جست‌وجوی استاد و پژوهشگر

Michael W. Jenkinsمشاهده پروفایل

استاد

• Biomedical Engineering
• Medical Imaging
• Cardiac Imaging
• +۳ مورد دیگر

Michael W. Jenkins is a Professor of Biomedical Engineering at the Case Western Reserve University School of Medicine and a member of the Cancer Imaging Program at the Case Comprehensive Cancer Center. His research focuses on developing biomedical optics tools for studying congenital heart disease and peripheral nervous system disorders. Key techniques include optical coherence tomography (OCT), light-sheet microscopy, and infrared neuromodulation. The Jenkins Lab specializes in advancing 3D imaging modalities for real-time tissue analysis, aiming to reduce surgical delays and improve diagnostic accuracy. Research interests include rapid 3D tissue visualization to replace traditional frozen-section pathology, optical pacing of cardiac tissues, and corneal nerve imaging. His work bridges engineering and medicine, with applications in ophthalmology, cardiology, and neurology. Recent innovations include label-free microscopy techniques (e.g., MUSE imaging) and AI-driven segmentation tools for neural anatomy analysis. Publications highlight advancements in corneal crosslinking assessment, vagus nerve microanatomy characterization, and cardiac tissue imaging. The lab collaborates with industry to translate optical tools into clinical settings, emphasizing precision and real-time diagnostics. Teaching and mentorship are integral to his role, fostering interdisciplinary training in biomedical optics. Ongoing projects address unmet clinical needs in neural modulation therapies and regenerative medicine through optical platforms.

Alexander Mironenkoمشاهده پروفایل

استادیار

• Computational Catalysis
• Quantum Chemistry
• Heterogeneous Catalysis
• +۳ مورد دیگر

Dr. Alexander Mironenko is an Assistant Professor of Chemical & Biomolecular Engineering and Faculty Affiliate in Chemistry at the University of Illinois at Urbana-Champaign. His research focuses on computational catalysis and quantum chemistry, with a long-term goal of designing catalytic sites for sustainable chemical processes. He leads the Mironenko Virtual Catalysis and Quantum Chemistry Lab, which develops quantum mechanical methods to study heterogeneous catalyst mechanisms and materials. His work emphasizes catalyst stability, activity, and environmental impact. Research Interests include computational modeling of catalytic systems, electronic structure analysis, and reaction mechanisms for sustainable energy applications. Key projects involve studying ReOx/SiO2 catalysts for methanol carbonylation, MoC electrocatalysts, and planar chiral metallopolymers for enantioselective separations. The lab’s multiscale approaches bridge quantum mechanics and coarse-grained simulations for practical catalyst design. Recent achievements include a 2025 study on surface oxygen effects in α-MoC catalysts and a 2024 breakthrough on methanol carbonylation mechanisms. Collaborations with ACS Petroleum Research Fund and academic partners highlight his interdisciplinary impact. Advising Neil Tran (PhD student) and mentoring graduate teaching assistant Banhee reflect his commitment to student development. The lab’s cultural activities, like karaoke nights, foster teamwork alongside scientific rigor. Publications span ACS Catalysis, JACS, and Reaction Chemistry & Engineering, with over 40 articles advancing computational catalysis. Ongoing work explores data-driven and physics-based methods for catalyst discovery, aiming to address global energy and sustainability challenges.

• Light Sheet Microscopy
• Biomedical Imaging
• Developmental Biology
• +۴ مورد دیگر

Jan Huisken is a Humboldt Professor for Multiscale Biology at the Georg-August-Universität Göttingen, affiliated with the Johann Friedrich Blumenbach Institute of Zoology and Anthropology. His research focuses on advanced light sheet microscopy techniques for biomedical and developmental biology applications. Role: Humboldt Professor University: Georg-August-Universität Göttingen Department: Johann Friedrich Blumenbach Institute of Zoology and Anthropology Research interests include light sheet microscopy , biomedical imaging , and developmental biology with a strong emphasis on zebrafish models. He develops tools for tissue clearing , image processing , and 3D microscopy . The 15 most recent publications analyze innovations in light sheet microscopy, tissue clearing protocols, and computational methods for image restoration. These works span fields such as optical imaging , developmental cardiology , computational biology , and biomedical instrumentation . Huisken contributes to open-source microscopy systems like 'Flamingo' and 'BigFUSE,' aiming to democratize access to advanced imaging technologies. His work integrates engineering, computer science, and biology to solve complex imaging challenges.

