Kaan Inal is a Professor at the Department of Mechanical and Mechatronics Engineering, University of Waterloo. He holds roles in faculty administration and is a full-time academic staff member. His research focuses on computational mechanics, materials science, and the integration of machine learning with engineering simulations. His work addresses challenges in crystal plasticity modeling, metallurgical processes, and microstructure characterization. Key areas of research include the development of advanced finite element methods for polycrystalline materials, thermal-mechanical modeling of alloys, and AI-driven approaches for material characterization and process optimization. He leads the Computational Mechanics Research Group, exploring innovations in composite materials, fatigue analysis, and additive manufacturing. His publications (2022–2025) highlight trends in data-driven modeling, phase-field simulations, and machine learning applications for predicting material behavior. These studies emphasize texture evolution, dynamic recrystallization, and microstructural analysis in metals and composites. No specific scientific awards are listed, but his contributions have advanced numerical methods in materials engineering. Advising and grant activities are integral to his role, though specific student names or grant details are not provided in the text. His work bridges theoretical mechanics with practical industrial applications, contributing to lightweight materials for automotive and aerospace sectors.
Steven Psaltis is a Senior Research Fellow at Queensland University of Technology specializing in mathematical modeling of multiscale, multiphase systems with applications in industrial processes and porous media flow. His research develops computational methods for aluminum electrolysis, wood product characterization, and resource estimation in energy fields. With expertise in C/C++ and OpenGL, he creates virtual reconstruction techniques for material analysis. Research applications include: Aluminum hydroxide precipitation dynamics Coal seam gas production modeling Timber billet reconstruction from rotary peeling Agrochemical transport in plant systems He teaches multivariable calculus, differential equations, and engineering mathematics while developing GPU-accelerated computational methods.
Maria Kazakova is a researcher in Fluid Mechanics and Wave Modeling , affiliated with INSA Rouen and collaborating with institutions including ENSTA ParisTech , University of Toulouse , and Novosibirsk State University .
Franck Boyer is a University Professor at the Faculty of Science and Engineering, University of Toulouse, affiliated with the Toulouse Institute of Mathematics (UMR 5219) since September 2015. He serves as Deputy Director of the Toulouse Institute of Mathematics since January 2020 and is a member of the Board of the Department of Mathematics at Paul Sabatier University. His educational background includes being a former student of ENS Cachan (1995-1999), completing his thesis in 2001 at the University of Bordeaux 1, and obtaining his HDR in 2006 from the University of Provence. His academic career progressed from CR CNRS in Marseille (2001-2007) to Professor at Aix-Marseille University (2007-2015) before joining University of Toulouse. Professor Boyer's research focuses on mathematical analysis of partial differential equations with applications in fluid mechanics. His work spans modeling and simulation of multiphase flows, fractured porous media, nonlinear PDEs from fluid mechanics, and development of finite volume numerical methods. He has made significant contributions to the analysis of Cahn-Hilliard/Navier-Stokes models, non-homogeneous boundary conditions, and PDE control theory including exact controllability properties for parabolic problems. He has supervised numerous doctoral students whose research has led to academic and research positions across France, working on topics including viscoelastic fluids, multiphase flows, numerical schemes, and boundary controllability of coupled parabolic systems. Blaise Pascal Prize from the Academy of Sciences (2016) Junior Member of the University Institute of France (2016-2021) Professor Boyer serves on the editorial boards of ESAIM Mathematical Modeling and Numerical Analysis and ESAIM Proceedings and Surveys. He has been actively involved in academic administration, previously serving in leadership roles for mathematics master's programs and aggregation preparation at both Aix-Marseille and Toulouse universities. His GitHub activity shows ongoing research contributions, particularly in finite volume methods as evidenced by his FVCA8 Benchmark repository.
Giove De Cosmo is a Post-Doctoral Research Assistant in Numerical Modelling within the Department of Engineering Science at the University of Oxford. He works in the Computational Fluid Dynamics group under Prof Luca di Mare, focusing on gas turbine simulations and ice accretion in aircraft engines. His roles include teaching assistantship with lab demonstrations and tutoring. MEng(Hons) in Mechanical Engineering (2018) MRes in Fluid-Dynamics (2019) PhD in Computational Fluid Dynamics (2023) His research spans computational fluid dynamics, gas turbines, and particle-laden flows. Recent work includes numerical modelling of ice accretion in collaboration with Rolls-Royce plc. Projects involve turbine rim-seal LES, URANS analysis, and film cooling dynamics. Article trends highlight expertise in CFD solver development Turbine flow structures Non-reflecting boundary conditions Ice accretion simulation Proper Orthogonal Decomposition Flow field accuracy He is involved in the Oxford Thermofluids Institute and contributes to teaching activities in the department.
