Dr. Leonard Kreutz is a Researcher at the Department of Mathematics , Technical University of Munich (TUM), leading an Emmy Noether Junior Research Group since 2023. He has held postdoctoral positions at Carnegie Mellon University, WWU Münster, and Universität Wien, and was an acting professor at TUM in 2019. Education: PhD (2018) from Gran Sasso Science Institute, Honors Master (2014) and Bachelor (2013) in Mathematics at TUM. Research Interests: His work focuses on the Calculus of Variations , Multiscale Methods , and Discrete-to-Continuum Limits , particularly in modeling crystallization, elastic materials with voids, and topological singularities in spin systems. He explores free-discontinuity problems and geometric rigidity in variable domains. Publications span 2023–2017, emphasizing atomistic models , nonlinear elasticity , and homogenization across mathematics, materials science, and physics. Collaborative projects with leading experts like M. Cicalese and A. Braides dominate his output. Scientific Award: Emmy Noether Junior Research Group Grant (2023–present). Collaborations include institutions such as Carnegie Mellon University, WWU Münster, and the University of Vienna. His research intersects with groups focused on Mathematical Finance , Numerical Analysis , and Quantum Information Theory at TUM.
Derek Groen serves as Reader in Computer Science at Brunel University within the College of Engineering, Design and Physical Sciences. He holds additional appointments as an Emeritus Fellow of the EPSRC-funded 2020 Science Network, Fellow of the Software Sustainability Institute, and Visiting Lecturer at University College London's Centre for Computational Science. His academic background includes an MSc in Grid Computing from the University of Amsterdam (2006) and a PhD in Computational Astrophysics from the University of Amsterdam and Leiden University (2010). Prior to joining Brunel in September 2015 as a Lecturer, he held postdoctoral positions on EU projects MAPPER and CRESTA focused on distributed multiscale computing and exascale high-performance computing. Groen's research centers on multiscale modeling and high-performance computing with applications spanning forced migration simulation, cerebral bloodflow modeling, and materials science. His work addresses critical challenges in performance optimization, distributed computing frameworks, and verification/validation methodologies for complex computational systems. Recent projects demonstrate strong interdisciplinary connections between computational science, social dynamics, and public health crises. Analysis of his 15 most recent publications reveals a clear trajectory toward increasingly sophisticated migration modeling tools (Flee 3, P-Flee), enhanced verification frameworks (VECMAtk, FabSim3), and pandemic response applications. His work consistently bridges computational rigor with real-world humanitarian challenges, particularly in forced displacement scenarios and public health emergencies. EPSRC eCSE funding for domain decomposition research Fellow of Software Sustainability Institute Co-author of first feature article in Advanced Materials (2014) with BBC/Daily Telegraph coverage Emeritus Fellow of 2020 Science Network Groen has secured significant research funding from EPSRC, European Commission, and United Nations for projects including SEAVEA (2021-2024), ITFLOWS (2020-2023), and STAMINA (2020-2022). His supervision history includes summer projects resulting in peer-reviewed publications, with current PhD opportunities focused on real-time environmental monitoring, migration modeling, and urban planning simulations. He actively leads Science Hackathons to foster interdisciplinary collaboration and maintains strong ties with EU research consortia through projects like ComPat and HIDALGO. His laboratory work centers on the FabSim automation toolkit and VECMAtk verification framework, supporting a research team that develops scalable solutions for global challenges. Current efforts focus on integrating machine learning with agent-based simulations to improve migration forecasting and pandemic response capabilities.
