contributions to the field of computational applied mathematics. Scientific advising includes over 20 graduate and undergraduate students, with notable alumni now in academia and industry. Collaborations include projects on volcano dynamics, fiber drawing instabilities, and concentrated solar power systems. His methods have advanced numerical simulations for engineering and physical systems involving discontinuous coefficients and sharp interfaces.

K.S. BabuView profile

Professor

• Theoretical Physics
• Particle Physics
• Neutrino Physics
• +4 more

K.S. Babu, Ph.D. , is a Regents Professor in the Department of Physics at Oklahoma State University . His research focuses on theoretical physics beyond the Standard Model, particularly in neutrino mass models, grand unification, and baryon/lepton number violation. Email: kaladi.babu@okstate.edu Contact: 405-744-5810 | 232 Physical Sciences, OSU Dr. Babu's work spans several key areas: Grand Unified Theories (GUTs): Studies of SO(10), SU(5), and E6 unification frameworks. Neutrino Physics: Development of models like the Zee-Babu mechanism for neutrino masses and research on oscillations. Dark Matter & Cosmology: Proposals for dark matter candidates and connections to inflation and baryogenesis. CP Violation & Leptogenesis: Mechanisms for generating matter-antimatter asymmetry. His recent publications highlight advancements in: Spontaneous CP violation in SO(10) (2025) Left-right symmetric models for leptogenesis (2025) Ultraviolet-completed two-loop neutrino mass models (2025) Probing baryon number violation at IceCube and LHC (2024) Accidental Peccei-Quinn symmetry for axion models (2024) Dr. Babu actively collaborates on international initiatives such as the Center for Theoretical Underground Physics (CETUP) and contributed to the Snowmass 2013 Community Planning Study. His lab has mentored numerous graduate and postdoctoral researchers, including Kirtiman Ghosh, Sudip Jana, and Shaikh Saad.

Burkhard MaessView profile

Research Professor

• Neuroscience
• Auditory Processing
• Signal Analysis
• +3 more

Dr. Burkhard Maess is a Research Professor and Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences, leading the Methods and Development Group Brain Networks. His research focuses on auditory and language processing, signal analysis, and dynamic modeling of neuronal networks. He holds a Diploma in Physics (University of Leipzig, 1987) and a PhD in Physics (University of Leipzig, 1990). His career includes postdoctoral positions at the Academy of Sciences of the GDR and the Free University of Berlin before joining the MPI in 1995. Since 2000, he has led research groups on MEG/EEG signal analysis and cortical network dynamics. His work integrates advanced neuroimaging techniques like MEG and EEG to study sensory processing, neural network dynamics, and the effects of aging on auditory attention. Key contributions include developing high-resolution BEM-FMM methods for source localization and analyzing cross-frequency coupling in neuroscience data. His group also explores spinal cord electrophysiology and the neural underpinnings of perceptual decision-making. Dr. Maess’ research spans cognitive neuroscience, biomedical engineering, and computational modeling, with a focus on bridging empirical findings with theoretical frameworks in neuroscience.

Marco PaggiView profile

Professor

• Fracture mechanics
• Contact mechanics
• Computational methods for nonlinear partial differential equations
• +15 more

Marco Paggi is a Full Professor of Structural Mechanics at the IMT School for Advanced Studies Lucca, Italy, since 2017. He previously held academic roles at Politecnico di Torino (Assistant Professor, 2007-2013) and has been an Alexander von Humboldt Fellow at Leibniz University Hannover. His research focuses on fracture mechanics, contact mechanics, and computational methods applied to renewable energy systems, composite materials, and multi-scale modeling. Key Themes: Fracture propagation, contact interfaces, phase field modeling, photovoltaic durability, and material heterogeneity. Awards: Stanford Top 2% Scientists (2020-2024) Research.com Top Scientists (2022-2024) European Structural Integrity Society Young Scientist Award (2010) Publications: His work spans tribology, computational fracture mechanics, and material degradation, with recent emphasis on phase field modeling for quasi-brittle materials and photovoltaic systems. He has pioneered methods for multi-scale and multi-physics analysis of structural systems. Mentorship: Supervised 17 PhD graduates and 14 postdocs, including award-winning researchers like Pietro Lenarda and Zeng Liu.

