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Arthur UtzView profile

Professor

• Physical Chemistry
• Surface Chemistry
• Heterogeneous Catalysis
• +3 more

Arthur Utz is a Professor of Chemistry at Tufts University's School of Arts and Sciences. He leads the Utz Group, which investigates molecular dynamics at gas-surface interfaces, focusing on heterogeneous catalysis and chemical vapor deposition. His research employs state-resolved laser excitation and supersonic molecular beams to control reaction parameters, revealing insights into energy redistribution and reaction control. Education: PhD (1991) and BS (1983) in Chemistry from the University of Wisconsin-Madison and Bradley University, respectively. His work has been supported by grants from the National Science Foundation and the Arnold and Mabel Beckman Foundation. He was awarded Fellowship in the American Vacuum Society (2016). Research highlights include vibrational control of methane dissociation on metal surfaces and the role of surface temperature in catalytic processes. His lab has trained numerous graduate students and postdoctoral researchers, with notable contributions to surface science and reaction dynamics. The group also emphasizes outreach, hosting workshops and conferences like the Gordon Research Seminar on Dynamics at Surfaces. Grants: SusChEM: Chemical Dynamics of Polyatomic Molecules at Surfaces (2018-2021), MRI: Single Crystal X-Ray Diffractometer (2012-2015) Key Students: Laurin, Molly, Yuxuan, Matt, Daniel Tinney, Eric High, Sally Shepardson-Fungairino Lab Facilities: Surface Science Research Laboratory with ultra-high vacuum chambers and laser systems Recent publications emphasize nonthermalized precursor-mediated reactions and vibrational activation in catalytic environments, advancing the rational design of catalytic materials.

Min SunView profile

Associate Professor

• Structural Engineering
• Steel Structures
• Civil Engineering
• +3 more

Dr. Min Sun is an Associate Professor and Director of the Undergraduate Program in the Department of Civil Engineering at the University of Victoria (UVic). He holds a PhD from the University of Toronto. His research focuses on structural engineering and steel structures, particularly in the areas of steel connections, seismic resilience, and numerical modeling. Dr. Sun has extensive academic and professional experience, including roles as Assistant Professor at UVic (2016–2022), Lecturer at the University of Toronto, and structural design roles in industry. His research interests emphasize the performance of steel structures under extreme loads, including earthquake engineering and material behavior. Recent work includes studies on stress concentration factors in steel connections, thermal integrity of piles, and wood-frame building reliability under lateral loads. He actively contributes to professional organizations, such as serving as Vice President (Western Region) for the Canadian Society for Civil Engineering (2018–2020). Dr. Sun teaches courses including Advanced Structural Analysis (CIVE 421) and Solid Mechanics (CIVE 220) at UVic. He currently supervises graduate students in structural steel design and construction. His publications span experimental and numerical analyses, with a focus on improving design standards for steel and wood structures. Labs/Teams: Affiliated with UVic's Engineering and Computer Science faculty and the IESVIC (Institute for Energy Systems and Sustainability at UVic), though specific lab names are not explicitly stated in the text.

• Knee Osteoarthritis
• Biomechanics
• Rehabilitation Science
• +7 more

Monica Maly is a Part-Time Associate Professor in Rehabilitation Science within the Faculty of Health Sciences at McMaster University. Her academic profile demonstrates extensive expertise in biomechanics and rehabilitation, with particular focus on knee osteoarthritis research. She maintains an active research program with numerous recent publications spanning rheumatology, biomechanics, and rehabilitation science. Dr. Maly's research interests center on understanding the biomechanical and physiological factors contributing to knee osteoarthritis progression and developing effective interventions. Her work examines knee joint mechanics, muscle strength and capacity, gait analysis, pain management strategies, and the impact of exercise interventions on OA symptoms. She has conducted significant research on sex differences in OA, racial disparities in pain experiences, and the relationship between obesity, inflammation, and joint function. Her methodological approaches include biomechanical analysis, clinical trials, systematic reviews, and innovative technologies like soft robotics for knee bracing. Analysis of her recent publications (2023-2025) reveals a strong focus on understanding knee osteoarthritis mechanisms through biomechanical and physiological lenses, with increasing attention to social determinants of health and health disparities. Her work spans multiple disciplines including rheumatology, biomechanics, rehabilitation science, and public health, demonstrating interdisciplinary collaboration. Key trends include examining racial disparities in pain experiences, developing novel interventions like soft robotic knee braces, and investigating the complex relationships between joint loading, biomarkers, and cartilage changes. Dr. Maly has collaborated extensively with researchers across multiple institutions, as evidenced by her numerous publications in high-impact journals such as Osteoarthritis and Cartilage, Arthritis & Rheumatology, and Clinical Biomechanics. Her work often utilizes data from large longitudinal studies including the Osteoarthritis Initiative and the Canadian Longitudinal Study on Aging. While specific grant information isn't detailed in the provided text, her extensive publication record suggests successful funding of multiple research projects.

