جست‌وجوی استاد و پژوهشگر

• Uncertainty Quantification
• Non-equilibrium Plasmas
• Hypersonics
• +۳ مورد دیگر

Marco Panesi is a Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign and Director of the Center for Hypersonics and Entry Systems Studies (CHESS). His research focuses on non-equilibrium phenomena in high-enthalpy flows, plasma dynamics, and uncertainty quantification. He holds a Ph.D. from the von Kármán Institute for Fluid Dynamics (2009) and M.S. degrees from Università di Pisa (2003) and VKI (2005). Roles: Faculty Member, Research Director, Principal Investigator Key Affiliations: CHESS, University of Illinois, VKI Research Interests: Hypersonic flow modeling, non-equilibrium plasmas, radiation effects, machine learning applications in aerothermodynamics, ablation processes, and state-to-state chemistry. His work bridges computational fluid dynamics with experimental validation in facilities like the Plasmatron X wind tunnel. Publications: Over 100 peer-reviewed articles on topics ranging from plasma kinetics to thermal protection systems. Recent work emphasizes adaptive neural operator models and Bayesian uncertainty quantification. Awards: Includes the Vannevar Bush Faculty Fellowship (2021), NASA Groundbreaker Award (2021), and multiple early-career recognitions from AFOSR, NASA, and ESA. Grants & Leadership: Secured funding from NSF, NASA, and DOD. Leads multidisciplinary teams on projects like the CHyPS material response solver and hypersonic entry modeling. Labs & Facilities: Principal investigator for the UIUC Plasmatron X facility, a key resource for studying high-enthalpy plasma flows.

Michael Haganمشاهده پروفایل

استاد

• Biophysics
• Soft Condensed Matter
• Active Matter
• +۴ مورد دیگر

Michael Hagan is a Professor of Physics at Brandeis University, affiliated with the Martin A. Fisher School of Physics. His research focuses on understanding the physical principles governing assembly and dynamic organization in biological and biomimetic systems. He employs computational and theoretical methods, including machine learning, to study viral capsid assembly, bacterial microcompartments, and active matter systems. His work bridges length and time scales to elucidate emergent behaviors in nonequilibrium systems. Education: PhD in Physics from the University of California, Berkeley (2003). His group, the Hagan Lab, collaborates with experimentalists and has received funding from the DOE, NSF, Keck Foundation, and NIH. Key areas include viral genome assembly optimization, bacterial microcompartment formation, and the dynamics of active nematics. Recent studies explore defect-ordered phases, phase separation in active colloids, and programmable self-assembly of geometric structures. Research interests span biophysics, soft condensed matter, and computational modeling. His lab's work has implications for synthetic biology, drug design, and material science. Collaborations with experimental groups (e.g., Z. Dogic's lab) have led to discoveries in active matter dynamics and biomimetic systems.

Stephen Pankavichمشاهده پروفایل

استاد

• Partial Differential Equations
• Kinetic Theory
• Mathematical Biology
• +۴ مورد دیگر

Stephen Pankavich is a Professor and Department Head in the Department of Applied Mathematics and Statistics at the Colorado School of Mines. He holds a PhD in Mathematical Sciences from Carnegie Mellon University, with research focused on partial differential equations, kinetic theory, and mathematical biology. His work bridges theoretical analysis and computational methods, addressing challenges in plasma dynamics, epidemiological modeling, and multiscale systems. Education: PhD, Mathematical Sciences, Carnegie Mellon University (2005) MS, Mathematical Sciences, Carnegie Mellon University (2001) BS, Mathematical Sciences, Carnegie Mellon University (2000) Research interests include the analytical and numerical study of collisionless plasmas, HIV dynamics, and epidemiological models. He has received awards such as the W.M. Keck Mentorship Award and the Colorado School of Mines Alumni Teaching Award. His articles explore topics like plasma decay rates, HIV therapy models, and particle-tracking algorithms. He has advised over 20 graduate and undergraduate students, contributing to impactful research in applied mathematics and computational science.