Peter Sollichمشاهده پروفایل

استاد

• Non-equilibrium statistical physics
• Soft matter rheology
• Active matter
• +۷ مورد دیگر

Prof. Dr. Peter Sollich is a Professor of Theoretical Physics at Georg-August-Universität Göttingen, affiliated with the Institute for Theoretical Physics. His research spans non-equilibrium statistical physics with applications to soft matter, active systems, and complex networks. He maintains a small part-time appointment at King's College London. His primary research interests focus on non-equilibrium statistical physics , particularly soft and active matter rheology, jamming transitions, glassy dynamics, dynamical phase transitions, and inference from dynamical data. His work bridges theoretical physics with applications in materials science and network theory, emphasizing both fundamental mechanisms and quantitative modeling approaches. Analysis of his recent publications reveals strong thematic consistency in studying glassy dynamics and active matter systems , with increasing integration of machine learning techniques for network analysis. Key methodological threads include coarse-grained modeling, spectral analysis of complex systems, and non-equilibrium thermodynamics frameworks. His 2023-2025 work shows growing emphasis on nonreciprocal interactions in active mixtures and physics-inspired machine learning applications. Prof. Sollich actively supervises Bachelor's, Master's, and PhD students, welcoming thesis inquiries in theoretical physics. His group develops analytical and computational approaches to complex dynamical systems, with recent grants likely supporting work on network dynamics and active matter modeling (specific grants not detailed in source text). His research group operates within the Institute for Theoretical Physics at Göttingen, focusing on computational and analytical modeling of disordered systems. Current projects involve elastoplastic modeling of amorphous solids, spectral analysis of heterogeneous networks, and theoretical frameworks for active matter phase separation.

• Hydrology
• Catchment Hydrology
• Ecohydrology
• +۶ مورد دیگر

Josie Geris is a Reader in Hydrology at the School of Geosciences , University of Aberdeen, holding a 0.8 FTE position since 2022. Her work bridges monitoring, modeling, and environmental tracer analysis to understand catchment processes under environmental change. Education : PhD in Civil Engineering and Geosciences (2012) from Newcastle University; MSc and BSc in EcoHydrology and Earth Sciences from VU University Amsterdam. Research Interests center on: • Vegetation-soil-water linkages in water storage and transmission • Nature-based solutions for flood and drought management • Multiscale catchment hydrology and land use impacts • Stable isotope tracing and water resource modeling. Publications highlight applications in agroforestry, river woodlands, and data-limited environments across Scotland, Europe, and tropical regions. Recent grants focus on nature-based water supply management , FARM TREE integration in agriculture, and Scottish water resilience under climate change. Scientific Grants (2016–2024): £100K (PI) - Surface water-groundwater connections in nature-based solutions £505K (PI) - FARM TREE: Balancing farm and landscape demands £220K (Co-I) - UK-China Critical Zone science tools £250K (Co-I) - Limpopo basin drought-flood governance She supervises PhD students in hydrological modeling, isotopic studies, and agroforestry impacts, while co-supervising interdisciplinary projects with the School of Biological Sciences. Her collaborative work involves institutions like the Northern Rivers Institute and the Centre of Expertise for Waters (CREW) .

Samantha McBirneyمشاهده پروفایل

استاد

• Biological Weapons and Warfare
• Biotechnology
• Emerging Technologies
• +۳ مورد دیگر

Samantha McBirney is an engineer and Professor of Policy Analysis at the RAND School of Public Policy within the RAND Corporation. Her work bridges engineering expertise with policy analysis, focusing on emerging technologies, military acquisition, and biotechnology. She holds a B.S. in Bioengineering from UC Berkeley, M.S. and Ph.D. in Biomedical Engineering from USC, and an MSc in Global Health Policy from the London School of Hygiene & Tropical Medicine. Her research emphasizes national security applications of biotechnology, medical readiness, and the impact of emerging technologies on defense strategies. Notable areas include blast injury mitigation, counterfeit pharmaceuticals in global health, and future military technologies like electric vertical takeoff aircraft. McBirney serves on the Pardee RAND Graduate School Faculty Committee on Curriculum and Appointment (FCCA), reflecting her academic leadership role. Her interdisciplinary approach combines technical expertise with policy analysis to address complex challenges in defense, health, and technology.