Sebastian Reich is a Professor of Numerical Analysis at the University of Potsdam and holds an honorary Visiting Professorship at Imperial College London . He leads the Chair of Numerical Mathematics and serves as Editor-in-Chief of the SIAM/ASA Journal on Uncertainty Quantification since 2021. Research Interests Numerical methods for Hamiltonian systems Data assimilation in geoscience Stochastic particle filters Bayesian inference algorithms Molecular dynamics simulation Multi-scale modeling Collaborative Projects : Principal Investigator and former Speaker (2017-2024) of SFB 1294 Data Assimilation , a DFG-funded Collaborative Research Center Active participant in SFB 1114 Scaling Cascades in Complex Systems at Freie Universität Berlin Books Authored : Probabilistic Forecasting and Bayesian Data Assimilation (Cambridge UP, 2015) Simulating Hamiltonian Mechanics (Cambridge UP, 2005) Technical Contributions : Development of symplectic integration methods Innovations in ensemble Kalman filtering Regularization approaches for geophysical models Stochastic algorithms for molecular simulations
Eleni Myrto Asimakopoulou is a Researcher and Postdoctoral fellow specializing in synchrotron radiation research at MAX IV Laboratory, which is closely affiliated with Lund University in Sweden. She holds multiple affiliations within Lund University's research ecosystem, including membership in NanoLund: Centre for Nanoscience, LTH Profile Area: Nanoscience and Semiconductor Technology, LTH Profile Area: Photon Science and Technology, and LU Profile Area: Light and Materials. Her research focuses on advanced X-ray imaging techniques, with expertise spanning X-ray physics, crystal optics, phase contrast imaging, and high-resolution imaging systems. Dr. Asimakopoulou's work primarily addresses challenges in synchrotron radiation applications, with particular emphasis on developing novel imaging methodologies for scientific investigation. Analysis of her recent publications reveals a strong focus on cutting-edge imaging technologies, particularly in the development of MHz X-ray phase contrast imaging, crystal optics for multi-projection imaging, time-resolved imaging techniques using diffraction-limited storage rings, and high-resolution volumetric imaging systems. Her research demonstrates a consistent trajectory toward improving imaging speed, resolution, and capabilities for materials science and structural analysis applications. Dr. Asimakopoulou has received significant attention for her work, with multiple publications garnering readership on academic platforms like Mendeley and social media mentions on platforms like X (formerly Twitter). Her collaborative approach is evident through her extensive co-authorship networks across international research institutions. As a researcher at MAX IV's Science division, she contributes to advancing the capabilities of one of Europe's premier synchrotron radiation facilities, with particular focus on developing next-generation imaging techniques that push the boundaries of what's possible in materials characterization and structural analysis.
Dr. Jun Huang is an Assistant Professor at Forschungszentrum Jülich, leading the Helmholtz Young Investigator Group focused on the 'Theory of Electrocatalytic Interfaces.' He is affiliated with the Institute of Energy Technologies (IET), specifically in the department of Theory and Computer-Based Modelling of Materials in Energy Technology. His research centers on theoretical electrocatalysis and electrochemical interfaces, with expertise in: Electrical double layer phenomena and capacitance behavior Density-potential functional theory for metal-solution interfaces Multiscale modeling of electrochemical reaction environments Electrocatalyst design through computational methods Ion transport and interfacial structuring in energy systems His recent publications demonstrate a strong focus on developing fundamental theoretical frameworks for understanding electrocatalytic interfaces, with recurring themes in double-layer effects, reaction kinetics, and computational method development. The work bridges theoretical electrochemistry with applications in energy conversion and storage. Major recognitions include: Helmholtz Young Investigator Group Grant European Research Council Starting Grant Dr. Huang leads a computational research group developing advanced theoretical models to decipher electrocatalytic processes. His team focuses on creating predictive frameworks for interfacial reactions relevant to energy technologies.
Esmae Woods is a Research Fellow in the Department of Engineering, specializing in theoretical and computational physics with a focus on algorithmic and software development. She completed her PhD at the University of Cambridge, where she studied dynamical processes on energy landscapes, particularly in large ill-conditioned systems. Currently, she contributes to the MaThRad project, advancing Monte Carlo simulations for radiation transport applications such as criticality safety calculations. Education: PhD in Physics, University of Cambridge Her research bridges computational physics, numerical analysis, and biophysics. She develops algorithms to address challenges in energy landscape analysis, rare event simulations, and Markov chain modeling. Recent work emphasizes Monte Carlo methods for radiation transport and multiscale modeling of chromatin organization. Publications highlight her contributions to fields including energy transfer in photosynthetic systems, polaritonic rate suppression, and the structural dynamics of chromatin. Her methods are particularly impactful for systems where numerical instability complicates direct computation. Woods collaborates with researchers like Eugene Shwageraus and David J. Wales, advancing mathematical and computational frameworks in interdisciplinary contexts.