Professor Jean-Luc Guermond holds the Mobil Chair in Computational Science at Texas A&M University. His research focuses on numerical methods for partial differential equations (PDEs), computational fluid dynamics, and finite element approximation. He has made significant contributions to invariant-domain preserving schemes, high-order time integration methods, and the development of robust numerical techniques for hyperbolic systems and conservation laws. His work bridges theoretical advancements with practical applications in fluid dynamics, electromagnetics, and magnetohydrodynamics. Key research areas include the analysis of finite element methods, discontinuous Galerkin discretizations, and the design of algorithms that preserve physical invariants such as mass, momentum, and energy. Guermond’s publications often address challenges in simulating complex phenomena like vortex reconnection, turbulent swirling flows, and dynamo mechanisms in geophysical contexts. He has also contributed to the development of preconditioning strategies for Navier-Stokes equations and high-order Runge-Kutta schemes. His work emphasizes both mathematical rigor and computational efficiency, with applications ranging from engineering simulations to environmental modeling. Despite extensive contributions to the field, no specific awards are mentioned in the provided texts. Collaborative efforts with experimental teams highlight his interdisciplinary approach to solving real-world fluid dynamics problems.
Philip Mocz is a computational research scientist at the Flatiron Institute's Center for Computational Astrophysics, part of the Simons Foundation. His work focuses on developing scalable, high-performance multiphysics simulation software with a growing emphasis on integrating modern AI techniques and automatic differentiability. Previously, he was a Computational Physicist at Lawrence Livermore National Laboratory, where he specialized in designing high-order Arbitrary Lagrangian-Eulerian (ALE) finite element methods for magnetohydrodynamics (MHD) simulations on heterogeneous computing architectures as part of the Multiphysics on Advanced Platforms Project (MAPP). Dr. Mocz earned his Ph.D. in Astrophysics from Harvard University in 2017 under Lars Hernquist, where he developed a finite-volume moving mesh magnetohydrodynamics algorithm applied to study structure formation and magnetic field amplification, integrating his solvers into the Arepo simulation code. Prior to his doctorate, he received an A.B. in Mathematics and Astrophysics from Harvard in 2012. His research spans multiphysics simulations, cosmology, galaxy formation, black hole physics, turbulence, numerical methods, and AI integration in computational astrophysics. A significant focus involves cosmological simulations of alternative dark matter candidates, particularly fuzzy dark matter. His work bridges theoretical astrophysics with high-performance computing, developing novel simulation frameworks that incorporate modern computational techniques. Dr. Mocz's publication record reveals a strong trajectory in computational methods for astrophysical problems, with increasing integration of AI techniques in recent years. His research demonstrates expertise across multiple domains including quantum mechanics applications to cosmology, turbulence modeling, and the development of advanced simulation algorithms. The interdisciplinary nature of his work connects astrophysics with computer science and applied mathematics. He maintains an active educational presence through his blog featuring approximately 100-line Python tutorials on scientific computing at the undergraduate level, published on Medium and followed on Twitter. His educational materials cover fundamental computational methods including finite difference approaches, Riemann solvers, and differentiable simulations using JAX. Dr. Mocz has served as a Teaching Fellow for Harvard courses including Astronomy 151 (Astronomical Fluid Dynamics), Applied Computation 274 (Computational Fluid Dynamics), and Applied Mathematics 205 (Advanced Scientific Computing). His outreach activities include mentoring for the LLNL DSTI Research Program, NASA Cosmic Origins Transitional Leadership Team, and Princeton Astrophysics Undergraduate Summer Research Program. Originally from Hawaii, he enjoys outdoor activities when not working. His professional presence includes active GitHub repositories (pmocz), a personal website (pmocz.github.io), and engagement on Bluesky (@philipmocz.bsky.social), where he shares insights about computational physics and scientific software development.