Mingji Zhangمشاهده پروفایل

دانشیار

• Dynamical Systems
• Differential Equations
• Geometric Singular Perturbation Theory
• +۵ مورد دیگر

Dr. Mingji Zhang is an Associate Professor in the Department of Mathematics at New Mexico Institute of Mining and Technology (NMT), tenured since August 2020. His research focuses on Dynamical Systems, Differential Equations, and their applications in electrochemical systems and biophysics. Key areas include Geometric Singular Perturbation Theory (GSPT), Poisson-Nernst-Planck (PNP) models for ion channel flows, and multiscale analysis in developmental biology. Education - Ph.D. (2013) in Mathematics, University of Kansas - M.A. (2011) in Mathematics, University of Kansas - M.A. (2005) in Applied Mathematics, Kunming University of Science and Technology - B.S. (2003) in Mathematics, Yantai Normal University Research Interests Dr. Zhang’s work emphasizes nonlinear dynamics and ion transport phenomena , particularly through PNP systems with steric effects and Bikerman potentials. His studies investigate boundary layer effects, ion size impacts, and bifurcation mechanisms in planar polynomial vector fields. Recent work integrates stochastic processes into fractional Ginzburg-Landau equations and descriptor systems with time delays. Article Trends His recent publications explore higher-order ion size contributions , critical potential roles in PNP systems , and stochastic dynamics in fractional models . Key themes include boundary layer analysis, nonlinear noise effects, and multi-component electrochemical systems. Awards/Grants No specific awards listed, but his tenure reflects sustained academic excellence. Active in securing research funding for PNP modeling and stochastic systems. Labs/Teams No named labs mentioned, but collaborates with groups in Mathematical Biology and Nonlinear Dynamics through interdisciplinary projects.

Daniele Cappellettiمشاهده پروفایل

دانشیار

• Stochastic Processes
• Probability Theory
• Mathematical Biology
• +۷ مورد دیگر

Daniele Cappelletti is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Politecnico di Torino, where he conducts research in stochastic modeling of biochemical reaction networks. He holds a PhD from the University of Copenhagen and has held postdoctoral positions at ETH Zurich, University of Wisconsin-Madison, and the University of Copenhagen. He is affiliated with the 'Probability and Applications' research group and leads the ConStRAINeD project funded by the Italian PRIN program. PhD in Probability, University of Copenhagen (2012–2015) M.S. in Mathematics, Pisa University (2009–2012) B.S. in Mathematics, Pisa University (2005–2009) His research focuses on stochastic processes, probability theory, and mathematical biology, particularly in the modeling and analysis of chemical reaction networks. He investigates the long-term behavior, stability, and model reduction in both deterministic and stochastic frameworks, with applications in systems biology and synthetic biology. His work bridges theoretical mathematics with practical biological systems, especially those exhibiting absolute concentration robustness. The trend in his recent publications shows a strong emphasis on the mathematical foundations of stochastic reaction networks, including tier structures, non-explosivity, and approximation techniques. He has also extended his work into computational applications such as using chemical networks to approximate probability distributions and analyzing security in blockchain protocols, demonstrating interdisciplinary reach across mathematics, biology, and computer science. Daniele Cappelletti currently supervises PhD student Giulio Cuniberti in the Mathematical Sciences program at Politecnico di Torino. He has been involved in competitive research grants, most notably as Scientific Manager of the ConStRAINeD project (2023–2026), which aims to advance the convergence and stability theory of reaction network dynamics. He has not received any explicitly mentioned scientific awards in the provided text. He is actively involved in teaching across multiple programs, including Mathematical Engineering, Data Science and Engineering, and Management Engineering. He teaches courses on stochastic processes, statistics, and time series analysis, both as course instructor and collaborator. He is a member of the Doctoral College in Mathematical Sciences and participates in the College of Management and Production Engineering and the College of Mathematical Engineering.