Karim SabraView profile

Professor

• Acoustics
• Structural Health Monitoring
• Biomechanics
• +7 more

Dr. Karim Sabra is a Professor at the George W. Woodruff School of Mechanical Engineering , Georgia Institute of Technology, specializing in Acoustics and Dynamics . He holds a Ph.D. from the University of Michigan (2003) and joined Georgia Tech in 2007 as an Assistant Professor. His research integrates theoretical and experimental approaches to study wave propagation in diverse fields including structural health monitoring, biomechanics, and ocean acoustics. Key areas of focus include passive imaging techniques using ambient noise and diffuse wave fields, with applications in non-invasive monitoring of mechanical systems and seismoacoustic environments. Education: Ph.D., University of Michigan, 2003 M.S., University of Michigan, 2000 M.Sc., École Nationale Supérieure de Techniques Avancées (France), 2000 Research Interests: Dr. Sabra’s work spans acoustics, structural health monitoring, biomechanical systems evaluation, underwater acoustics, and geophysics . Recent projects include developing passive elastography techniques for soft tissues using physiological vibrations and exploring ambient noise-based tomography for ocean environments. His interdisciplinary approach bridges multi-scale engineering challenges with multi-wave tools (acoustical, electrical, optical). Publications: His work focuses on advanced acoustic technologies, including underwater communication systems, passive acoustic identification tags, and ray-based tomography methods. Themes include seamount effects on sound propagation, machine learning for acoustic modeling, and environmental sensing using shipping noise. Awards: R. Bruce Lindsay Award (2011) Fellow of the Acoustical Society of America (2007) Institute of Acoustics A.B. Wood Medal (2009) Advising & Grants: Dr. Sabra mentors graduate students in acoustics and wave phenomena, emphasizing interdisciplinary collaboration. His research is supported by grants focused on underwater acoustics, environmental sensing, and biomedical applications. Labs/Teams: His research group develops novel sensors and algorithms for oceanographic and biomedical applications, collaborating with industry and academic partners.

Sean WelleckView profile

Assistant Professor

• Large Language Models
• Mathematical Reasoning
• Code Generation
• +4 more

Sean Welleck is an Assistant Professor at Carnegie Mellon University's School of Computer Science, specifically within the Language Technologies Institute (LTI). He leads the L3 Lab and serves as an advisor for the AI for Math Fund. His academic journey includes a PhD from New York University under Kyunghyun Cho and postdoctoral positions at the Allen Institute for Artificial Intelligence and the University of Washington with Yejin Choi. Dr. Welleck's educational background shows a strong foundation in computer science. He earned his PhD in Computer Science from New York University, where he worked under the mentorship of Kyunghyun Cho and Zheng Zhang. Prior to this, he completed his MSE and BSE in Computer Science from the University of Pennsylvania, demonstrating a long-standing commitment to the field. Dr. Welleck's research focuses on bridging informal and formal reasoning with AI, with particular emphasis on developing learning, inference, and evaluation algorithms for large language models. His work spans multiple cutting-edge areas including mathematical reasoning , code generation , inference algorithms , and AI reasoning agents . A significant portion of his recent work involves combining AI with formal methods for mathematics, where he has developed frameworks like Llemma (an open-source language model for mathematical reasoning) and meta-generation (for inference-time algorithms). His research is characterized by a strong theoretical foundation coupled with practical applications that push the boundaries of what AI systems can achieve in formal reasoning domains. Analysis of Dr. Welleck's recent publications reveals a clear research trajectory focused on enhancing language models' capabilities in formal reasoning and mathematical problem-solving. His work demonstrates an evolution from foundational research in neural text generation to increasingly sophisticated approaches that integrate formal methods with deep learning. Key trends include the development of inference-time algorithms that improve model performance without additional training, frameworks for mathematical reasoning that connect informal and formal proofs, and novel evaluation methodologies for language models. His publications consistently appear in top-tier conferences including NeurIPS, ICLR, ICML, and ACL, reflecting the high impact of his contributions to the field. Dr. Welleck's scientific achievements have been recognized with several prestigious awards: NAACL 2025 Best Paper Award ICLR 2025 Oral Presentation (Top 2%) ICLR 2025 Spotlight Presentation (Top 5%) NeurIPS 2021 Outstanding Paper Award (Top 0.1%) for MAUVE NVIDIA AI Labs Pioneering Research Award (2017 and 2018) As an educator and mentor, Dr. Welleck actively guides the next generation of AI researchers. He currently advises multiple PhD students including Pranjal Aggarwal, Weihua Du, Andre He, and Seungone Kim (some co-advised with other faculty), along with MS students Riyaz Ahuja, Jiewen Hu, Qinyue Tan, and Thomas Zhu, and undergraduate Tate Rowney. At CMU, he teaches advanced courses such as Neural Code Generation and Advanced NLP, and has previously taught at New York University and the University of Washington. His commitment to education extends to creating resources like the Thesis Review Podcast and developing tutorials on neural theorem proving that have been presented at major conferences. Dr. Welleck leads the L3 Lab at CMU, which focuses on the intersection of language, learning, and logic. The lab brings together students and researchers to tackle challenging problems in AI reasoning, with particular emphasis on mathematical reasoning and code generation. Recent initiatives include the development of Llemma, an open-source language model specialized for mathematical reasoning, and work on inference-time algorithms that enable language models to improve their performance through additional computation during inference rather than through additional training.