Mohammad Sarhil is a researcher at the University of Duisburg-Essen and a PostDoc at TU Dortmund University, affiliated with the Institute of Mechanics and Jörg Schröder's Lab. He holds a Dr.-Ing. (PhD) in Mechanics with distinction from 2024. Diploma in Structural Engineering (2012) from Latakia University, Syria M.Sc. in Computational Mechanics (2015) from University of Duisburg-Essen His research focuses on phase-field modeling , micromorphic continua , and metamaterials , particularly for fatigue analysis in fiber-reinforced concrete and higher-order homogenization theories. Key trends include finite element formulations, parameter identification, and multiscale residual stress analysis. Scientific recognition includes: DAAD scholarship Best Graduate award (Latakia University) His work bridges computational mechanics, generalized continuum theories, and fracture mechanics with applications in structural and materials engineering.
Daniele Padula serves as an Associate Professor in the Department of Biotechnology, Chemistry and Pharmacy at the University of Siena, where he teaches Applied Computational Chemistry, Organic Chemistry, and Heterocyclic Organic Chemistry for Chemistry, Biotechnology, and Pharmacy degree programs. His institutional contact details include office location (II lotto, III floor, room B_03_86) and direct communication channels through university email and phone systems. Padula's research integrates computational and organic chemistry methodologies to investigate fundamental properties of organic electronic materials. His primary focus areas include quantum-mechanical modeling of charge transport mechanisms, design of chiral photoluminescent systems with inverted singlet-triplet gaps, development of accurate force fields for molecular simulations, and computational exploration of photoswitches and organic semiconductors. This interdisciplinary work bridges theoretical chemistry with practical applications in optoelectronics and materials science. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research thrusts: (1) Advanced computational protocols for quantum-mechanically derived force fields (evident in JOYCE3.0 development), (2) Fundamental studies of chiral phenomena in organic materials for circularly polarized luminescence applications, and (3) Multiscale modeling of charge and exciton transport mechanisms in organic semiconductors. His work increasingly incorporates machine learning techniques to accelerate materials discovery while maintaining quantum chemical accuracy. Scientific awards: No awards or fellowships were documented in the provided materials. Advising and grant activities: The available documentation does not specify doctoral students, postdoctoral researchers, or externally funded research projects. His teaching portfolio indicates supervision of graduate and undergraduate theses within his computational chemistry courses. Research infrastructure: While specific laboratory facilities aren't detailed, his publication record suggests active participation in computational research groups with access to high-performance computing resources, likely through the University of Siena's computational chemistry infrastructure and potential collaborations with experimental groups for validation studies.
Jens Wackerfuß is a Full Professor of Structural Analysis and Executive Director of the Institute of Structural Mechanics at the University of Kassel, Germany, positions he has held since 2014. He also leads an Emmy Noether Junior Research Group at the university, demonstrating his significant research leadership. His academic background includes a Dr.-Ing. (Civil Engineering) from Technical University Darmstadt in 2005 and a Dipl.-Ing. (Civil Engineering) from the same institution in 1997. His professional journey includes post-doctoral work at UC Berkeley (2007-2008) and leadership of an Emmy Noether Junior Research Group at Technical University Darmstadt (2010-2013). Professor Wackerfuß's research spans computational mechanics with particular expertise in nonlinear finite element methods, advanced beam formulations, multiscale methods, and molecular mechanics. His work bridges theoretical developments with practical engineering applications, and he has developed the research code dockSIM for computational structural analysis. His teaching portfolio includes Structural Analysis I and II for Bachelor's students and Finite Element Methods, Material Models, and Multiscale Methods for Master's students. His recent publications (2022-2024) reveal a strong focus on constraint handling in finite element analysis, graphene modeling, and innovative structural formulations. Key trends include efficient methods for nonlinear multi-point constraints, coupling different structural elements, and applying computational methods to nanoscale materials. His scientific achievements have been recognized with several prestigious awards: Emmy Noether Programme of the German Research Foundation (DFG) in 2010 Zienkiewicz Medal and Prize in 2009, London (UK) Research fellowship of the German Research Foundation (DFG) at TU Darmstadt in 2008 Research fellowship of the German Research Foundation (DFG) at UC Berkeley in 2007 Professor Wackerfuß supervises doctoral and master's students through his Research Colloquium for Thesis and Doctoral Students. His grant portfolio includes significant funding from the German Research Foundation (DFG), particularly through the Emmy Noether Programme which supports outstanding early-career researchers. He leads the Institute of Structural Mechanics at the University of Kassel and maintains the research code dockSIM. His team focuses on developing advanced computational methods for structural analysis, with particular expertise in nonlinear systems, constraint handling, and multiscale modeling approaches that bridge molecular and continuum mechanics.
