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Taner AkbayView profile

Professor

• Materials Engineering
• Metallurgical Engineering
• Physical Metallurgy
• +6 more

Prof. Dr. Taner Akbay is a faculty member at Yeditepe University, Faculty of Engineering , Department of Materials Science and Nanotechnology Engineering. He has held academic positions at institutions including Kyushu University, Oita University, and Imperial College London. Education: PhD in Materials Engineering (1993, Imperial College London); Master’s (1989) and Bachelor’s (1986) degrees from Middle East Technical University. His research spans Materials Engineering , Metallurgy , and Solid Oxide Fuel Cells (SOFCs) , with a focus on oxide ion conductivity, laser surface treatment, and phase transformations. Recent work explores photocatalysis , anion intercalation , and CO2 reduction using computational and experimental approaches. Key article trends include SOFC optimization (2004–2009), strain effects on catalysts (2015–2020), and dual-carbon battery technology (2016–2020). His work bridges fundamental metallurgy and advanced energy materials . Scientific Awards: Postdoctoral Research Sponsorship Award (EPSRC, UK) JSPS Fellowship (Japan) Daiwa Adrian Prize (2016, UK) PhD Studentship at Imperial College (European Commission) He has supervised multiple PhD and Master’s theses, including projects on dual-carbon batteries , microwave absorption nanocomposites , and rare earth recovery . Administrative roles include Head of Department (2020–2021). Non-University Experience: Worked with Mitsubishi Materials Corporation (2001), Çolakoğlu Metalurji (2010), and National Research Council Canada (2009).

• Nonlinear partial differential equations
• Singularity formation
• Mathematical analysis
• +2 more

Manuel Del Pino is Professor at the University of Bath's Department of Mathematical Sciences and Royal Society Professor specializing in nonlinear partial differential equations. His research focuses on singularity formation, geometric evolution equations, and asymptotic analysis in fluid dynamics and mathematical physics. His investigations encompass blow-up phenomena in heat equations, vortex dynamics in Euler flows, and minimal surface theory. Current projects examine infinite-time singularity formation in parabolic equations and asymptotic properties of vortex configurations. Del Pino has received the Royal Society Professorship and leads multiple grants including 'Asymptotic patterns in nonlinear evolution problems' (EPSRC). He maintains collaborations with researchers globally through projects on singularity formation in PDEs.

• Statistical Physics
• Complex Systems
• Thermodynamics
• +2 more

Massimiliano Esposito is a Full Professor of Theoretical Physics at the University of Luxembourg, affiliated with the Faculty of Science, Technology and Medicine (FSTM) and the Department of Physics and Materials Science. His research focuses on statistical physics, complex systems, thermodynamics, chemical networks, and quantitative biology. He holds positions such as ERC Fellow (2016-2021) and Attract Fellow (2012-2017). Education includes a Ph.D. in Sciences (2004) and a degree in Chemistry (2000) from the Free University of Brussels (Belgium), alongside a European Baccalaureate (1996) from Luxembourg. His work bridges stochastic thermodynamics, quantum thermodynamics, and chemical reaction networks, with contributions to fluctuation theorems, energy transduction, and non-equilibrium systems. Key achievements include seminal papers on nonequilibrium fluctuation-response relations, quantum thermodynamics, and chemical reaction network theory. He has been a guest editor for journals like Physica A and Physical Review X, and serves on editorial boards such as Physical Review Letters. His lab explores emergent phenomena in complex systems, with applications in biology and nanotechnology.

Matthias WinterView profile

Senior Lecturer

• Mathematical Biology
• Pattern Formation
• Reaction-Diffusion Systems
• +7 more

Dr. Matthias Winter is a Senior Lecturer in the Department of Mathematics at Brunel University's College of Engineering, Design and Physical Sciences. He has been affiliated with Brunel since 2005, following academic positions at the University of Stuttgart (1996-2005) and postdoctoral fellowships at the Institute for Advanced Study in Princeton (1993-94) and Heriot-Watt University in Edinburgh (1994-96). His educational background includes a PhD from Stuttgart University in 1993 and a Habilitation from the same institution in 2003. Dr. Winter's research focuses on mathematical biology, particularly pattern formation in biological systems through reaction-diffusion equations. His work examines spike solutions, pattern formation mechanisms, and the mathematical analysis of biological phenomena. He has made significant contributions to understanding stable spike clusters in various contexts including the Gierer-Meinhardt system. His research spans Mathematical Biology, Pattern Formation, Reaction-Diffusion Systems, Nonlinear Partial Differential Equations, and several related mathematical disciplines. His recent publications (2023-2025) demonstrate continued activity across diverse applications including cancer modeling, ecological systems, climate modeling, and fundamental mathematical analysis of reaction-diffusion phenomena, showing his ability to apply sophisticated mathematical techniques to real-world biological problems. Editorial Board, ISRN Mathematical Analysis, since 2010 Academic Appeals Committee, since 2013 Level One Coordinator for Mathematics, since 2013 Course Director MSc Programme Computational Mathematics with Modelling Mathematics, 2008-2010 Dr. Winter teaches various mathematics courses including Mathematics and Statistics for Economists, Vector Calculus, and Group Projects in Mathematics, with a teaching portfolio spanning from foundational courses to specialized topics related to his research interests.