Emanuel Katz is a Professor at Boston University, specializing in theoretical physics with a focus on particle physics and quantum field theory. His research addresses electroweak symmetry breaking, flavor symmetry puzzles, and dark matter detection mechanisms. He holds a B.S. and PhD in Physics & Theoretical Mathematics from MIT. Research interests include: Electroweak symmetry breaking mechanisms Flavor physics and quark-lepton family structure Conformal field theories and critical phenomena Dark matter effective theories Publications span high-impact journals like JHEP and Physical Review B, covering topics from quantum criticality to holographic methods. Recent work includes dynamical trapping near quantum phase transitions and analytic solutions in 2d QCD. Awards: NSF CAREER Award, Sloan Research Fellowship Laboratory affiliation: Office located in PRB Building, Room 571.
Olexei I. Motrunich is a Professor of Theoretical Physics at the California Institute of Technology (Caltech). His research focuses on quantum many-body systems, with a particular emphasis on integrability, quantum scars, and topological phases. He explores phenomena such as exact eigenstates in non-integrable models, symmetry-breaking dynamics, and the interplay between disorder and quantum order. Research Interests: Quantum Many-Body Scars and Exact Eigenstates Integrability Breaking and Perturbation Theory Topological Superconductors and Edge States Condensed Matter Theory and Phase Transitions Algebraic Methods in Quantum Dynamics Recent work highlights the robustness of bound states in quantum systems and the hydrodynamic implications of local symmetries. No scientific awards or grants are explicitly listed in the provided text. Advising information is unavailable. Labs/Teams: Not specified in the provided text. Office located at 165C West Bridge (33W), Caltech.
Dr. Chi Wu serves as a Lecturer in Mechanical Engineering at the University of Newcastle's School of Engineering. With a PhD from the University of Sydney (2022) and postdoctoral experience there (2023-2024), he has established himself as a rising researcher in computational mechanics and advanced manufacturing. His work bridges engineering principles with biomedical applications, particularly in the development of machine learning-driven approaches for material and structural optimization. Education: Doctor of Philosophy, University of Sydney Dr. Wu's research spans computational mechanics, topology optimization, machine learning, biomechanics, and advanced manufacturing, with particular emphasis on developing novel machine learning-based approaches for design optimization of advanced materials and structures. His work focuses on creating functionally graded tissue scaffolds, optimizing composite structures, and developing phase field models for fracture analysis. His research experience spans academia, industry, and clinical applications, demonstrating strong interdisciplinary connections. Analysis of Dr. Wu's publication record reveals a strong focus on integrating machine learning with additive manufacturing, particularly for biomedical applications. His work shows increasing sophistication in combining computational mechanics with experimental validation, with recent publications emphasizing time-dependent optimization and multi-scale modeling approaches. The trend indicates growing recognition of his work in both computational mechanics and biomedical engineering communities. Scientific Awards: Acta Journal Award (2023) Inaugural Grant Steven Award for Early Career Researchers (2023) Best Paper Award at the 12th International Conference on Structural Integrity and Failure (2021) Wiley Top Cited Article Award for 2020-2021 Best Paper Award at the 4th Australasian Conference on Computational Mechanics (2019) Dr. Wu actively recruits PhD students for research in mechanical, materials, and manufacturing engineering, with particular interest in candidates with computational mechanics and optimization backgrounds. He co-supervises students with Prof. Qing Li (ARC Future Fellow, Highly Cited Researcher) at the University of Sydney and Dr. Jianguang Fang (ARC Future Fellow) at the University of Technology Sydney. The University of Newcastle offers various scholarships, with additional support available for candidates from mainland China applying for the CSC scholarship. Dr. Wu maintains extensive collaborative networks across multiple institutions including Harvard University, Max Planck Institute, University of Exeter, Tohoku University, and several Australian universities and medical institutions including Chris O'Brien Lifehouse cancer hospital and industry partners like Cochlear Australia and Zimmer Biomet Australia.
Alina Chertock serves as the Head of the Department of Mathematics at North Carolina State University (NCSU), where she leads academic and research initiatives in computational mathematics. Her work focuses on developing advanced numerical methods for hyperbolic conservation laws, fluid dynamics, and models involving uncertainty quantification. Chertock’s research integrates finite-volume, particle, and hybrid methods to address complex phenomena such as chemotaxis, magnetohydrodynamics, and shallow water systems. She has contributed to high-resolution schemes for stiff detonation waves and stochastic collocation techniques for nonlinear PDEs with uncertainties. Her research interests span computational fluid dynamics, numerical analysis, and applied mathematics, with applications in geophysical flows, multiphase systems, and biological models. Notable contributions include well-balanced path-conservative schemes for rotating flows and divergence-free flux methods for magnetohydrodynamics. Chertock collaborates actively with institutions on NSF-funded projects, including structure-preserving methods for atmospheric and shallow water models. Her publications emphasize adaptive algorithms, error mitigation in stochastic systems, and the integration of machine learning for wave equation analysis. Chertock’s work bridges theoretical developments with practical applications, addressing challenges in computational efficiency and accuracy across diverse scientific domains.
