جست‌وجوی استاد و پژوهشگر

• Theoretical Computer Science
• Error-Correcting Codes
• Approximation Algorithms
• +۵ مورد دیگر

Venkatesan Guruswami is a Chancellor's Professor in the Department of EECS and a Senior Scientist at the Simons Institute for the Theory of Computing at UC Berkeley . He also holds a Professor position in the Department of Mathematics . His academic journey began with a B.Tech in Computer Science from the Indian Institute of Technology, Madras (1997) , followed by a Ph.D. in Computer Science from the Massachusetts Institute of Technology (2001) . After a Miller Research Fellowship at UC Berkeley (2001–02), he held faculty roles at the University of Washington and Carnegie Mellon University before returning to UC Berkeley in January 2022. Education : B.Tech, IIT Madras (1997) Ph.D., MIT (2001) Professional Affiliations : Chancellor's Professor, UC Berkeley (EECS) Senior Scientist & Interim Director, Simons Institute Professor, UC Berkeley (Mathematics) Guruswami's research spans multiple domains within Theoretical Computer Science , focusing on Error-Correcting Codes , Approximation Algorithms , Randomness in Computing , Probabilistically Checkable Proofs , and Computational Complexity . His groundbreaking work in List Decoding has enabled codes with minimal redundancy for correcting worst-case errors, while recent advancements include Polar Codes , Deletion-Correcting Codes , and Constraint Satisfaction Problems . He has also contributed to Quantum Coding Theory , Locally Recoverable Codes , and Approximation Hardness in various computational contexts. His publications reflect a deep engagement with interdisciplinary topics. Key trends include: Quantum Information Theory : Quantum LDPC codes, transversal gates, and quantum storage. Algebraic Coding : Reed-Solomon codes, AG codes, and polynomial-based constructions. Computational Complexity : Hardness of approximation, CSPs, and parameterized intractability. Data Transmission : Polar codes, deletion channels, and feedback mechanisms. Algorithmic Techniques : Spectral methods, semirandom models, and Lasserre hierarchy applications. Guruswami has received numerous accolades, including the Simons Investigator Award , Presburger Award , Packard Fellowship , Sloan Research Fellowship , ACM Doctoral Dissertation Award , and the IEEE Information Theory Society Paper Award . He is an ACM Fellow (2017) and IEEE Fellow (2019) , with recent honors like the Guggenheim Fellowship (2023) and AMS Fellow (2023) . As an advisor, he has mentored over 25 PhD and postdoctoral researchers , including Atri Rudra , Prasad Raghavendra , and Peter Manohar , whose work has won awards like the Edmund M. Clarke Doctoral Dissertation Award and CRA Outstanding Undergraduate Researcher Award . His research is supported by grants from the National Science Foundation , Packard Foundation , and Sloan Foundation . He also serves as Editor-in-Chief of the Journal of the ACM and holds leadership roles in IEEE and arXiv moderation. Guruswami is actively involved in Simons Institute programs and co-organized workshops on Coded Computation and Information Theory . His work bridges theoretical advancements with practical applications in Cloud Storage , Quantum Computing , and Group Testing , including pandemic-era contributions like AC-DC: Amplification Curve Diagnostics for SARS-CoV-2 .