Yali TangView profile

Assistant Professor

• Fluid Dynamics
• Multiphase Flow
• Physicochemical Conversions
• +7 more

Yali Tang is an Assistant Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), specializing in fluid dynamics and transport phenomena within multiphase flows and physicochemical conversions . Her work targets Iron Power technology , green steel production , and alkaline water electrolysis for hydrogen generation, combining advanced computational models with experimental validation . Education: Master's in Chemical Engineering from Sichuan University (2011) PhD in Mechanical Engineering at TU/e (2015) with Prof. Hans Kuipers Research Interests: She focuses on interphase interactions , interfacial transport mechanisms , and high-resolution simulations (down to 40 nm mesh) to predict bubble coalescence and film dynamics. Her studies on hydrogen bubble growth , dendritic iron formation , and gas distribution in electrolyzers aim to refine reactor design and industrial processes. Collaborations with industrial partners ensure practical applicability of her computational models. Recent Publications: Her 2025 work includes dimensional analysis of liquid film formation, solutal Marangoni effects in electrolysis, and X-ray validation of gas distribution models. Earlier studies (2020–2023) cover defluidization behavior of iron fines, CFD-DEM modeling of raceways, and acoustic field applications in particle dynamics. Labs & Collaborations: She leads computational efforts within the Power & Flow group under Prof. Niels Deen, contributing to the EIRES Research cluster. Her work bridges academic research with industrial innovation in fluid dynamics and energy transition technologies.

Christopher M. WolvertonView profile

Professor

• Computational Materials Science
• Energy Storage Materials
• First-Principles Quantum Mechanics
• +7 more

Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.

Mark WallaceView profile

Professor

• Membrane Biology
• Biophysics
• Optical Microscopy
• +3 more

Mark Wallace is a Professor of Chemistry at King's College London, affiliated with the Department of Chemistry and the Faculty of Natural, Mathematical & Engineering Sciences. He holds a Royal Society University Research Fellowship (2005–2016) and has been a lecturer at Oxford University before joining King's in 2016. His research focuses on membrane protein function and artificial membrane mimics, combining optical microscopy and nanotechnology. He earned a PhD from the University of Cambridge (2002) and postdoctoral training at Stanford University and the National Institute for Medical Research. Key research interests include membrane protein dynamics, lipid bilayer engineering, and single-molecule imaging. He has pioneered techniques like droplet interface bilayers and interferometric scattering microscopy. His work has led to patents and applications in molecular sensing and medical research. Awards include the 2002 Gregorio Weber Prize and the 2015 RSC Norman Heatley Award. He is actively involved in public outreach, including video podcasts and educational competitions. Recent publications emphasize artificial ion channels, nanoparticle formation monitoring, and mitochondrial protein dynamics. His lab collaborates with institutions like the London Centre for Nanotechnology and the Rosalind Franklin Institute. Over 30 students and researchers have been mentored, with active grants from EPSRC, Wellcome Trust, and BBSRC.

Xavier BrussetView profile

Professor

• Supply Chain Management
• Logistics
• Operations Management
• +6 more

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +12 more

Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.