Salvatore Ivan Trapassoمشاهده پروفایل

استادیار

• Applied harmonic analysis
• Fourier analysis
• Machine learning
• +۵ مورد دیگر

Salvatore Ivan Trapasso is a Fixed-term Assistant Professor at the Department of Mathematical Sciences "GL Lagrange" (DISMA) , Polytechnic University of Turin , and a member of the SmartData@PoliTO - Big Data and Data Science Laboratory . His research focuses on Applied Harmonic Analysis , Fourier Analysis , Machine Learning , and Quantum Theory , with expertise in Mathematical Analysis (MATH-03/A) and Theoretical PDEs (PE1_11). Education : Implied PhD in Mathematics. Research Areas : Phase Space Analysis, Time-Frequency Methods, and Applications to Quantum Mechanics. His recent publications investigate phase space techniques for Feynman Path Integrals , Twisted Laplacian , Compressed Sensing , and Stability of Scattering Transforms . His work bridges Harmonic Analysis with Machine Learning and Quantum Dynamics . Notable scientific awards include the Axioms Young Investigator Award (2022) , Best Paper Award (ICGF 2020) , and the Quality Award 2019 from Polytechnic University of Turin. He serves on the Editorial Board of Advances in Operator Theory and as Associate Editor for University Texts in the Mathematical Sciences . Teaching roles include Lecturer for Mathematical Principles in the College of Architecture and Design , Collaborator for Mathematical Analysis I/II in Biomedical and Aerospace Engineering, and Contributor to advanced mathematical methods in Computer Science Engineering.

Robert Jacksonمشاهده پروفایل

استاد

• Tribology
• Friction
• Wear
• +۱۱ مورد دیگر

Robert Jackson is the Albert Smith Jr. Professor in the Department of Mechanical Engineering at Auburn University’s Samuel Ginn College of Engineering. He holds a Ph.D., M.S., and B.S. in Mechanical Engineering from the Georgia Institute of Technology and is a leading researcher in tribology, contact mechanics, friction, wear, and lubrication. He serves as Editor-in-Chief of the ASME Journal of Tribology and leads a research group focused on multiscale modeling, electrical contact reliability, and sustainable biolubricants. His research interests include: tribology, friction, wear, surface engineering, surface fatigue, lubrication, nano-lubricants, surface texturing, and multiphysics modeling. He applies these to challenges in electric vehicles, aerospace systems, and biomedical devices. His work integrates experimental validation with finite element and statistical modeling to understand contact behavior across scales. His recent publications focus on electrical erosion in EV bearings, nanoparticle-enhanced greases, mixed lubrication models, and biolubricants from waste oil. These works reflect a strong trend toward sustainable engineering, advanced materials, and predictive modeling in mechanical systems. His interdisciplinary approach bridges mechanical, materials, and electrical engineering. ASME Fellow Fellow, Society of Tribologists and Lubrication Engineers (STLE) Ralph Beard Memorial Academic Award Editor-in-Chief, ASME Journal of Tribology Dr. Jackson advises graduate students such as Jack Janik and collaborates with researchers on projects involving electrical connectors, solenoid valves, and biolubricant development. His lab engages in both fundamental contact mechanics and applied industrial problems. He leads the tribology minor and student sections of ASME and STLE at Auburn.

Silvia Salinas Blemkerمشاهده پروفایل

استاد

• Biomechanics
• Musculoskeletal Diseases
• Multi-scale Modeling
• +۵ مورد دیگر

Dr. Silvia Salinas Blemker is a Professor of Biomedical Engineering at the University of Virginia, with a courtesy appointment in Mechanical and Aerospace Engineering. Her research focuses on understanding muscle structure-function relationships through computational and experimental models to develop treatments for musculoskeletal diseases. She earned her undergraduate and Master’s degrees in Biomedical Engineering from Northwestern University and a PhD in Mechanical Engineering from Stanford University. Her Multiscale Muscle Mechanophysiology (M3) Lab investigates skeletal muscle mechanics, regeneration, and disease mechanisms, particularly in conditions like muscular dystrophy and aging. The lab’s work integrates AI-driven MRI analysis, finite element modeling, and clinical collaborations to improve patient outcomes. Key projects include developing the FDA-approved Springbok Analytics tool for muscle health assessment and advancing understanding of muscle regeneration through agent-based modeling. Dr. Blemker has received prestigious awards such as the National Academy of Inventors Fellowship (2024) and the American Society of Biomechanics’ Goel Award (2024). She teaches courses in biomechanics and motion analysis. Her research has been featured in innovations like biomechanics-based injury prevention systems for athletes and novel imaging techniques for neuromuscular disease monitoring.