• Chromatography
• Porous Media
• Materials Science
• +۷ مورد دیگر

Ulrich Tallarek serves as Professor of Analytical Chemistry in the Faculty of Chemistry at Philipps University of Marburg, where he has held a W3 professorship since 2011. He also serves on the Board of Directors for the Materials Science Center at the university, a position he has held since 2007. His research group focuses on the fundamental understanding of transport phenomena in porous media with applications spanning chromatography, battery technology, and microfluidic systems. The group maintains strong collaborations with institutions worldwide and secures substantial research funding for advanced computational and experimental work. Professor Tallarek's research interests center on functional porous solids, with specific focus on morphology-transport-performance relationships. His work bridges multiple scales from molecular dynamics simulations of solute behavior in nanopores to macroscopic transport in chromatographic columns and battery electrodes. Key research areas include diffusion in hierarchical porous media, electrokinetic phenomena in microfluidic systems, molecular simulation of chromatographic processes, and advanced characterization of porous materials using tomography and other techniques. His group has pioneered multiscale simulation approaches that connect molecular-level surface chemistry to macroscopic transport properties. The research output demonstrates consistent focus on understanding fundamental transport mechanisms in porous systems, with recent publications emphasizing multiscale simulation techniques, molecular dynamics studies of solvent effects in chromatography, advanced characterization of mesoporous structures, and applications to separation science and energy storage. The work shows strong integration of computational modeling with experimental validation across multiple length scales. 2003: Desty Memorial Prize for Innovation in Separation Science, The Royal Institution of Great Britain, London 2006: Young Scientist Award from DECHEMA e.V. 2011: Named Discussion Leader at the 2011 Gordon Research Conference on Physics & Chemistry of Microfluidics 2011–2012: Chairman of the German Chemical Society (GDCh), Marburg 2013: Finalist, World Technology Awards, for category Environment 2013: Named as one of the 100 most influential analytical scientists in the world (The Analytical Scientist Power List) 2017: Recipient of the Silver Jubilee Medal 2017, The Chromatographic Society, UK Professor Tallarek's research has been supported by numerous grants enabling high-performance computing resources, advanced instrumentation, and international collaborations. His group maintains strong ties with industry partners in separation science and analytical instrumentation. The Tallarek Research Group includes postdoctoral researchers, PhD students, and technical staff working across experimental and computational domains. Current projects focus on molecular simulation of chromatographic processes, advanced characterization of porous battery electrodes, and development of novel separation methodologies. The Tallarek Research Group operates state-of-the-art facilities for computational modeling, including access to high-performance computing resources at Forschungszentrum Jülich. The group also maintains experimental capabilities for chromatographic analysis, materials characterization, and microfluidic device development. Their work on physically reconstructed porous media has established new standards for connecting microstructure to transport properties in complex materials systems.

Kenneth S Schweizerمشاهده پروفایل

استاد

• Statistical Mechanics
• Soft Materials
• Complex Fluids
• +۵ مورد دیگر

Professor Kenneth S Schweizer is the G. Ronald and Margaret H. Morris Professor of Materials Science and Engineering, and holds concurrent professorships in Chemistry, Chemical and Biomolecular Engineering, and the Materials Research Laboratory at the University of Illinois at Urbana-Champaign (UIUC). He earned his B.S. (summa cum laude) from Drexel University and his Ph.D. in Physics from UIUC. His research focuses on statistical mechanics of soft materials, including polymers, colloids, and complex fluids, with emphasis on their thermodynamics, phase transitions, and nonlinear rheology. Key contributions include theories of glass transition dynamics, nanoparticle-polymer suspensions, and vitrimer networks. Schweizer has received prestigious awards such as the American Academy of Arts and Sciences membership (2021), APS Polymer Physics Prize (2008), and Hildebrand Award (2016). He has led major NSF-funded initiatives, including the Nanoscale Science and Engineering Center for Directed Assembly of Nanostructures. His work bridges fundamental theory and practical material design, addressing challenges in energy storage, biomaterials, and nanotechnology. Research interests span structural organization in soft materials, dynamic arrest phenomena, and the interplay between thermodynamics and relaxation processes. Recent studies explore ion transport in polymerized ionic liquids, activated dynamics in colloidal suspensions, and elastic properties of vitrimers. His theoretical frameworks, such as elastically collective activated dynamics and self-consistent hopping models, provide predictive tools for material innovation. Teaching and advising excellence is highlighted by UIUC awards including the 2022 Campus-wide Award for Excellence in Graduate Teaching. Schweizer’s labs and collaborations involve interdisciplinary teams addressing cutting-edge topics like biomolecular condensates and nanoconfined systems.

Matthew Jenssenمشاهده پروفایل

دانشیار

• Discrete Probability
• Probabilistic/Extremal Combinatorics
• Statistical Physics
• +۵ مورد دیگر

