جست‌وجوی استاد و پژوهشگر

Charles Holtمشاهده پروفایل

استاد

• Experimental economics
• Mathematical economics
• Behavioral game theory
• +۷ مورد دیگر

Charles Holt is the A. Willis Robertson Professor of Political Economy at the University of Virginia's Department of Economics and Director of the Veconlab. His work bridges experimental economics , game theory , and economic education , with a focus on quantal response equilibrium (QRE), asset market bubbles , and belief/risk elicitation methods. He co-founded the journal Experimental Economics and has advised students like Ricky Sahu and Angela Smith on award-winning research. Education: BA, Washington & Lee University MS, PhD, Carnegie Mellon University Holt’s research demonstrates how stochastic decision-making in QRE explains systematic deviations from Nash equilibrium across social dilemmas, auctions, and voting games. His experimental auction designs for institutions like the FCC and Regional Greenhouse Gas Initiative have informed real-world policy. He also pioneered the Holt-Laury measure of risk aversion and the Veconlab software , used by 15,000 students monthly. Scientific awards include the 2023 AEA Distinguished Economic Education Award , the 2018 UVA Thomas Jefferson Award , and the 2008 SEA Kenneth Elzinga Teaching Award .

Shaowei Wangمشاهده پروفایل

استاد

• Heat and mass transfer in porous media
• Fluid mechanics
• Mathematical methods in mechanics

Shaowei Wang is a Professor in the Department of Engineering Mechanics at the School of Civil Engineering, Shandong University, China. He holds a Ph.D. in Mathematics (2007) from Shandong University and completed post-doctoral research in fluid mechanics (2009) at Peking University. His research focuses on heat and mass transfer in porous media , fluid mechanics , and mathematical methods in mechanics . His recent publications highlight advancements in electro-osmotic flows, oscillatory non-Newtonian fluid dynamics, and stability analysis of bioconvection in porous media. Key themes include modeling viscoelastic fluids (Oldroyd-B, Maxwell), fractional calculus applications, and microchannel transport phenomena. First Prize in Natural Science of the Ministry of Education (2015) Second Prize of Natural Science Award of Shandong Province (2015) Du Qinghua Young Scholar Award (2016) Wang serves as Director of Shandong Society of Mechanics and editorial board member of multiple journals. His work bridges theoretical fluid dynamics with practical applications in microfluidics and geophysical systems.

Christopher Wolfeمشاهده پروفایل

دانشیار

• Physical Oceanography
• Large-Scale Circulation
• Overturning Circulation
• +۴ مورد دیگر

Christopher Wolfe is an Associate Professor of Marine Science at the School of Marine and Atmospheric Sciences (SoMAS) at Stony Brook University. He conducts research on physical oceanography, focusing on large-scale ocean circulation, overturning dynamics, and mesoscale eddy interactions. Education: Ph.D. in Physical Oceanography (2006), Oregon State University M.S. in Physics (2000), Indiana University B.S. in Physics and Mathematics (1999), Evergreen State College His research integrates theoretical frameworks, idealized numerical models, and realistic ocean circulation simulations to study the ocean’s role in climate systems. Key areas include overturning circulation stability, buoyancy-driven currents, and predictability of geophysical flows. Recent publications highlight his work on interannual variability in the Indian Ocean, salt feedback mechanisms, and multi-scale instabilities. He advises Ph.D. and postdoctoral researchers in the Pitt Wolfe group , which has produced alumni now working at institutions such as NOAA and the Ocean University of China. Scientific Affiliations: Active in computational oceanography and nonlinear dynamics Collaborator with P. Cessi, R. M. Samelson, and others

Kevin Griffinمشاهده پروفایل

پژوهشگر

• Computational Fluid Dynamics
• Machine Learning
• High-Performance Computing
• +۳ مورد دیگر

Kevin Griffin is a Researcher III in Computational Science at the National Renewable Energy Laboratory (NREL). His work focuses on integrating advanced computational techniques with energy systems research. Bachelor of Mechanical and Aerospace Engineering, Princeton University PhD in Mechanical Engineering, Stanford University Master of Mechanical Engineering, Stanford University Griffin's primary research interests include multi-fidelity simulation , neuromorphic computing , and energy-efficient computing . He specializes in computational fluid dynamics and turbulence modeling for energy applications, particularly wind energy systems. His recent publications emphasize adaptive computing frameworks for scale-up problems, pressure-gradient sensors for turbulence prediction, and boundary layer modeling extensions. These works span computational methods, uncertainty management, and energy systems design. Gerald J. Lieberman Fellowship (2022) National Defense Science and Engineering Graduate Fellowship (2017) NREL Key Contributor Award (2023) NREL Outstanding Mentor Award (2024) Stanford Graduate Fellowship (2017) Griffin contributes to collaborative networks like the American Physical Society, Sigma Xi, and Tau Beta Pi, advancing turbulence modeling and computational efficiency in energy applications.