• Precision Machine Design
• Medical Device Design
• Renewable Energy Systems
• +5 more

Professor Alexander Slocum holds the Walter M. May (1939) and A. Hazel May Chair in Emerging Technologies at MIT's Department of Mechanical Engineering within the School of Engineering. A distinguished educator and researcher, Slocum has made significant contributions across precision machine design, medical device innovation, and renewable energy systems. His research interests span precision machine design for medical devices and energy industry applications, with particular focus on offshore renewable energy storage systems and kinematic couplings. Slocum's work bridges theoretical mechanical engineering principles with practical applications that address real-world challenges in healthcare and sustainable energy. His recent publications demonstrate a strong emphasis on bio-inspired engineering, underwater energy storage systems, and medical device innovation. The articles reveal a consistent pattern of applying fundamental mechanical engineering principles to solve problems in healthcare delivery and renewable energy storage, often with a focus on practical implementation in resource-constrained environments. NSF Presidential Young Investigator (1987) MacVicar Faculty Fellow (1999) Massachusetts Professor of the Year Award (2000) Multiple R&D 100 Awards (1994-2010) ASME Leonardo da Vinci Award (2004) ASME Machine Design Award (2008) ASME Ruth and Joel Spira Outstanding Design Educator Award (2018) National Academy of Inventors Fellow (2021) Slocum actively mentors students through MIT's Experimental Study Group (which he directs) and his renowned 2.75/2.750 Precision Machine Design courses. His educational approach emphasizes hands-on learning and real-world problem solving, particularly through medical device design projects developed in collaboration with Boston-area clinicians. His research has been supported by significant grants from the NSF, Department of Energy, and military research agencies. His PERG (Precision Engineering Research Group) lab fosters interdisciplinary collaboration, bringing together mechanical engineers, materials scientists, and medical professionals to develop innovative solutions for healthcare and energy challenges. The lab is particularly known for its work on kinematic couplings, hydrostatic bearings, and bio-inspired engineering solutions.

Olesya ZhupanskaView profile

Professor

• Mechanics of Composites
• Structural Composites in Extreme Environments
• Multi-Field Effects (Mechanical, Thermal, Electromagnetic)
• +12 more