Jonathan Doyeمشاهده پروفایل

استاد

• DNA Biophysics
• DNA Nanotechnology
• Liquid Crystals
• +۶ مورد دیگر

Jonathan Doye is a Professor of Theoretical Chemistry at the University of Oxford, affiliated with Queens College. He holds positions in the Department of Chemistry and collaborates with the Brandeis Bioinspired Soft Materials MRSEC. His research focuses on theoretical and computational studies of soft matter and biomolecular systems, including DNA biophysics, DNA nanotechnology, liquid crystals, and quasicrystals. He co-developed the oxDNA coarse-grained model for DNA simulations, widely used in nanotechnology research. Education: Bachelor’s and PhD in Theoretical Chemistry from the University of Cambridge Postdoctoral research at FOM Institute in Amsterdam (1996–1998) Research Interests: Coarse-grained modeling of DNA and RNA Patchy-particle self-assembly (including quasicrystals) Prokaryotic S-layer structural analysis Liquid crystal phase behavior of DNA origami rods Key Achievements: Discovery of one-component icosahedral quasicrystals via patchy particles Development of oxDNA model for DNA origami simulations Structural elucidation of S-layers across prokaryotes Awards: Royal Society of Chemistry Harrison Memorial Prize (2000) Labs/Teams: Jonathan Doye's Research Group focuses on computational studies of soft matter systems, with experimental collaborations in DNA nanotechnology and materials science.

Celia Reinaمشاهده پروفایل

دانشیار

• Materials Science
• Computational Mechanics
• Non-equilibrium Thermodynamics
• +۳ مورد دیگر

Celia Reina is an Associate Professor in the Department of Mechanical Engineering and Applied Mechanics at the University of Pennsylvania’s School of Engineering and Applied Science (SEAS). Her research focuses on multiscale modeling of materials, bridging statistical mechanics, thermodynamics, and machine learning. She develops novel frameworks for predicting non-equilibrium material behavior using data-driven methods and uncertainty quantification. Her work emphasizes integrating computational tools like neural networks (Stat-PINNs, VONNs) with physical principles to model dissipative systems, phase transitions, and mesoscale dynamics. Key areas include coarse-graining techniques, epistemic uncertainty analysis, and predictive modeling of complex materials under dynamic loading. Recent publications highlight advancements in stochastic systems, resonant metamaterials, and the derivation of thermodynamic models from particle-level fluctuations. She leads efforts in experimental-simulation co-design to enhance predictive capabilities in materials science.

• Fluvial Geomorphology
• Sediment Transport
• Gravel-bed Rivers
• +۶ مورد دیگر

Professor Rebecca Hodge is a Professor in the Department of Geography at Durham University, where she has served since 2011 after progressing from Lecturer (2011-2016) to Associate Professor (2016-2022). Her academic foundation includes a PhD in Geography from the University of Cambridge (2007) and prior postdoctoral work at the University of Glasgow (2007-2011). Her educational background: PhD, Geography, University of Cambridge (2007) Professor Hodge's research centers on fluvial geomorphology , specializing in sediment transport mechanics within gravel-bed and bedrock-alluvial river systems. She pioneers the integration of high-resolution measurement techniques —including Terrestrial Laser Scanning, CT scanning, and 3D printing—with advanced numerical modeling (e.g., Cellular Automaton frameworks) to investigate how grain-scale interactions govern reach-scale sediment flux. Her work critically examines sediment cover dynamics, critical shear stress thresholds, and the upscaling of small-scale processes in river morphology. Analysis of her 15 most recent publications (2019-2025) reveals a dominant focus on quantifying river bed roughness , sediment cover dynamics , and innovative measurement methodologies . Key trends include the application of 3D point cloud analysis for critical shear stress estimation, acoustic monitoring of river systems, and network-scale modeling of alluvial processes across diverse environments from Antarctic ice shelves to U.S. bedrock rivers. Her significant recognition includes: Gordon Warwick Medal from the British Society for Geomorphology (2022) for excellence in geomorphological research within 15 years of her doctorate Professor Hodge actively mentors PhD candidates including Holly Wytiahlowsky, Jiao Chen, and Mel Oliveira Guirro, with research spanning Antarctic glacial channels, bedrock-alluvial transitions, and gravel-bed river mechanics. Her collaborative projects involve institutions across the UK, USA, and Brazil, addressing fundamental questions in sediment transport and river response to environmental change. Her laboratory work emphasizes experimental flume studies and field deployments of cutting-edge sensors, directly informing theoretical models of river evolution and sediment dynamics.