Tillman Weydeمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Signal Processing
• Data Analysis
• +۵ مورد دیگر

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

Elena D'Onghiaمشاهده پروفایل

دانشیار

• Galactic Dynamics
• Stellar Structure Formation
• Numerical Simulations
• +۳ مورد دیگر

Elena D'Onghia is an Associate Professor in the Department of Astronomy at the University of Wisconsin-Madison. Her research focuses on unraveling the dynamical processes that shape the stellar structure of the Milky Way and nearby galaxies using analytical models and high-resolution numerical simulations. She leverages data from the GAIA satellite to study galactic evolution, emphasizing the importance of understanding our cosmic environment beyond the Solar System. University: University of Wisconsin-Madison Department: Astronomy Contact: edonghia@astro.wisc.edu | 4504 Sterling Hall Research Interests D'Onghia's work spans galactic dynamics, stellar structure formation, and interstellar medium processes. She investigates how gravitational interactions, stellar bars, and supernova-driven outflows influence galactic morphology. Her studies often integrate multi-wavelength observations with cosmological simulations to trace the evolution of galaxies like the Milky Way and Magellanic Cloud analogs. Recent Publications Her recent articles highlight galactic disk corrugations, starburst outflows in the LMC, and the role of classical bulges in shaping stellar bars. Collaborative projects include the Sloan Digital Sky Survey and ALMA-based studies of high-redshift galaxies. Scientific Awards 2018-2020 Vilas Associate Professor Research Fellow 2013-2017 Alfred P. Sloan Research Fellow 2013 Kavli Fellow Frontiers of Science 2009-2012 Keck Fellowship (Harvard) 2005-2006 Max-Planck Research Fellowship

Juan R. Cebralمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Hemodynamics
• Cerebral Aneurysms
• +۷ مورد دیگر

Juan R. Cebral is a Professor in the Departments of Bioengineering and Mechanical Engineering at the Volgenau School of Engineering, George Mason University. He leads the Computational Hemodynamics Laboratory and maintains affiliations with the Center for Computational Fluid Dynamics and the Krasnow Institute for Advanced Studies. His research bridges engineering and medicine to address life-threatening vascular conditions through computational modeling. He earned his PhD in Computational Sciences and Informatics from George Mason University in 1996 and completed his MSc in Physics at the University of Buenos Aires, Argentina in 1991. Originally from Plaza Huincul in Patagonia, Argentina, he has built an internationally recognized research program focused on patient-specific modeling of cerebral blood flow. Professor Cebral's research centers on using computational fluid dynamics to model hemodynamics in cerebral aneurysms and other vascular diseases. His work investigates the relationship between blood flow patterns and aneurysm development, rupture, and treatment outcomes, with particular focus on flow diversion techniques. His lab develops methods for constructing patient-specific anatomical models from medical images and applies them to enhance risk assessment and personalize endovascular treatments. His research has been funded by the National Institutes of Health, American Heart Association, Whitaker Foundation, and industry partners including Philips Healthcare and Boston Scientific. His recent publications (2024-2025) demonstrate continued focus on cerebral aneurysm hemodynamics with increasing attention to flow diversion mechanisms, fibrin accumulation, and aneurysm wall integrity. His work integrates computational modeling with biological and clinical data to better understand aneurysm growth patterns, rupture risks, and treatment outcomes, featuring sophisticated multi-scale modeling approaches that connect hemodynamic conditions with biological responses in the vessel wall. His research has been funded by prestigious organizations including the National Institutes of Health, American Heart Association, and Whitaker Foundation His work has been featured in Forbes Argentina (August 5, 2024 and October 7, 2024) His student Medhini Sosale earned the prestigious Goldwater Scholarship (April 12, 2022) Professor Cebral mentors students in bioengineering research, with several advisees receiving significant recognition. His research program is supported by multiple NIH grants including R01 NS076491 (Computational and Biological Approach to Flow Diversion) and R21 NS094780 (Improved evaluation of PCOM aneurysms), as well as funding from Philips Medical Systems and Mayo Clinic. He collaborates extensively with clinicians at Inova Fairfax Hospital, Mayo Clinic, and international institutions to translate computational findings into clinical practice. He directs the Computational Hemodynamics Laboratory at George Mason University, which specializes in patient-specific modeling of blood flows in cerebral aneurysms. The lab works closely with the Center for Computational Fluid Dynamics and collaborates with clinicians and researchers from Inova Fairfax Hospital, Mayo Clinic, Allegheny General Hospital, Kuopio Medical Center in Finland, Clinica ENERI in Argentina, University of Pittsburgh, and Barcelona Supercomputing Center.