Matthew Jenssen is a Reader in Probability at King's College London and a UKRI Future Leaders Fellow. He holds a BA and MMath from the University of Cambridge (2012–2013) and a PhD from the London School of Economics (supervised by Jozef Skokan and Julia Boettcher). His research focuses on the intersection of combinatorics, statistical physics, and theoretical computer science, particularly on large-scale structure formation in systems with local interactions. Notable contributions include advancements in sphere packing, Ramsey numbers, and random matrix theory. Jenssen has held postdoctoral positions at the University of Oxford and the University of Birmingham before joining King’s in 2023. His research group at King’s explores discrete probability, extremal combinatorics, and algorithms, with applications to statistical physics and high-dimensional geometry. Key achievements include a groundbreaking improvement on sphere packing lower bounds and resolving extremal questions in graph theory. Jenssen’s work often bridges combinatorial theory with computational methods, yielding impactful results in probabilistic combinatorics. Scientific awards include the UKRI Future Leaders Fellowship (2020). His grants include a 2023–2026 project on statistical physics methods in combinatorics and geometry. Jenssen collaborates widely, with notable co-authors including Will Perkins, Jozef Skokan, and Felix Joos. He is actively involved in the Probability Group at King’s and contributes to international conferences and arXiv publications.

• Applied Mathematics
• Mathematical Physics
• Computational Science
• +۳ مورد دیگر

Ben Goddard is a Professor in the School of Mathematics at the University of Edinburgh. His work bridges applied mathematics with real-world scientific challenges, emphasizing interdisciplinary collaboration across engineering, biology, chemistry, and physics. He earned his PhD at the University of Warwick, later completing his final year at TU Munich following his advisor. His research focuses on mathematical modeling, numerical methods, and asymptotic analysis applied to problems such as quantum chemistry, fluid dynamics, and biological systems. Education: Bachelor’s degree in Mathematics (undergraduate details unspecified) PhD in Mathematical Quantum Chemistry (University of Warwick/TU Munich) Research interests include: Dynamic density functional theory (DFT) for complex fluids and nanoparticles Interfacial phenomena and contact line dynamics Numerical optimization and pseudospectral methods Biological systems modeling (e.g., RNA transcription mechanics) Recent work explores applications like ouzo phase behavior, aerosol droplet stability, and opinion dynamics in social networks. His collaborations span diverse fields, including experimental biology at the Welcome Centre for Cell Biology. He advocates for mathematicians’ role in interdisciplinary problem-solving, emphasizing clear communication and adaptability. Advising and grants: While specific grant details are not listed, his projects reflect significant funding and team-based research. He actively promotes STEM engagement through activities like designing math-themed escape rooms with his spouse, a statistician. Labs/Teams: Collaborates extensively with Edinburgh’s Schools of Engineering, Biology, and Informatics, though no specific lab names are mentioned.

Rajinder Palمشاهده پروفایل

استاد

• Rheology
• Colloidal Dispersions
• Material Science
• +۷ مورد دیگر

Rajinder Pal is a Professor at the University of Waterloo, specializing in rheology of complex fluids, colloidal systems, and transport phenomena. His research focuses on the rheological behavior of suspensions, emulsions, and nanomaterials, with particular emphasis on non-Newtonian fluid dynamics, interfacial phenomena, and exergy analysis of multiphase flows. He has contributed extensively to understanding the viscosity modeling of concentrated suspensions and emulsions, nanoparticle-stabilized dispersions, and thermodynamic optimization of industrial processes. Key research areas include the development of novel viscosity models for asphaltene nanoaggregates, cellulose nanocrystals, and starch nanoparticles in industrial applications. His work bridges fundamental fluid mechanics with practical engineering challenges, addressing topics such as catastrophic phase inversion in Pickering emulsions, drag reduction in turbulent flows, and exergy destruction in pipeline systems. Pal also investigates the integration of nanomaterials into energy storage systems, such as graphene-based supercapacitors stabilized by ionic liquid/surfactant complexes. His publications span over two decades, demonstrating sustained contributions to chemical engineering, material science, and colloid science. Notable recent work includes studies on rheology of high internal phase emulsions (HIPEs), nanocomposite mechanical properties, and the thermodynamic analysis of cyclic processes using the Gouy-Stodola theorem. Pal's research has implications for food processing, pharmaceuticals, oil recovery, and sustainable materials development. While no formal awards or grants are explicitly listed in the provided materials, his extensive publication record reflects significant academic impact. He advises on graduate research in rheology and colloids but no specific student names are mentioned. Pal's work often emphasizes practical applications of fundamental fluid mechanics principles, with a focus on energy-efficient systems and nanotechnology-driven solutions.