Neville HoganView profile

Professor

• Rehabilitation Engineering
• Robotics
• Motor Neuroscience
• +3 more

Neville Hogan is a Professor of Mechanical Engineering and Brain & Cognitive Sciences at MIT, and Director of the Newman Laboratory for Biomechanics and Human Rehabilitation. He holds a Ph.D. from MIT and has been a faculty member since 1979, leading roles in the Mechanical Engineering department's System Dynamics and Control division. His research bridges biology and engineering, focusing on motor neuroscience, rehabilitation robotics, and human-robot interaction. He co-founded Interactive Motion Technologies, Inc. and is a board member at Advanced Mechanical Technologies, Inc. Education: Dip. Eng. (Dublin College of Technology), M.S., M.E., and Ph.D. (MIT) Research interests include developing robots for neurological rehabilitation, such as gentle physiotherapy devices for stroke patients. His work emphasizes physically cooperative machines and human balance control analysis. Awards include Honorary Doctorates from Delft University and Dublin Institute of Technology, and the Silver Medal from Ireland’s Royal Academy of Medicine. Awards: Honorary Doctorates, Silver Medal, and other distinctions Led the Newman Lab, focusing on biomechanics and human rehabilitation. Advised numerous students (not listed here). His publications explore dynamic primitives, impedance control, and human-robot interaction, with applications in exoskeletons and rehabilitation therapies.

Nick HeardView profile

Professor

• Computational Bayesian Inference
• Clustering
• Changepoint Analysis
• +6 more

Nick Heard is a Professor and Chair in Statistics at the Department of Mathematics, Faculty of Natural Sciences, Imperial College London. His research focuses on computational Bayesian inference, clustering, and changepoint analysis applied to dynamic networks (e.g., computer networks, social networks) and bioinformatics. He leads the EPSRC-funded NeST project on Network Stochastic Processes and Time Series, collaborating with universities including Bristol, Oxford, and LSE. His work bridges statistical theory with applied problems in cyber-security and neuroscience. Research Interests - Modelling large dynamic networks - Changepoint analysis and anomaly detection - Statistical methods for cyber-security - Bayesian computation and inference - Spectral clustering and graph embeddings Grants & Collaborations - Co-leads the NeST project on Dynamic graph embeddings: procedures and inference - EPSRC Programme Grant (EP/T004870/1) supporting Network Stochastic Processes and Time Series research Software & Tools - Developed open-source packages for Bayesian changepoint analysis (e.g., changepoints ) - Code for p-value combination methods ( standardised_partial_product )

Patrick JennyView profile

Professor

• Computational Fluid Dynamics
• Turbulent Reactive Flows
• Multiphase Flow Modeling
• +3 more

Prof. Patrick Jenny is a Full Professor at the Department of Mechanical and Process Engineering and Head of the Institute of Fluid Dynamics at ETH Zurich. His research focuses on computational fluid dynamics (CFD), numerical methods for turbulent and multiphase flows, and reservoir simulation. He has held positions at ChevronTexaco and Cornell University, and received the National Latsis Prize 2005. PhD in CFD from ETH Zurich (1997) Postdoctoral work at Cornell University (1997–1999) Senior Researcher at ChevronTexaco (1999–2003) Research interests include: turbulent reactive flows, PDF modeling, multi-scale reservoir simulation, and data assimilation in engineering systems. He teaches courses on fluid dynamics, turbulence, and computational methods. Over 100 peer-reviewed publications span topics like fracture modeling, LES/RANS coupling, and particle-laden flows. His work bridges academia and industry, addressing challenges in energy systems, environmental engineering, and numerical algorithms. Winner: National Latsis Prize 2005 Led over 20 PhD projects and collaborates with institutions globally. His lab develops open-source tools for CFD and energy systems analysis.