Dr. Olesya Zhupanska is a Professor in the Department of Aerospace and Mechanical Engineering at the University of Arizona, where she holds a faculty position and is a member of the Graduate Faculty. Her research focuses on the mechanics of composite materials, especially under extreme multi-field conditions involving mechanical, thermal, and electromagnetic loads. Education: PhD in Mechanics of Solids and Applied Mathematics, Taras Shevchenko National University of Kyiv, Ukraine, 2000 BS/MS in Mechanics and Applied Mathematics (with Highest Honors), Taras Shevchenko National University of Kyiv, Ukraine, 1996 Her research interests span mechanics of composites, impact and damage, micromechanics, multi-field effects, and structural health monitoring, with applications in aerospace, wind energy, and smart materials. She has made significant contributions to understanding lightning strike damage, electrified composites, and thermostructural response of advanced materials. Her work integrates experimental, analytical, and computational methods to solve complex engineering problems. The 15 most recent publications highlight a strong trend in composite materials under electrical and thermal loads, with a focus on damage mechanisms, contact mechanics, and predictive modeling. Her research bridges mechanics, materials science, and electromagnetics, with increasing integration of machine learning for damage detection. Applications span aerospace structures, hypersonic vehicles, and wind turbine blades. Scientific Awards and Honors: DARPA Young Faculty Award (2011) Elsevier Young Composites Researcher Award (2008) ASME/Boeing Structures & Materials Award (2007) Multiple ASC Best Paper Awards National Research Council Senior Research Associateship Award (2022, 2015) Air Force Summer Faculty Fellowships (multiple years) Woman of Impact Award, University of Arizona (2022) Fellow, ASME Associate Fellow, AIAA ASME Dedicated Service Award (2023) Dr. Zhupanska has advised numerous graduate students, many of whom have won prestigious awards such as the DoD SMART Scholarship and NASA Fellowships. Her research has been funded by DARPA, NSF, NASA, AFOSR, AFRL, and industry partners. She has served on technical review boards including ARL and actively promotes engineering education and inclusion through NSF-funded initiatives. She holds leadership roles in professional societies, currently serving as President of the American Society for Composites (ASC) and as a member of the ASME IMECE Steering Committee Senate. She also serves as a Topic Editor for Composites and Advanced Materials and on the editorial board of Applied Composite Materials.

Christian EngwerView profile

Professor

• Partial Differential Equations
• Numerical Analysis
• Finite Element Methods
• +7 more

Christian Engwer is a full Professor at the University of Muenster in the Institute for Applied Mathematics, specializing in Analysis and Numerics. He leads the Engwer Group focused on Applications of Partial Differential Equations and is actively involved in the Cells in Motion initiative as a supervisor in the CiM-IMPRS Graduate Programme. His research centers on developing numerical methods for partial differential equations, particularly addressing challenges in complex geometries and multi-physics applications. He specializes in Unfitted Discontinuous Galerkin methods, which allow simulations on complex geometries without requiring domain-fitted meshes. His work spans porous media modeling, biological systems, and bioelectromagnetism applications, with significant contributions to EEG/MEG forward modeling in neuroscience. Analysis of his recent publications reveals a strong focus on model order reduction techniques, stabilized numerical schemes for cut-cell meshes, and applications in bioelectromagnetism. His work demonstrates a consistent trajectory toward developing robust, efficient numerical methods applicable to real-world problems in medical imaging and biological modeling, with increasing emphasis on high-performance computing implementations. Professor Engwer actively supervises doctoral students, with recent completions including Lukas Renelt (2025), Michael Wenske (2021), and Maria Carla Piastra (2019), among others working on topics related to numerical methods and biomedical applications. He leads several major research projects including BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (NIH-funded since 2019), multiple EXC 2044 Cluster of Excellence projects through 2025, and the InterKI interdisciplinary teaching program on machine learning and artificial intelligence. His group develops several important software packages including DUNE (Distributed and Unified Numerics Environment), duneuro (for bioelectromagnetism applications), and TPMC (Topology Preserving Marching Cubes). These tools support research in numerical methods and their applications to complex scientific problems.