Norman J. Wagnerمشاهده پروفایل

استاد

• Rheology of Complex Fluids
• Neutron Scattering
• Colloid Science
• +۵ مورد دیگر

Norman J. Wagner holds the Unidel Robert L. Pigford Chair in Chemical & Biomolecular Engineering at the University of Delaware, with affiliations in Physics & Astronomy, Biomedical Engineering, and Biomechanics & Movement Science. He directs the Center for Neutron Science (CNS) and served as CBE Department Chair (2007–2012). His research focuses on rheology of complex fluids, colloids, polymers, and nanotechnology, with applications to space materials and biomedical systems. Education: B.S. from Carnegie Mellon (1984), Ph.D. in Chemical Engineering from Princeton (1988). Postdoctoral fellowships at Los Alamos National Lab and the University of Stuttgart (Germany). Visiting professorships at ETH Zurich (1997) and University of Rome (2004). Research spans shear thickening fluids, neutron scattering, and protein formulation stability. Key contributions include commercializing STF-based body armor and developing novel rheological instruments. Over 200 publications and patents highlight his work in soft matter physics and materials science. Notable awards: National Academy of Engineering membership (2015), Bingham Medal (2014), Siple Award (2002). Editorial roles include AIChE Journal (Soft Matter Section) and multiple international journals. Active in neutron science leadership, including Neutron Scattering Society of America. Labs/Teams: Center for Neutron Science, STF Technologies LLC (co-founded 2003). Current projects include lunar exploration materials, geopolymer cements, and biomedical fluid dynamics.

Thomas Franoschمشاهده پروفایل

استاد

• Transport in crowded and disordered media
• Time-dependent nonlinear response
• Active and non-equilibrium systems
• +۳ مورد دیگر

Prof. Dr. Thomas Franosch is a Full Professor of Theoretical Physics at the Universität Innsbruck, Department of Theoretical Physics. His research focuses on transport phenomena in complex systems, including crowded and disordered media, active matter, non-equilibrium systems, and the glass transition. He leads the Bio and Nano Physics research group and has held academic positions at institutions such as Friedrich-Alexander-Universität Erlangen-Nürnberg and Ludwig-Maximilians Universität München. His career includes a PhD from TU München (1996) and postdoctoral research at Harvard University (1998-2000). He has contributed extensively to understanding dynamics in confined colloidal systems, mode-coupling theories for glass transitions, and active particle dynamics. His work bridges theoretical frameworks with applications in soft matter and biophysics. Research interests emphasize time-dependent nonlinear response, anomalous transport, and the interplay between geometry and dynamics in confined environments. Recent publications explore light-induced caging effects in colloids, Anderson localization in fluctuating media, and stochastic dynamics of active particles. Publications span over two decades, with a focus on theoretical models explaining complex fluid behavior. Notable contributions include studies on confined hard-sphere fluids, Lorentz gas models, and active matter systems. His work frequently employs advanced simulation techniques and mode-coupling theory to analyze non-equilibrium phenomena.

Qingbing Xiaمشاهده پروفایل

پژوهشگر ارشد

• Energy Storage
• Materials Science
• Electrochemistry
• +۳ مورد دیگر

Dr. Qingbing Xia is a Postdoctoral Research Fellow at the School of Mechanical and Mining Engineering , The University of Queensland , with over 11 years of research experience in electrode materials for lithium/sodium-ion batteries. He received his B.Sc. and M.Sc. in Materials Science and Engineering from Central South University (China) in 2012 and 2015, followed by a Ph.D. in Materials Engineering (Energy Materials specialization) from University of Wollongong (Australia) in 2019. Current research themes: Low-cost electrode materials for high-energy-density batteries In situ/operando techniques for battery interface studies Solid polymer electrolytes and solid-state metal batteries His work has produced 48 publications (47 journal articles + 1 book chapter) focusing on energy materials, with specific contributions to: Sub/nanoscale surface engineering of electrodes 2D superlattice synthesis via molecularly mediated thermal approaches Sheet-in-sphere nanostructure design for 2D material stabilization Advanced in situ X-ray diffraction studies of ion storage mechanisms Research grants from Australian Nuclear Science and Technology Organisation (2013–2025) supported his work on battery materials. He serves as Associate Advisor for multiple Ph.D. projects in electrochemical energy systems and solid-state batteries.