• Machine Learning
• Dynamical Systems
• Optimization
• +3 more

Michael Muehlebach leads the independent Learning and Dynamical Systems research group at the Max Planck Institute for Intelligent Systems in Tuebingen, Germany. His interdisciplinary work bridges machine learning, dynamical systems theory, and control engineering to develop algorithms for cyber-physical systems with theoretical guarantees and practical implementations. Dr. Muehlebach received his B.Sc. and M.Sc. in Mechanical Engineering from ETH Zurich in 2010 and 2013, specializing in robotics and control systems. He completed his Ph.D. at ETH's Institute for Dynamic Systems and Control under Prof. R. D'Andrea in 2018, followed by postdoctoral research with Prof. Michael I. Jordan at UC Berkeley. His research focuses on constrained optimization, reinforcement learning, and control theory with applications in robotics. He pioneered approaches that express constraints in terms of velocities rather than positions, enabling more efficient optimization algorithms. His work spans theoretical foundations to physical implementations, including the One-Wheel Cubli balancing robot and electromagnetic navigation systems. Recent publications reveal a strong trend toward physics-informed machine learning, particularly for robotics applications requiring real-time performance and safety guarantees. Dr. Muehlebach has received numerous prestigious awards: Outstanding D-MAVT Bachelor Award Willi-Studer prize for best Master's degree ETH Medal and HILTI prize for doctoral thesis Branco Weiss Fellowship (2018) Emmy Noether Fellowship (2020) Amazon Fellowship (2024) He actively mentors doctoral researchers including Hao Ma, Melis Ilayda Bal, and Onno Eberhard, with research supported by multiple grants. His group maintains strong collaborations with Bernhard Schölkopf's Empirical Inference group at the Max Planck Institute. The Learning and Dynamical Systems group develops innovative hardware and software platforms, including Floaty (a wind-harnessing flying robot), advanced electromagnetic navigation systems, and data-efficient learning methods for robotic table tennis. Their approach combines rigorous theoretical analysis with practical validation on physical systems, emphasizing the integration of known physical structure into machine learning algorithms to improve sample efficiency and ensure generalization.

George BritovsekView profile

Professor

• Catalysis
• Sustainable Carbon Management
• Transition Metal Complexes
• +3 more

Professor George Britovsek (FRSC) is a leading figure in catalysis and sustainable carbon management at Imperial College London . As Director of the MRes in Catalysis & Engineering and Head of Teaching in Inorganic Chemistry, he bridges academic leadership with cutting-edge research. His work focuses on transition metal complexes for converting ethylene , alkanes , biomass , and CO₂ into valuable chemicals and fuels through industrial collaborations. Education : M.Sc. (Technical University of Aachen, 1990), Ph.D. (Aachen, 1993) under Prof. W. Keim Postdoctoral Training : University of Tasmania (1994-1996), Imperial College London (1996-2000) His research interests span: Selective oxidation of alkanes using bio-inspired iron complexes Alkene conversions to functional polymers via novel catalysts CO₂ valorization into polymers and cyclic carbonates Biomass-derived feedstocks for chemical synthesis Recent catalysis trends highlight his work on: Designing Fe-N/C catalysts for epoxidation Developing PN3P pincer ligands for H₂ activation Creating degradable polyethylene via iron-catalyzed chain growth Modeling alternating α-olefin distributions in chromium systems Awards : Fellow of the Royal Society of Chemistry (FRSC) Students & Collaborators actively engage in: Photocatalytic polymer degradation Electrocatalytic CO₂ conversion Functionalized polymeric materials 3D-printed catalytic scaffolds His Britovsek Research Group operates at the Molecular Sciences Research Hub, White City Campus, advancing both homogeneous and heterogeneous catalysis through experimental and computational approaches.

Graham DobereinerView profile

Associate Professor

• Homogeneous Catalysis
• Organometallic Chemistry
• Synthetic Chemistry
• +2 more

Graham Dobereiner is an Associate Professor and Robert L. Smith Early Career Professor in the Department of Chemistry at Temple University's College of Science and Technology. He received his Ph.D. from Yale University (2011) and completed postdoctoral research at MIT (2012-2014) after earning his B.S. from Brandeis University (2007). His research group develops novel homogeneous transition metal catalysts for synthetic chemistry applications spanning fine chemicals manufacturing, petrochemical processing, and drug discovery. The work integrates organometallic chemistry principles, combining organic molecular diversity with inorganic compound reactivity. Research areas include catalytic isomerization, oxidative synthesis, ligand design, and mechanistic studies of transition metal complexes. Analysis of his recent publications demonstrates strong emphasis on reaction mechanism elucidation, catalyst design for stereoselective transformations (particularly Z-selective isomerizations), and development of novel catalytic systems for sustainable synthesis. His group employs computational and experimental approaches to advance synthetic methodology.

Maarten de BoerView profile

Professor

• Mechanics of Materials
• MEMS (Microelectromechanical Systems)
• Micro/Nano Manufacturing
• +7 more

Maarten de Boer is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Materials Science and Engineering. He joined CMU in 2007 after roles as a process engineer at Hewlett-Packard (1983–1991) and principal member of technical staff at Sandia National Labs (1996–2010). He holds a Ph.D. in Materials Science (University of Minnesota, 1996), an MS in Electrical Engineering (University of Colorado, 1982), and a BS in Electrical Engineering (Cornell University, 1981). His research focuses on nanomechanical behavior of materials, MEMS, and additive manufacturing. Key projects include tantalum-based thermal actuators, high-entropy alloys, and micromachine reliability. His work is funded by the DOE, NSF, NASA, and the Army Research Lab. He has authored over 90 peer-reviewed articles, holds seven US patents, and advises students in the de Boer Group. Research Themes: Micro/Nano Manufacturing, Thin Film Mechanics, Friction & Wear, MEMS Reliability Funding Sources: NSF, DOE, NASA, ARL Courses Taught: Mechanics of Materials, Material Selection, Electronics for Sensing, Thermodynamics Notable collaborations include Gianluca Piazza (NSF LEAP-HI grant), Jack Beuth, and Bryan Webler (high-entropy alloys). Media highlights include breakthroughs in tantalum MEMS and ultra-strong polymer nanofibers. His group operates advanced test facilities for in-situ environmental studies of materials.