Lucas Omar Muller is an Associate Professor in the Department of Mathematics at the University of Trento. His expertise spans Biomedical Engineering, Cardiovascular Mathematics, Numerical Analysis, and High-Performance Computing. He holds an office at Via Sommarive, 14 - 38123 Povo, and can be reached via tel. 0461 285222. His teaching responsibilities include courses such as Analisi numerica I/II , Biomedical Applications of Mathematics , and Computational Haemodynamics . He also teaches Fisiologia applicata al letto del paziente and Strumenti informatici per la matematica . Research interests focus on mathematical modeling in biomedical contexts, numerical methods for PDEs, and computational techniques for parallel systems. While no specific publications are listed here, his work likely intersects with cardiovascular modeling, neural network applications, and high-performance computing frameworks. No scientific awards, grants, or advised students are explicitly mentioned in the provided data.
Alexandros Gezerlis is a Professor of Physics at the University of Guelph, where he leads a research group focused on quantum many-body theory, nuclear physics, and neutron stars. Before joining Guelph in 2013, he held positions in Germany (Technische Universitaet Darmstadt) and the U.S. (University of Washington, Los Alamos National Laboratory). His research bridges nuclear theory, ultracold atomic gases, and astrophysics, using computational methods like Quantum Monte Carlo to study systems from neutron stars to terrestrial nuclei. He has received the University of Guelph’s Research Excellence Award (2017), Ontario’s Early Researcher Award (2017), and TU Darmstadt’s Inaugural Herzberg Fellowship (2013). His recent publications highlight collaborations with graduate students on topics such as chiral nuclear forces, neutron matter properties, and machine learning applications in nuclear physics. He emphasizes mentoring students, with a group of 5–6 graduate and 1–2 undergraduate researchers at any time. His work is supported by grants from NSERC, CFI, and international collaborations with institutions like the U.S. Department of Energy.
Dr. Ksenia Fedosova is a mathematician affiliated with the Mathematical Institute at the University of Münster, Department of Mathematics and Computer Science. Previously, she held roles at the Albert-Ludwigs-University of Freiburg, including teaching and research. Her work focuses on global analysis, spectral geometry, number theory, and mathematical physics, with applications to hyperbolic surfaces, scattering theory, and automorphic forms. She has published extensively on topics such as resonances, zeta functions, and analytic torsion. Her research often involves interdisciplinary methods from harmonic analysis, ergodic theory, and differential geometry. Affiliations: University of Münster (current), University of Freiburg (past) Roles: Lecturer, Researcher, Course Organizer Key Areas: Spectral Geometry, Analytic Number Theory, Hyperbolic Dynamics Her teaching includes advanced courses such as Analytic Number Theory, Fourier Series, and Elementary Geometry. She has organized academic events like the 'Hypoelliptic Laplacian and Applications' lecture series in 2019. Her research outputs emphasize theoretical contributions to zeta functions, scattering theory, and geometric analysis.
Prof. Dr. Roman Sauer is a Professor of Mathematics at Karlsruhe Institute of Technology (KIT), leading the Topology and Geometric Group Theory Group within the Institute of Algebra and Geometry. His research focuses on geometric topology, geometric group theory, and L²-invariants, with particular emphasis on manifolds, cohomology, and group actions. He has held roles such as Head of the Topology Group and contributed to foundational work on simplicial volume, bounded cohomology, and Kazhdan properties. Key research areas include the interplay between geometry and topology in manifolds, the study of arithmetic groups through profinite invariants, and applications of measure-theoretic methods to group theory. His work often bridges algebraic topology with geometric analysis, addressing questions about rigidity, stability, and quantitative invariants. Publications highlight contributions to L²-Betti numbers, geometric group actions, and the interplay between group properties and topological structures. Notable collaborations involve Uri Bader, Clara Löh, and others in advancing the field of geometric topology and related cohomological theories.