Zachary E. RossView profile

Professor

• Seismology
• Geophysics
• Machine Learning
• +7 more

Zachary E. Ross is a Professor of Geophysics at the California Institute of Technology (Caltech) and holds the William H. Hurt Scholar distinction since 2021. His research integrates machine learning, computational mathematics, and seismology to analyze earthquakes and fault zones using large seismic datasets. Education B.S., University of California, Davis (2009) M.S., California Polytechnic State University, San Luis Obispo (2011) Ph.D., University of Southern California (2016) His research focuses on high-resolution imaging of fault zones, understanding earthquake sequences in space and time, and applying artificial intelligence to seismic data analysis. He develops scalable algorithms for waveform inversion, ground-motion synthesis, and real-time seismic monitoring. Recent publications highlight his work on neural operators for wave propagation, AI-driven seismicity analysis, and induced earthquake dynamics. He teaches advanced courses including Ge 264 – Machine Learning in Geophysics and Ge 271 – Dynamics of Seismicity . Scientific Awards William H. Hurt Scholar (2021–present)

Hyungwoong AhnView profile

Senior Lecturer

• Adsorption Processes
• CO2 Capture
• Carbon Capture and Storage
• +5 more

Dr. Hyungwoong Ahn is a Senior Lecturer in Chemical Engineering at the University of Edinburgh and an Adjunct Professor at Yonsei University. His expertise lies in adsorption process engineering, particularly for CO2 capture and gas separation. He leads the Carbon Capture Group and coordinates exchange programs for chemical engineering students. Dr. Ahn holds a BSc, MSc, and PhD in Chemical Engineering from Yonsei University. Roles: Senior Lecturer (Edinburgh) & Adjunct Professor (Yonsei) Research Focus: Pressure Swing Adsorption (PSA), CO2 capture technologies, hydrogen purification, and industrial decarbonisation Key Projects: PSA-SPUR technology development, ship-based carbon capture, and collaboration with HD Korea Shipbuilding Awards: KOFST Brain Pool Fellow, IChemE Global Awards finalist, and Honeywell UniSim Design Challenge winner His research integrates equilibrium theory analysis, numerical simulation, and experimental validation to advance carbon capture systems. He has authored over 50 publications (H-index 32) and secured funding from EPSRC, BEIS, KETEP, and others.

Mohamed FarhatView profile

Researcher

• Cavitation & Multiphase flows
• Flow Induced Noise & Vibration
• Fluid-Structure Interaction
• +5 more

Mohamed Farhat is a Senior Scientist at EPFL's School of Engineering, Department of Mechanical Engineering, where he leads the Research Group on Cavitation and Interface Phenomena. He serves as PhD Director, Lecturer, and Member of EPFL Doctoral Committee (Mechanics), while also representing EPFL at CLUSER association and coordinating activities at the Société Hydrotechnique de France (SHF). His research expertise spans Cavitation & Multiphase flows, Flow Induced Noise & Vibration, Fluid-Structure Interaction, Flow control, Flow instabilities in hydro turbines and pumps, Condition monitoring of Hydraulic Machines, Hemodynamics, and Advanced Instrumentation in Fluid Dynamics. Farhat's work uniquely bridges fundamental fluid mechanics with practical applications across hydropower, marine propulsion, healthcare, and water management sectors. Analysis of his recent publications reveals strong focus on cavitation bubble dynamics, with particular emphasis on measurement techniques for collapsing bubbles, vortex shedding control, hydrodynamic monitoring of hydraulic machinery, and biomedical applications of cavitation phenomena. His work increasingly integrates advanced imaging techniques with computational modeling to understand complex multiphase flow phenomena. 2021: Life Sciences Book Award of the International Academy of Astronautics 2019: 1st Prize Winner of Scientific Image Contest (Swiss National Science Foundation) 2020: EPFL-Rhyming Prize (Best PhD thesis in Fluid Mechanics) 2018: EPFL-EDME Prize (Best PhD thesis in Mechanics) 2015: Edmund Optics Educational Award 2014: APS-DFD Gallery of Fluid Motion Award Farhat has successfully supervised numerous PhD students including Ali Amini, Philippe Ausoni, and Outi Supponen, with research spanning from fundamental bubble dynamics to practical hydraulic machinery applications. His Cavitation Research Group maintains strong collaborations with industry partners in hydropower and medical device sectors. Current research directions include advanced instrumentation for cavitation monitoring, condition-based maintenance of hydraulic machinery, and biomedical applications of cavitation phenomena in therapeutic ultrasound and drug delivery.