Huan Leiمشاهده پروفایل

استادیار

• Computational Mathematics
• Numerical Analysis
• Scientific Machine Learning
• +۴ مورد دیگر

Huan Lei is an Assistant Professor at Michigan State University, holding a joint appointment in the Department of Computational Mathematics, Science and Engineering and the Department of Statistics and Probability. He earned his Ph.D. in Applied Mathematics from Brown University in 2012 under George Karniadakis and a B.S. in Special Class for the Gifted Young from the University of Science & Technology of China in 2005. His research integrates scientific machine learning with numerical analysis to develop structure-preserving algorithms for partial and stochastic differential equations arising in multi-scale systems. His work spans multi-scale modeling , non-Markovian dynamics , coarse-grained molecular simulations , and data-driven parameterization . Recent publications focus on learning generalized Langevin equations with state-dependent memory, consensus-based free energy surfaces, and non-equilibrium coarse-grained models. His team applies these methods to fluid dynamics, biomolecular solvation, and climate systems. NSF CAREER Award (2021) Brown University Dissertation Fellowship (2012) He advises graduate and undergraduate researchers and seeks Ph.D. candidates with expertise in numerical analysis or scientific computing. His group receives funding from NSF, DOE, Ford, and MSU Foundation.

• Quantum Thermodynamics
• Stochastic Thermodynamics
• Open Quantum Systems
• +۵ مورد دیگر

Gonzalo Manzano Paule is a Ramón y Cajal tenure-track researcher at IFISC (Instituto de Física Interdisciplinar y Sistemas Complejos), a joint research institute of CSIC (Consejo Superior de Investigaciones Científicas) and UIB (University of the Balearic Islands), where he has been working since January 2023. He previously held a Juan de la Cierva Incorporation fellowship (2021-2023), was an ESQ Postdoc at IQOQI Vienna (2020-2021), and a Postdoc at ICTP Trieste (2018-2020) funded by Scuola Normale Superiore. He obtained his PhD in Physics from Universidad Complutense de Madrid in July 2017, followed by a short Postdoc at IFISC (2017-2018). His research interests focus on quantum and stochastic thermodynamics, open quantum systems, information theory, and the foundations of nonequilibrium statistical physics and quantum mechanics. He is particularly interested in applying concepts from nonequilibrium thermodynamics to understand classical and quantum complex systems. While his work is primarily theoretical, he actively seeks collaborations with experimentalists. His research has been featured in popular science journals including Physics, Quanta Magazine, and Diario de Mallorca. He has also collaborated with artist Evarist Torres to merge art and science and has written a popular science article for Investigación y Ciencia (Scientific American). Manzano Paule's recent publications demonstrate a strong focus on quantum thermodynamics, fluctuation theorems, and quantum information processing. His work spans theoretical foundations of quantum thermodynamics to applications in quantum heat engines and molecular motors. A notable pattern in his research is the exploration of how quantum effects can enhance thermodynamic processes and the relationship between information theory and thermodynamics. His scientific achievements have been recognized through prestigious fellowships including the Ramón y Cajal program, Juan de la Cierva Incorporation fellowship, and ESQ Postdoc fellowship. His work has also garnered attention in popular science media, indicating its broader impact beyond academic circles. As an educator, Manzano Paule supervises Master's students and teaches advanced courses including Open Quantum Systems for the Master's Degree in Advanced Physics and Applied Mathematics and the Master's Degree in Physics of Complex Systems. His teaching portfolio also includes Quantum Collective Phenomena, Quantum and Nonlinear Optics, Thermodynamics, and Atomic and Molecular Physics. He currently leads the research project 'QTD-InFlexity Quantum thermodynamics: information, fluctuations and complexity' and participates in the 'CoQuSy Complex Quantum Systems' project. He is also part of the María de Maeztu Unit of Excellence at IFISC, which has received continuous funding since 2008.

Stefan Klusمشاهده پروفایل

مدرس

• Data-driven model reduction
• Transfer operator approximation
• Machine learning
• +۸ مورد دیگر

Dr. Stefan Klus is a Lecturer at the School of Mathematics and Physics, University of Surrey. His research focuses on data-driven model reduction, transfer operator approximation, and kernel-based machine learning applied to dynamical systems. He specializes in interdisciplinary applications across quantum physics, fluid dynamics, and computational biology. Education: PhD in Industrial Mathematics (2011, Paderborn University) and Habilitation (2020, Freie Universität Berlin). Research Interests : Data-driven modeling and reduced-order methods Koopman operator theory and transfer operators Machine learning for dynamical systems (e.g., Deeptime library) Tensor decompositions and quantum systems analysis Graph-based analysis (e.g., microbiome dynamics) Publications : Klus has contributed to over 50 peer-reviewed articles, with recent work emphasizing: Kernel methods for quantum chemistry and physics Tensor-based approaches for high-dimensional systems Applications in climate science (e.g., Pacific SST modeling) Agent-based modeling and social systems Technical Contributions : Co-developer of the Deeptime Python library for dynamical modeling Pioneer in Koopman operator-based model reduction Advanced graph kernel methods for microbiome analysis