Tapio Ala-Nissilä is Professor of Physics at Aalto University School of Science, Finland, where he heads the Multiscale Statistical and Quantum Physics (MSP) group. He simultaneously serves as Head of the Interdisciplinary Centre for Mathematical Modelling and Professor of Applied Mathematics & Theoretical Physics at Loughborough University, UK, and as Adjunct Professor of Physics at Brown University, USA. His research spans statistical physics, quantum mechanics, and soft matter systems with emphasis on computational approaches. Key interests include complex fluids, nanofluids, polymer translocation, quantum thermodynamics, and open quantum systems. He extensively employs molecular dynamics, Monte Carlo methods, and density functional theory to study nanoscale phenomena in biological, material, and quantum contexts. Recent publications (2024-2025) reveal strong interdisciplinary trends across quantum materials, biophysics, and environmental engineering. Work focuses on thermal properties of 2D materials like graphene, protein dynamics in viral systems, novel surface phenomena in liquid-repellent materials, and advanced computational methods for many-body quantum systems. He directs the Multiscale Statistical and Quantum Physics group at Aalto University investigating fundamental quantum and statistical phenomena, and leads the Interdisciplinary Centre for Mathematical Modelling at Loughborough University fostering cross-departmental collaboration in applied mathematics.
Patricio Farrell is an applied mathematician and Research Group Leader at the Weierstrass Institute Berlin (WIAS), focusing on numerical analysis, scientific computing, and mathematical modeling for semiconductor devices. His work bridges applied analysis and practical applications, particularly through structure-preserving numerical methods for drift-diffusion systems and nonlinear PDEs. Key applications include next-generation semiconductors, perovskite photovoltaics, and neuromorphic computing. He actively collaborates with institutions like Inria Lille, the University of Oxford, and the Helmholtz Zentrum Berlin. Vice Chair of KOMSO (Committee for Mathematical Modeling, Simulation and Optimization) Editor of Open Mathematics Scientific Ambassador for Brain City Berlin Developed ChargeTransport.jl , an open-source Julia tool for semiconductor simulations used in academia and industry His research interests span numerical analysis, nonlinear PDEs, finite volume methods, and meshfree techniques, with applications in perovskites, nanowires, memristors, quantum wells, and laser design. He has secured ~€1.5M in third-party funding from organizations like the Leibniz Association and MATH+. Scientific Awards: Capital's Top 40 under 40
Jian-Guo Liu is a Professor of Mathematics and Physics at Duke University, with primary affiliations in the Departments of Mathematics and Physics. His research encompasses applied mathematics, partial differential equations, kinetic theory, computational fluid dynamics, and stochastic algorithms. Professor Liu's work bridges theoretical modeling and numerical methods, particularly in complex systems involving nonlinear dynamics, fluid behavior, and emergent phenomena. Research interests focus on multiscale modeling of physical systems, including stochastic processes in chemical reactions, fluid-structure interactions, and materials science. Recent publications demonstrate strong emphasis on mathematical foundations of biological and physical systems, with recurring themes in Fokker-Planck dynamics, mean-field games, tumor growth modeling, and computational methods for interfacial phenomena. Publications showcase consistent focus on analytical and numerical solutions to high-dimensional problems, with applications ranging from medical imaging to electrochemistry. The work exhibits advanced techniques in asymptotic analysis, stochastic approximations, and geometric evolution equations.