Richard Beckerمشاهده پروفایل

استاد

• Environmental Remote Sensing
• GIS Applications
• Hydrogeology
• +۷ مورد دیگر

Dr. Richard Becker is a Professor in the Department of Environmental Sciences at the University of Toledo , affiliated with the College of Natural Sciences and Mathematics . He directs the Environmental Remote Sensing Lab , where he employs interdisciplinary methods including remote sensing, geochemistry, hydrologic modeling, and UAV technologies to address geological and environmental challenges. Education: Ph.D. (2008) from Western Michigan University, M.A. and B.A. from Washington University Contact: richard.becker@utoledo.edu | 419.530.4571 | Wolfe Hall, Toledo, OH Research Focus Dr. Becker's work spans three decades, concentrating on: Environmental applications of remote sensing and GIS for geohazard mapping Assessment of land subsidence in arid regions and coastal areas Monitoring toxic algal blooms in the Laurentian Great Lakes Hydrological impacts of engineering projects on wetland systems Climate change effects on groundwater resources in Africa and the Middle East Article Trends His recent publications (2018-2024) demonstrate a consistent focus on: Integration of UAV/drone technologies for high-resolution environmental monitoring Application of remote sensing to track climate change impacts on water systems Development of multi-model ensembles for watershed management Analysis of human-environment interactions through geospatial methods

Bradford Knightمشاهده پروفایل

استادیار

• Naval Hydrodynamics
• Ocean Renewable Energy
• Computational Fluid Dynamics
• +۵ مورد دیگر

Bradford Knight serves as an Assistant Professor in the Ocean Engineering Department at the University of Rhode Island, specializing in naval hydrodynamics and ocean renewable energy through advanced Computational Fluid Dynamics (CFD) and data-driven modeling techniques. His educational background includes: Ph.D. in Naval Architecture & Marine Engineering, University of Michigan (2021) M.S.E. in Aerospace Engineering, University of Michigan (2020) M.S.E. in Naval Architecture & Marine Engineering, University of Michigan (2018) B.S.E. in Aerospace Engineering, University of Michigan (2012) B.S.E. in Mechanical Engineering, University of Michigan (2012) Dr. Knight's research spans naval hydrodynamics, ocean renewable energy systems, vessel maneuvering/seakeeping dynamics, and hydrokinetic turbine optimization. He integrates machine learning with CFD to model complex fluid-structure interactions, particularly focusing on hull-propeller-rudder systems and marine energy converters under realistic flow conditions. Analysis of his 15 most recent publications (2022-2025) reveals evolving research trajectories: increasing emphasis on AI-enhanced hydrodynamic modeling (notably Gaussian process regression for propeller/rudder systems), multi-fidelity CFD frameworks for turbine optimization, and real-time wave forecasting systems. His work demonstrates consistent focus on practical marine applications while advancing computational methodologies for renewable energy and naval architecture. Dr. Knight actively recruits graduate students for research in computational marine hydrodynamics and renewable energy systems. His current projects involve hydrokinetic turbine design optimization, ship maneuvering simulation in waves, and novel energy harvesting systems, supported by computational infrastructure at URI's Narragansett Bay Campus.