• Large deformation FE analysis of soils
• Soil–structure interaction
• Offshore foundation systems
• +7 more

Yuxia Hu is a Professor at the University of Western Australia, affiliated with the School of Engineering (Civil, Environmental and Mining Engineering) and the School of Social Sciences, Planning and Transport Research Centre. Her research focuses on geotechnical engineering, particularly in large deformation FE analysis, offshore foundation systems, and soil-structure interaction. She has contributed to advancements in suction caissons, plate anchors, and computational mechanics, with applications in offshore wind energy and infrastructure stability. Research Interests: Large deformation FE analysis of soils, soil-structure interaction, offshore foundation systems, soil mechanics, and pavement engineering. Awards: Telford Premium, British Geotechnical Association Prize, and Significant Junior/Senior Paper Award. Grants: Leads projects on offshore anchors, carbon capture in pavements, and road maintenance optimization. Her work addresses challenges in geotechnical design and sustainable infrastructure, with a focus on numerical modeling and experimental validation. Collaborations span academia and industry, emphasizing practical solutions for complex soil-structure systems.

Ed ChienView profile

Assistant Professor

• Computer Science
• Graphics
• Computational Engineering
• +3 more

Ed Chien is an Assistant Professor at Boston University's Department of Computer Science within the College of Arts & Sciences. He specializes in applying differential geometry and topology to graphics, computational engineering, and machine learning. Previously, he was a postdoctoral researcher at MIT's CSAIL and Bar-Ilan University. His work focuses on mathematically rigorous solutions to problems in geometric data processing and optimal transport. Education PhD in Mathematics, Rutgers University (2015) A.B. in Mathematics & Physics, Dartmouth College (2009) Research Highlights Dr. Chien's research includes fundamental studies on hexahedral mesh topology for Finite Element Modeling, optimal transport applications in machine learning, and singularity-free geometric algorithms. His work bridges theoretical mathematics with computational tools for engineering and graphics. Publications span top venues like NeurIPS, Eurographics, and SIGGRAPH, reflecting contributions to geometry processing and machine learning intersections. Program committee roles include Eurographics SGP (2019) and AAAI (2020). Awards & Recognition No specific awards listed, but notable service includes program committee memberships and peer-reviewed contributions to leading conferences. Grants & Advising Active in mentoring through academic positions but no explicit grant details provided. Research focuses on advancing geometric algorithms and optimal transport methodologies.

Celia ReinaView profile

Associate Professor

• Materials Science
• Computational Mechanics
• Non-equilibrium Thermodynamics
• +3 more

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.

Jonathan WeareView profile

Professor

• Monte Carlo sampling
• Multiscale analysis
• Randomized numerical linear algebra
• +2 more