• Dark Matter
• Particle Astrophysics
• Cosmology
• +2 more

Pearl Sandick is a Professor in the Department of Physics and Astronomy and Interim Dean in the College of Science at the University of Utah. She has previously served as Associate Chair of the Department of Physics and Astronomy and Associate Dean for Faculty and Research in the College of Science. Her academic journey at the University of Utah began in 2011 as an Assistant Professor, progressing to Associate Professor in 2017, and achieving the rank of Professor in 2022. Her educational background includes: BA in Mathematics from New York University (2003) PhD in Physics from the University of Minnesota (2008) Sandick is a theoretical particle physicist whose research focuses on physics beyond the Standard Model, with particular emphasis on dark matter. Her work spans theoretical modeling, connections to astrophysical observations, and implications for experimental detection. She investigates various dark matter candidates and their potential signatures in current and future experiments, including collider searches, direct detection experiments, and indirect detection through astrophysical observations. Her research also extends to connections between particle physics and cosmology, including early universe phenomena and implications for cosmic structure formation. She has developed computational tools like MADHAT for dark matter analysis and has made significant contributions to understanding how stellar evolution can constrain axion physics. Her scholarly contributions have been recognized with several prestigious awards: University of Utah Early Career Teaching Award (2016) University of Utah Distinguished Mentor Award Linda K. Amos Award for Distinguished Service to Women University of Utah Presidential Scholar Sandick has been actively involved in mentoring graduate students, as evidenced by her teaching of PhD thesis research and Master's research courses. She has secured significant research funding from the National Science Foundation and other agencies to support her work on dark matter, dark energy, and new physics. Her grant portfolio includes projects on theoretical particle physics, connections to astrophysical observations, and studies on graduate education reform following a departmental tragedy. She is an active member of the American Physical Society, having served as Chair of the regional Four Corners Section in 2021-2022, demonstrating her commitment to the broader physics community and leadership in her field.

Zohreh DavoudiView profile

Associate Professor

• Quantum Chromodynamics
• Quantum Computing
• Lattice Gauge Theory
• +5 more

Zohreh Davoudi is an Associate Professor in the Department of Physics at the University of Maryland, College Park. She holds additional roles as a Fellow of the Joint Center for Quantum Information and Computer Science (QuICS) and Associate Director for Education at the NSF Institute for Robust Quantum Simulation. Her research focuses on simulating strongly interacting systems using lattice quantum chromodynamics (LQCD), quantum simulation, and quantum computing. She earned her B.Sc. and M.Sc. from Sharif University of Technology in Iran, followed by a Ph.D. in Theoretical Physics from the University of Washington (2014), and served as a postdoctoral researcher at MIT's Center for Theoretical Physics before joining UMD in 2017. Her research interests include developing computational frameworks to study nuclear and particle physics phenomena, such as neutrino interactions, dark matter scattering, and neutron star dynamics. She has pioneered efforts to leverage quantum computing to address the 'sign problem' in fermionic systems and simulate real-time dynamics of early universe matter. Notable awards include the 2025 Presidential Early Career Award, 2024 Simons Emmy Noether Fellowship, and 2019 Alfred P. Sloan Fellowship. Her educational contributions include leading training programs in quantum information science and fostering collaborations across institutes like RIKEN (2017–2021) and the NSF Quantum Simulation Institute. She supervises a dynamic research group focused on lattice gauge theory, quantum algorithms, and interdisciplinary applications such as neutrinoless double-beta decay calculations.

Nikolaos NikiforakisView profile

Professor

• High Performance Computing
• Numerical Algorithms
• Computational Fluid Dynamics
• +4 more

Prof Nikolaos Nikiforakis is a Professor at the University of Cambridge, leading the Laboratory for Scientific Computing at the Cavendish Laboratory. He holds roles including Director for Academic Programmes of the Centre for Scientific Computing, Course Director of the MPhil in Scientific Computing, and Deputy Director of the EPSRC Centre for Doctoral Training in Computational Methods for Materials Science. He is also a Fellow and Director of Studies in Mathematics at Selwyn College, Cambridge. He directs The Gianna Angelopoulos Programme for Science Technology and Innovation. He holds a BSc in Aeronautical Engineering from the University of Manchester, followed by an MSc in Aerospace Propulsion and a PhD in 'Evolution of Detonation Waves' from Cranfield Institute of Technology. His postdoctoral research at the University of Cambridge’s Department of Chemistry focused on computational models for stratospheric ozone depletion. He later founded the Laboratory of Computational Dynamics at the Department of Applied Mathematics and Theoretical Physics before joining the Cavendish Laboratory in 2008. His research focuses on numerical algorithms and High Performance Computing for multi-physics simulations involving complex systems of nonlinear PDEs. Applications span detonation dynamics, plasma physics, and materials science, with industry collaborations for software development. His work addresses multi-scale, multi-physics problems previously deemed intractable, with practical applications in aerospace, energy, and environmental fields. He leads academic programmes in scientific computing and supervises doctoral research through the EPSRC CDT. His contributions bridge fundamental science and industrial innovation, emphasizing computational methods for materials and fluid dynamics.