G. Allan Johnson is the Charles E. Putman University Distinguished Professor of Radiology at Duke University, with concurrent appointments in Physics (Trinity College of Arts & Sciences) and Biomedical Engineering (Pratt School of Engineering). He serves as Director of the Duke Center for In Vivo Microscopy , an NIH/NIBIB national Biomedical Technology Resource Center focused on developing preclinical imaging technologies and applying them to critical biomedical questions. Ph.D. in Radiology from Duke University (1974) Current leadership in preclinical MRI and connectomics His research spans high-resolution magnetic resonance imaging , diffusion MRI , and structural connectomics , with applications to neurodegenerative diseases , brain development , and biomedical engineering . Recent work includes creating multicontrast MR atlases for rodent brains and pioneering ex vivo MRI-histology fusion techniques . Selected publications reveal expertise in diffusion tensor imaging , tractography , and multimodal imaging workflows for both preclinical and clinical applications . Grants include leadership in projects funded by the CHDI Foundation (Huntington's disease), University of Pittsburgh (connectome atlases), and University of Tennessee Health Science Center (Alzheimer's imaging genetics). Scientific recognition includes NIH/NIBIB Resource Center Leadership Charles E. Putman University Distinguished Professorship His team at the Duke Center for In Vivo Microscopy develops multiparametric imaging platforms , 4D cardiac micro-CT atlases , and quantitative susceptibility mapping methods for applications ranging from neurotoxicology to plant root imaging .
Dr Adnan Sufian is an Honorary Lecturer at the School of Civil Engineering, University of Queensland, with expertise in multiscale mechanics of granular materials. His research bridges geotechnical engineering and computational modeling, focusing on fluid-soil interactions and civil infrastructure resilience. PhD from UNSW Sydney Visiting scholar at MIT Postdoctoral work at Imperial College London Industry experience with SMEC Australia His research addresses granular material behavior under complex conditions, including internal erosion dynamics in dams, particle migration in gap-graded soils, and seismic stability of engineered landfills. Methodologically, he employs CFD-DEM coupling , pore network models , and Voronoi tessellation for granular simulations. The 15 most recent publications highlight a focus on erosion mechanisms , filter design , seismic stability , and microcapsule retention in granular media. These works utilize computational methods (CFD-DEM, PNM-DEM) and experimental techniques (X-ray CT, time domain reflectometry) to analyze soil-fluid interactions. Dr Sufian is available for supervision, with current projects on resilient infrastructure and past completions investigating micro-scale erosion conditions and particle migration dynamics . His research has been supported by grants from ARC and UQ, including projects on real-time erosion prediction and geotechnical data integration. Key collaborations span physicists, mathematicians, and engineers , reflecting the interdisciplinary nature of his work on granular material behavior. The ARC Advance Timber Hub and partnerships with institutions like Imperial College London and UNSW Sydney further contextualize his academic network.
Dr. Travis Mitchell is a Lecturer at the School of Mechanical and Mining Engineering , The University of Queensland , and an affiliate of the Centre for Multiscale Energy Systems . He holds a PhD in Multiphase Computational Fluid Dynamics and dual degrees in Mechanical Engineering (BE Hons) and Mathematics (BSc). Education: PhD in Multiphase Computational Fluid Dynamics, The University of Queensland BE (Hons) in Mechanical Engineering, The University of Queensland BSc in Mathematics, The University of Queensland Research Interests focus on numerical modeling of multiphase fluid dynamics in porous media , with applications spanning CO2 electrolysis , hydrogen production via methane pyrolysis , biomedical fluid-structure interaction , and geomechanical fracture analysis . His methodological expertise includes Lattice Boltzmann techniques and high-performance computing . Recent Work Trends encompass multiphase transport in fractured media , gas diffusion electrode optimization , fiber-based air filter design , and thermocapillary flow modeling , reflecting his interdisciplinary impact in energy, health, and resource engineering. Scientific Recognition includes the ICMMES-CSRC Award for multiphase lattice Boltzmann research and an EAIT Citation for Excellence in Student Learning (2023) . Teaching Portfolio includes coordination of MECH2700: Computational Engineering and Data Analysis and lectures in MECH3780: Computational Mechanics and MECH6480: Computational Fluid Dynamics .