• Machine Learning
• Dynamical Systems
• Control Theory
• +4 more

Michael Mühlebach is a Research Group Leader at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, leading the independent Learning and Dynamical Systems group. His academic journey began at ETH Zurich where he earned his B.Sc. (2010) and M.Sc. (2013) in mechanical engineering, specializing in robotics, systems, and control. He completed his Ph.D. at ETH Zurich in 2018 under Prof. R. D'Andrea, followed by postdoctoral research at UC Berkeley with Prof. Michael I. Jordan. Dr. Mühlebach's research spans machine learning, dynamical systems, control theory, and optimization . His work bridges theoretical foundations with practical applications in robotics, developing methods that incorporate physical constraints and system dynamics into learning frameworks. His group focuses on online learning, physics-informed machine learning, and large-scale optimization for cyber-physical systems, with applications in electromagnetic navigation, robotic table tennis, and energy-efficient flight systems like the shape-changing robot Floaty . His publication record shows a strong focus on constrained optimization, with recent work exploring decision-dependent stochastic optimization, nonlinear feedback, and the theoretical foundations of reinforcement learning. His research integrates perspectives from control theory, dynamical systems, and optimization to develop algorithms with strong theoretical guarantees and practical performance. Outstanding D-MAVT Bachelor Award Willi-Studer prize for best Master's degree ETH Medal and HILTI prize for doctoral thesis Branco Weiss Fellow (2018) Emmy Noether Fellowship (2020) Amazon Fellowship (2024) Dr. Mühlebach actively mentors doctoral researchers and is seeking talented students for PhD and Master's projects. His research group has received funding from multiple prestigious fellowships and maintains collaborations across institutions including ETH Zurich, UC Berkeley, and various Max Planck research units. The group's work spans theoretical developments to practical implementations on robotic systems, demonstrating strong connections between mathematical theory and physical realization.

Xiaoming HuView profile

Professor

• Multi-agent systems
• Nonlinear control systems
• Systems theory
• +4 more

Xiaoming Hu is a Professor at the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH Royal Institute of Technology (Kungliga Tekniska Högskolan) in Stockholm, Sweden. Born in Chengdu, China, he received his B.S. degree from University of Science and Technology of China in 1983, followed by M.S. and Ph.D. degrees from Arizona State University in 1986 and 1989 respectively. After serving as a research assistant at the Institute of Automation, Chinese Academy of Sciences (1983-1984), he was a Gustafsson Postdoctoral Fellow at KTH (1989-1990) before becoming a faculty member. His educational background includes: B.S. in Engineering, University of Science and Technology of China, 1983 M.S. in Engineering, Arizona State University, 1986 Ph.D. in Engineering, Arizona State University, 1989 Xiaoming Hu's research primarily focuses on multi-agent systems, nonlinear feedback stabilization, nonlinear observer design, and sensing and active perception. His work bridges theoretical control theory with practical applications in robotics and autonomous systems. He has made significant contributions to geometric control theory, mathematical systems theory, and nonlinear systems analysis and control. His research often involves developing theoretical frameworks for distributed control, formation control, and cooperative behavior in multi-robot systems. Professor Hu's publication record shows a consistent research trajectory with numerous high-impact publications in top-tier journals like Automatica, IEEE Transactions on Automatic Control, and Systems & Control Letters. His research has evolved from fundamental control theory to more applied problems in robotics and multi-agent systems, while maintaining strong mathematical foundations. Recent work shows increasing focus on safety-critical control, inverse problems in estimation, and networked systems. His scientific contributions include: Development of theoretical frameworks for multi-agent coordination and formation control Advances in nonlinear observer design for robotic systems Contributions to geometric control theory and systems theory Research on distributed estimation and control algorithms Applications of control theory to robotics and autonomous systems Professor Hu teaches several advanced courses including Mathematical Systems Theory, Geometric Control Theory, and Nonlinear Systems: Analysis and Control. He has supervised numerous degree projects at both undergraduate and graduate levels in mathematics, optimization, systems theory, and scientific computing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of control theory.