Jim W Evansمشاهده پروفایل

استاد

• Non-Equilibrium Statistical Physics
• Multi-Scale Modeling
• Nanoscience
• +۶ مورد دیگر

Jim W Evans is a Professor of Physics & Astronomy and Mathematics at Iowa State University, and a Faculty Scientist at the Ames Laboratory (USDOE). His research focuses on non-equilibrium statistical physics and multi-scale modeling of nanoscale systems, including metallic nanoclusters, epitaxial thin films, catalytic surface reactions, and nanoporous materials. Evans holds a B.Sc. (Hons) in Mathematics from the University of Melbourne (1975) and a Ph.D. in Mathematical Physics from the University of Adelaide (1979). He has authored over 360 publications and maintains editorial roles at journals like Nanomaterials and Surface Science . His research interests span: Stability and dynamics of metallic nanocrystals Coarsening mechanisms in epitaxial films Reaction-diffusion systems and non-equilibrium phase transitions Interfacial catalysis and nanoporous transport phenomena Recent work includes: Real-time KMC simulations of nanocrystal intermixing Thermodynamic modeling of intercalated metal systems Statistical mechanics of surface dynamics Honors include APS Fellowship (2002), APS Outstanding Referee (2015), and an h-index of 58 (Google Scholar). He leads DOE-funded projects on exascale software for catalysis modeling and intercalation chemistry in layered materials.

Chandrika Sadanandمشاهده پروفایل

استادیار

• Low Dimensional Topology
• Geometry
• Hyperbolic Geometry
• +۳ مورد دیگر

Chandrika Sadanand is an Assistant Professor in the Department of Mathematics at Bowdoin College. She holds a PhD from Stony Brook University and a BS from the University of Toronto. Her research focuses on low-dimensional topology and geometry, specifically exploring curves on surfaces, hyperbolic geometry, billiards, translation surfaces, and 3-manifolds. She has held postdoctoral positions at the University of Illinois Urbana Champaign, Technion, and Hebrew University of Jerusalem. Dr. Sadanand teaches courses in mathematical reasoning, geometry, and topology. Her recent courses include MATH 2020 (Introduction to Mathematical Reasoning), MATH 2404 (Geometry), and MATH 3402 (Topology). She has also mentored undergraduate research projects on flat surfaces and participated in outreach activities through programs like the Stony Brook Math Summer Camp and WISE. Her research contributions include studies on translation surfaces of infinite type, billiards dynamics, and geometric structures. She has contributed to innovative conferences like the Nearly Carbon Neutral Geometry and Topology Conferences through video presentations. Her work bridges pure mathematics with computational methods, addressing questions in geometric topology and dynamical systems.

Rainer Böckmannمشاهده پروفایل

استاد

• Computational Biology
• Theoretical Biophysics
• Membrane Biophysics
• +۷ مورد دیگر

Rainer Böckmann is a Professor of Computational Biology in the Department of Biology at Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Germany, where he leads the Group for Theoretical and Computational Membrane Biophysics. His research integrates molecular dynamics simulations with biophysical analysis to study membrane structure, dynamics, and function. Research Interests: His work focuses on computational biophysics, particularly lipid bilayers, membrane proteins, molecular dynamics, and structural bioinformatics. He investigates how lipid composition, cholesterol, and embedded peptides influence membrane organization, curvature, and permeability, with applications in antimicrobial strategies and mRNA vaccine delivery systems. Recent Research Trends: His recent publications reflect a strong emphasis on lipid nanoparticles (LNPs), particularly their phase behavior, pH-dependent protonation, and structural transitions relevant to mRNA vaccines. He also explores antimicrobial peptides, membrane domain formation, and the role of cholesterol in modulating membrane properties. His group develops and applies advanced simulation techniques, including constant-pH MD and coarse-grained modeling. Member of Editorial Board, Biophysical Journal (2024–present) Elected Member, DFG Review Board for Biophysics (2020–present) Chairman, Molecular Biophysics Section, German Biophysical Society (2011–2012) Leadership and Service: Böckmann is actively involved in academic governance, serving on editorial boards, DFG committees, and as a guest editor for special issues in Frontiers journals. He contributes to graduate education and high-performance computing initiatives at FAU, including the NHR@FAU and Life@FAU Graduate School. He has organized major conferences and workshops in biophysics and membrane modeling. Laboratory and Collaboration: He leads a research group focused on biomembrane physics, collaborating with experimentalists and theorists. His lab develops and applies simulation tools to study membrane systems, bridging computational insights with biological function.