Brian B. Lairdمشاهده پروفایل

استاد

• Theoretical Chemistry
• Computational Chemistry
• Statistical Mechanics
• +۵ مورد دیگر

Brian B. Laird is Professor and Department Chair of Chemistry at the University of Kansas. He earned dual B.S. degrees in Chemistry and Mathematics from the University of Texas at Austin (1982) and a Ph.D. in Theoretical Chemistry from UC Berkeley (1987). His career includes postdoctoral positions at Columbia University, Forschungszentrum Jülich (NATO Fellowship), University of Utah, University of Sydney, and University of Wisconsin, with visiting appointments at the University of Mainz, University of Leicester, and UC Davis. Research focuses on applying statistical mechanics and molecular simulation to materials science, with three primary areas: (1) structure and thermodynamics of condensed-phase interfaces, (2) phase coexistence under nanoscale confinement, and (3) advanced molecular dynamics algorithms. His publications demonstrate strong emphasis on surface thermodynamics, nanomaterial interactions, and ecological applications of computational methods. Honors include the NSF CAREER Award. Professor Laird directs an active research group mentoring 19+ graduate students/postdocs. The Laird Lab frequently collaborates internationally with institutions in China, Germany, and the UK.

MP Gururajanمشاهده پروفایل

استاد

• Computational Materials Science
• Microstructural Evolution Modeling
• Phase Field Modeling
• +۶ مورد دیگر

MP Gururajan is a Professor in the Department of Metallurgical Engineering and Materials Science at the Indian Institute of Technology Bombay (IIT Bombay), where he has been serving since May 2021. He previously held the positions of Associate Professor (2016–2021) and Assistant Professor (2009–2016), indicating a long-standing and active academic career at IIT Bombay. B.Sc (Physics), Madras University, 1994 M.Sc (Materials Science), Anna University, Madras, 1996 M.Sc. (by research), Indian Institute of Science, Bangalore, 1999 Ph.D., Indian Institute of Science, Bangalore, 2006 His research focuses on computational modeling of microstructural evolution, employing both atomistic (Monte Carlo, molecular dynamics) and continuum (phase field modeling) approaches. Key areas include phase transformations, deformation mechanisms, materials mechanics, and thermodynamics. His work bridges theoretical modeling with experimental validation in metallic systems. The selected publications reflect a consistent focus on phase field modeling, interfacial phenomena, and microstructure evolution under various thermomechanical conditions. Topics such as precipitate growth, grain boundary grooving, strain effects, and anisotropy are recurrent, demonstrating deep expertise in multiscale materials simulation. No scientific awards or fellowships are mentioned in the provided text. Prof. Gururajan leads an active research group (CMEGAT IITB) and has secured funding from national agencies including the Department of Science and Technology (DST), Defence Research and Development Organisation (DRDO-SASE), and industrial partners like Tata Steel and GE. Collaborative IMPRINT projects with TCS and GE Global Research highlight his engagement in indigenous software development and life prediction methodologies for advanced alloys. He maintains a research group website and is involved in both teaching and research supervision at IIT Bombay. His lab focuses on computational materials engineering, with emphasis on predictive modeling of microstructure and mechanical behavior.

• Geometric Modeling
• Topological Analysis
• Soft Matter Physics
• +۲ مورد دیگر

Prof. Dr. Myfanwy Evans is a Professor of Applied Geometry and Topology at the University of Potsdam . Her research focuses on geometric and topological modeling of soft and biological systems, with emphasis on analyzing complex microstructures through experimental and theoretical approaches. She is affiliated with the Institute of Mathematics, leading projects in geometric constraints in biological and synthetic materials. Current Position: Professor, University of Potsdam (2020–present) Previous Roles: Emmy Noether Research Group Leader (2015–2020), Humboldt Postdoctoral Fellow (2011–2014) Research Highlights: Evans investigates topological potentials in protein assembly, curvature in biological systems, and geometric optimization in tensegrity frameworks. Her work spans 3-periodic entanglements, network theory, and bicontinuous structures. Funding & Collaborations: Participates in Matters of Activity and MATH+ excellence clusters, collaborating across Berlin universities and Germany. She contributes to research on discretization in geometry and dynamical systems. Software Development: Co-created SPIRE , a tool for bicontinuous phase recognition applied to plastid cubic membranes and biological structures. Technical Expertise: Utilizes Riemannian optimization for geometric modeling, explores auxetic materials, and studies foam coarsening dynamics.