Jonathan Weare is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds affiliations with the Faculty of Arts and Science and the Graduate School of Arts and Science. His academic journey includes roles as an Associate Professor at the University of Chicago (2014–2019) and Assistant Professor (2011–2014), following postdoctoral work as a Courant Instructor at NYU. He earned his Ph.D. in Mathematics from UC Berkeley in 2007. His research focuses on stochastic algorithms and models, with applications in astrophysics, biophysics, computational chemistry, and climate science. Key areas include Monte Carlo methods, rare event simulation, and machine learning-driven scientific analysis. Collaborations with domain experts ensure his work addresses real-world challenges in diverse fields. Recent publications emphasize advancements in trajectory stratification, rare event prediction using machine learning, and efficient algorithms for high-dimensional problems. Notable contributions include the BAD-NEUS framework and AI-based solar system instability predictions. His group’s interdisciplinary approach bridges computational methods with scientific inquiry. Weare has advised numerous students and mentored postdocs, fostering talent in applied mathematics and computational science. His work on Mercury’s orbital dynamics and extreme weather prediction showcases the societal impact of his research. Current projects explore AI applications in weather modeling and rare event analysis, leveraging cutting-edge machine learning techniques. Labs/Teams: His research group at Courant develops stochastic algorithms and collaborates with interdisciplinary teams in computational chemistry, climate science, and astrophysics. Key collaborations include the University of Chicago and Columbia University.

Ruming ZhangView profile

Academic

• Partial Differential Equations
• Inverse Problems
• Numerical Methods
• +4 more

Prof. Dr. Ruming Zhang is a Tenure-Track Professor at TU Berlin's Faculty II - Mathematics and Natural Sciences, leading the Analysis and Applications group since May 2023. He specializes in numerical methods for partial differential equations and inverse problems, with a focus on wave scattering and periodic structures. His research bridges theoretical analysis and computational techniques, addressing challenges in areas like photonic crystals and non-destructive testing. Education & Career: PhD in Mathematics (Chinese Academy of Sciences, 2014) Postdoctoral Researcher at Michigan Technological University Marie-Curie Fellow (University of Bremen, 2015-2018) Junior Group Leader at KIT (Karlsruhe Institute of Technology, 2018-2023) Research Interests: Analysis and numerical methods for PDEs, inverse scattering problems, waveguide analysis, periodic structures, and their applications in nanotechnology and engineering. His work emphasizes high-order numerical schemes and theoretical frameworks for ill-posed problems. Key Contributions: Development of nonuniform mesh methods for periodic surface scattering, high-order numerical techniques for bi-periodic structures, and monotonicity-based shape reconstruction in waveguides. His methods address challenges in computational wave physics and mathematical modeling. Awards: Richard-von-Mises Prize (GAMM, 2023) Marie-Curie Fellowship (EU FP7-PEOPLE, 2015-2017) Teaching & Mentorship: Offers courses on inverse problems, scattering theory, boundary element methods, and applied analysis. Advises students on thesis topics in mathematical theory for photonic crystals and wave propagation. Actively promotes interdisciplinary collaboration between mathematicians and engineers. Grants & Projects: DFG Grant (2019-2024): Higher-order methods for acoustic scattering in periodic structures Marie-Curie COFUND Fellowship (Bremen TRAC, 2015-2017) Labs/Teams: Leads the Analysis and Applications research group at TU Berlin, focusing on interdisciplinary projects combining mathematical theory with computational tools for real-world applications.

• International Relations
• American Foreign Policy
• International Security
• +3 more

Michael C. Desch is the Packey J. Dee Professor of Political Science and the Brian and Jeannelle Brady Family Director of the Notre Dame International Security Center at the University of Notre Dame. He previously served as Chair of the Department of Political Science, founding Director of the Scowcroft Institute of International Affairs at Texas A&M University, and held roles in U.S. government agencies including the State Department and Congressional Research Service. Desch holds a B.A. (Honors) in Political Science from Marquette University (1982), an A.M. in International Relations (1984), and a Ph.D. in Political Science (1988) from the University of Chicago. His research focuses on international security, U.S. foreign policy, and civil-military relations, with notable works including Power and Military Effectiveness (2008) and Cult of the Irrelevant (2018). He critiques the disconnect between academic research and policy-making, emphasizing the need for relevance in social science. His articles address topics like U.S.-China relations, nuclear strategy, and the academic-policy divide. He has spoken at numerous conferences, including the American Political Science Association and the Atlantic Council, and has appeared on media outlets such as CNBC and Al Jazeera. Key Contributions: Over 100 scholarly articles, four authored books, and co-edited volumes on security studies and policy. Grants & Funding: Supported by institutions like the Carnegie Corporation and the Minerva Initiative. Labs/Teams: Leads the Notre Dame International Security Center, fostering interdisciplinary research on global security challenges.