Jorge Viñalsمشاهده پروفایل

استاد

• Soft Matter Physics
• Materials Science
• Biomechanics
• +۵ مورد دیگر

Jorge Viñals is a Professor at the School of Physics and Astronomy , University of Minnesota, and Director of Graduate Studies. His research focuses on theoretical and computational studies of nonequilibrium phenomena in extended systems, with applications to Soft Matter Physics, Materials Science, and Biomechanics. Affiliation: Director of Graduate Studies, School of Physics and Astronomy Institution: University of Minnesota Collaborations: Minnesota Supercomputing Institute, University of Oslo, Cornell, Carnegie Mellon His work examines mesoscale theories of systems outside thermodynamic equilibrium, particularly unstable interfaces and moving topological defects. Current projects include studies of chiral symmetry breaking in nematic liquid crystals, field dislocation mechanics in defected solids, and biomechanics of epithelial tissue with orientational order. Recent publications highlight computational approaches to nematic defect structure , topological charge quantification , and plasticity modeling . Key journals include Soft Matter , Proceedings of the Royal Society A , and Physical Review B . Key collaborators: Lucas Myers, C.D. Schimming, Luiza Angheluta, Manas Upadhyay Grants: NSF-funded projects on active matter and liquid crystal dynamics, Department of Defense research on intraosseous catheters

Alex Mironenkoمشاهده پروفایل

استادیار

• Catalysis
• Computational Chemistry
• Quantum Mechanics
• +۷ مورد دیگر

Dr. Alex Mironenko is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. His research focuses on developing quantum mechanical methods to predict catalytic behaviors for renewable energy and chemical production. He leads the Mironenko Lab, which emphasizes computational models for heterogeneous catalysis, reactive force fields, and nanozyme design. Education: PhD in Chemical Engineering, University of Delaware (2018) Kadanoff-Rice Postdoctoral Scholar, University of Chicago (2018-2020) MS in Chemical Engineering, University of Kansas (2012) Diploma of Engineer, Omsk F.M. Dostoevsky State University, Russia (2009) Research Interests: Computational heterogeneous catalysis Reactive force fields derived from first principles Low-dimensional metal oxide catalysts Nanozymes and biomimetic catalysis Selective C-C coupling for CO₂ valorization Improving density functional theory accuracy Awards: ACS Petroleum Research Fund Doctoral Investigator Award (2021) Allan P. Colburn Outstanding Dissertation Prize (2019) Kadanoff-Rice Postdoctoral Fellowship (2018-2020) Advising and Grants: Advised PhD student Neil Tran (publication on methanol carbonylation mechanisms) Funded by NSF, ACS, and industry partnerships Labs/Teams: Mironenko Virtual Catalysis and Quantum Chemistry Lab Collaborations with institutions like University of Chicago and industry partners

Udo Seifertمشاهده پروفایل

استاد

• Stochastic Thermodynamics
• Non-equilibrium Statistical Mechanics
• Biophysics
• +۳ مورد دیگر

Udo Seifert is a Professor in the II. Institute for Theoretical Physics at the University of Stuttgart, part of Faculty 08. His research focuses on stochastic thermodynamics, non-equilibrium statistical mechanics, and entropy production in complex systems. He has contributed significantly to understanding Markov networks, thermodynamic inference, and the interplay between fluctuations and irreversibility. His work bridges theoretical frameworks with experimental techniques, such as single-molecule experiments and motor-bead assays. Key areas of interest include entropy estimation in partially accessible systems, localization of entropy production, and the development of model-free entropy estimators. His recent studies explore the thermodynamic uncertainty relation, active matter systems, and the dynamics of biochemical oscillators. He has published extensively on topics like nonequilibrium fluctuations in chemical reaction networks, driven systems, and the application of stochastic processes to biophysical systems. Seifert's research also extends to membrane mechanics, with studies on fluid vesicle shapes and membrane-mediated interactions. His work emphasizes the integration of theoretical models with experimental data, aiming to uncover fundamental principles governing non-equilibrium phenomena. Despite the absence of listed awards or students in the provided text, his prolific publication record underscores his influential role in advancing stochastic thermodynamics and related fields.