Jan Kierfeldمشاهده پروفایل

استاد

• Soft Matter Physics
• Biological Physics
• Statistical Physics
• +۱۲ مورد دیگر

Prof. Dr. Jan Kierfeld is a faculty member in the Department of Physics at Technical University of Dortmund, where he leads a research group focused on soft matter theory and biological physics. His work bridges statistical physics, mechanics, and hydrodynamics of soft and biological systems, with strong interdisciplinary connections to materials science and biophysics. His research interests include polymer physics , cytoskeletal filaments (actin and microtubules), elastic capsules and shells , active matter , and the development of novel simulation techniques such as event-chain Monte Carlo. He is particularly interested in how chemical energy (e.g., ATP/GTP hydrolysis) drives mechanical forces in biological systems, and in the mechanics of semiflexible polymer networks and microswimmers. His group also pioneers the application of machine learning to problems in soft matter, such as pendant drop tensiometry and traction force microscopy. The recent publications of Prof. Kierfeld span topics in biophysics, soft matter, and computational physics, showing a strong trend toward integrating theoretical modeling with experimental collaboration, especially in microswimmer dynamics, microtubule mechanics, and interfacial phenomena. His work frequently appears in journals such as Soft Matter , Physical Review , Biophysical Journal , and Nature Communications . He has no listed scientific awards in the provided text, but his active publication record and leadership in DFG programs (e.g., SPP1726 Microswimmers) indicate significant recognition in the field. He advises students and postdoctoral researchers in theoretical and computational soft matter physics, though specific names are not listed. His research is supported by grants from German funding agencies such as the DFG. Prof. Kierfeld’s group develops and applies advanced simulation methods and collaborates with experimentalists on problems involving elastic instabilities (buckling, wrinkling), microswimmers , and chemomechanical models of cellular structures. The group maintains strong technical development in numerical algorithms and data analysis tools, including open-source software like MLFTM for traction force microscopy.

Samantha Pettiمشاهده پروفایل

استادیار

• Bioinformatics
• Computational Biology
• Machine Learning
• +۴ مورد دیگر

Samantha Petti is an Assistant Professor in both the Department of Mathematics (School of Arts and Sciences) and the Department of Computer Science (School of Engineering) at Tufts University. She is based at 177 College Avenue, Medford, MA. Her research focuses on computational biology, bioinformatics, and machine learning, with particular emphasis on protein structure analysis, genotype-phenotype mapping, and algorithm design for biological sequence analysis. She teaches courses such as Master's Thesis supervision, PhD Thesis guidance, and specialized topics in mathematics and computer science. Her work integrates interdisciplinary approaches, combining statistical methods, deep learning, and probabilistic models to address challenges in genomics, structural biology, and network science. Recent projects include developing end-to-end protein alignment tools and exploring sparse graph models for biological systems. Teaching: Supervises graduate thesis work (Master’s/PhD) and advanced courses in mathematics and computer science at Tufts. Lab/Team: Engages in collaborative research at the intersection of computational methods and biological systems.

Vincent E. Debetsمشاهده پروفایل

پژوهشگر

• Soft Matter Physics
• Machine Learning
• Non-Equilibrium Physics
• +۳ مورد دیگر

Vincent E. Debets is a Researcher at the Applied Physics and Science Education department of Eindhoven University of Technology, specializing in Non-Equilibrium Soft Matter . His work bridges physics and computational methods to study complex material behaviors. Education : Master's thesis on Collective Cell Dynamics in Cancer Metastasis (2019), supervised by Dr. C. Storm and Dr. L. M. C. Janssen. Research Interests : Debets focuses on soft matter systems near non-equilibrium states, utilizing machine learning and deep learning to analyze glassy dynamics , active matter , and memory effects in materials. His recent studies examine structural properties of amorphous systems and correlation functions in dense active fluids. Article Trends : His publications emphasize computational approaches (machine learning, deep learning) to model non-equilibrium phenomena in soft matter, particularly glassy and active systems. Topics include structural aging, particle classification, and chiral fluid dynamics, with applications in materials science and biophysics. Collaborations : Works with international researchers like Dr. L. M. C. Janssen (Eindhoven), Prof. H. Löwen (Bochum), and Dr. T. Voigtmann (Aachen). Frequent media engagement on topics like 'glassy materials' and 'cancer cell modeling'. Labs/Teams : Affiliated with the Non-Equilibrium Soft Matter group at Eindhoven University of Technology, contributing to cross-disciplinary research in physics and biomedical applications.