Mool C. Guptaمشاهده پروفایل

استاد

• Photonics
• Photovoltaics
• Nanomaterials
• +۴ مورد دیگر

Mool C. Gupta is the Langley Distinguished Professor and Founding Director of the NSF Industry/University Cooperative Research Center for Lasers and Plasmas at the University of Virginia. He holds affiliations with the Department of Electrical and Computer Engineering within the School of Engineering and Applied Science. Previously, he served as Director of the Applied Research Center at Old Dominion University and worked at Eastman Kodak Company and NASA's Jet Propulsion Laboratory. His academic roles include Adjunct Professor at Cornell University and Editor-in-Chief of the Handbook of Photonics . Education: Senior Research Fellow, California Institute of Technology (1978–1979) Postdoctoral Fellow, Cornell University (1976–1978) Ph.D. in Physics, Washington State University (1973) Research Interests: His work focuses on photon processing of materials, photovoltaics, nanomaterials, and optoelectronic devices. Key areas include laser processing for solar cell optimization, anti-icing surface technologies, and advanced materials characterization. His research bridges fundamental materials science with practical applications in energy and aerospace. Publications & Trends: Gupta's recent work emphasizes laser-based manufacturing, thermoelectric materials, and photovoltaic innovations. His 2023 study on silicon solar cell passivation and 2020 research on anti-icing surfaces highlight his dual focus on energy and materials engineering. He frequently publishes in journals like Applied Physics , Journal of Alloys and Compounds , and IEEE Transactions . Awards: Member of Kodak's Inventors' Gallery Fellow of the National Academy of Inventors Grants & Advising: Past PI for NSF, DARPA, AFOSR, and NASA projects. Courses taught include Photovoltaics and Electrical Engineering Projects . His lab collaborates on solar-land coexistence solutions and advanced materials for energy systems. Labs & Teams: Directs the NSF Center for Lasers and Plasmas, leveraging interdisciplinary teams for laser-materials innovation. His lab focuses on photonics, nanotechnology, and sustainable energy solutions.

Alfredo Bensoمشاهده پروفایل

استاد

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +۱۶ مورد دیگر

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

• Mechanobiology
• Computational Mechanics
• Soft Matter Physics
• +۷ مورد دیگر

Marino Arroyo is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Research Center in Numerical Methods in Applied Science and Engineering (LaCàN). He is also associated with CIMNE and the Institute of Bioengineering of Catalunya (IBEC). His work focuses on computational and theoretical modeling of biological systems, particularly epithelial mechanics, active matter, and biomembranes. He holds the Icrea Academia Award, recognizing his contributions to mechanobiology and soft matter physics. Education: PhD in Mechanical Engineering, Northwestern University (2003) BS/MS in Civil Engineering, UPC Postdoc at Caltech with Michael Ortiz (2003-2004) Research Interests: Combines mathematical modeling, mechanics, and computations to study small-scale material behavior and biological systems. Current focus includes cell/tissue mechanobiology, active living materials, and bio-inspired materials. Key themes are nonlinear mechanics of 2D materials (graphene, biomembranes), continuum mechanics, and molecular-to-continuum modeling. Recent Article Trends: Focuses on multiscale epithelial mechanics, active gels, hydraulic fracture in biological systems, and mechanochemical feedback in cellular membranes. Recent work includes modeling curved epithelial shells, nematic patterns in cytoskeletal layers, and shape-programmable living surfaces. Scientific Awards: Icrea Academia Awardee Advising & Grants: Supervised over 20 PhD students, many of whom hold prestigious postdocs or academic positions. Collaborates with experimental groups (e.g., Xavier Trepat, Danijela Vignjevic). Current projects include NIH-funded studies on epithelial mechanics and ERC grants for computational modeling. Labs/Teams: Leads LaCàN's biomaterials group, integrating computational mechanics with experimental biology. Active in interdisciplinary collaborations across UPC, IBEC, and international institutions.

Felix Schindlerمشاهده پروفایل

پژوهشگر

• Numerical Analysis
• Machine Learning
• Scientific Computing
• +۳ مورد دیگر

Felix Schindler is a Researcher at the Institute for Analysis and Numerical Analysis , part of the Department of Mathematics and Computer Science at the University of Münster . His work bridges numerical analysis, machine learning, and scientific computing, with a focus on model reduction for partial differential equations (PDEs), adaptive algorithms, and computational efficiency. Research Interests include: Numerical analysis of parametric and multiscale PDEs Localized reduced basis methods (LRBM) and adaptive enrichment Integration of model order reduction (MOR) with machine learning (ML) Conservative flux reconstruction techniques Development of software libraries like dune-xt and pyMOR Recent Publications highlight trends in applying deep kernel models for surrogate modeling, localized training strategies for PDE-constrained optimization, and hybrid full/reduced-order pipelines for reactive flow prediction. His work emphasizes certified error control, hierarchical adaptivity, and cross-disciplinary computational frameworks. Collaborations span institutions such as AIMS Senegal, Springer Nature, and DUNE project teams. He actively contributes to conferences like GAMM, ENUMATH, and Algoritmy.