Artem Kaznatcheevمشاهده پروفایل

استادیار

• Evolutionary Biology
• Theoretical Computer Science
• Computational Complexity
• +۵ مورد دیگر

Artem Kaznatcheev is an Assistant Professor at Utrecht University in the Department of Mathematics and Department of Information and Computing Sciences within the Science faculty. His research bridges theoretical computer science and evolutionary biology to analyze biological and social systems through an algorithmic lens. Current role since January 2023 Recruiting PhD students and postdocs Previously: James S. McDonnell postdoctoral fellow at University of Pennsylvania His work focuses on: Computational complexity of evolution Evolutionary game theory Algorithmic biology Mathematical modeling of cancer dynamics Cultural evolution of science Selected article trends show: Interdisciplinary integration of computer science and cancer biology Key themes: fitness landscapes, evolutionary games, treatment optimization 2021-2020 publications dominate Mathematical formalisms applied to biological and social phenomena Scientific contributions include: James S. McDonnell Foundation Independent Postdoctoral Fellowship 2019 Genetics paper on computational complexity as evolutionary constraint 2017 Nature Ecology & Evolution study on fibroblast-drug interactions in cancer Collaborative environments: Worked with Theory, Evolution and Games Group Previous affiliations: Oxford University, University of Pennsylvania, Moffitt Cancer Center, McGill University Developed teaching roles at Oriel College (Oxford)

Praveen Lingaمشاهده پروفایل

استاد

• Clathrate (Gas) Hydrates
• Energy Storage
• Carbon Dioxide Capture and Storage (CCS)
• +۷ مورد دیگر

Praveen Linga is a Professor in the Department of Chemical and Biomolecular Engineering at the National University of Singapore (NUS) , where he has served since 2010. He held leadership roles as Vice Dean (Industry-Relation, Innovation & Enterprise) and Vice Dean (Communications & Outreach) at NUS's College of Design and Engineering . Dr. Linga co-leads the Centre for Energy Research & Technology (CERT) at NUS and maintains visiting professorships at institutions in India, China, and Thailand. His research focuses on clathrate hydrates for clean energy storage , CO₂ capture , and environmental stewardship , aligning with UN Sustainable Development Goals 6, 7, and 13. The Linga Lab combines fundamental and applied studies to optimize hydrate formation/dissociation kinetics and explore energy recovery from natural gas hydrates. Recent publications highlight innovations in CO₂ hydrate kinetics using amino acid promoters, methane storage in seawater systems, and hydrogen hydrate stability analysis. His work appears in leading journals like Energy & Fuels , Applied Energy , and Chemical Engineering Journal , with over 200 peer-reviewed papers and significant citation impact (h-index 77). Dr. Linga is recognized as a Highly Cited Researcher (Clarivate, 2018-2024), NRF Investigator (S$3.5M grant), and recipient of multiple Best Paper Awards from Applied Energy and Advances in Applied Energy . He serves as Executive Editor of Energy & Fuels and sits on editorial boards of 12 journals. Linga Lab's work has been featured in global media (Chemistry World, Science et Vie) and recognized by Research.com as #9 in Singapore's engineering scientists. His research bridges chemical engineering fundamentals with large-scale energy applications, particularly in hydrate-based CO₂ sequestration and unconventional gas storage.

• Quantum Computing
• Atomic Electronics
• Quantum Devices
• +۲ مورد دیگر

Professor Michelle Y Simmons AO is a Laureate Fellow and Director of the Centre of Excellence for Quantum Computation and Communication Technology at UNSW Sydney. She founded Silicon Quantum Computing (SQC), Australia's first vertically integrated quantum computing company, and pioneered atomic electronics by creating devices in silicon with atomic precision. Research focuses on quantum computing, spin qubits, and atomic-scale engineering Key achievements: first quantum gates with donor atoms, 3D atomic chip architecture Recent publications highlight advancements in silicon qubit fabrication, quantum coherence, multi-qubit control, and noise mitigation. These works emphasize scalable architectures and practical quantum computing solutions. Scientific awards include: 2023 Prime Minister’s Prize for Science 2023 Swiss Erna Hamburger Prize 2022 AmCham Alliance Award 2021 Bakerian Medal 2018 Australian of the Year 2017 L’Oréal-UNESCO Laureate Her leadership in quantum research has secured major industry partnerships (CBA, Telstra, Commonwealth Bank) and driven the development of silicon-based quantum technologies. Current work involves optimizing spin qubit performance and exploring applications of quantum computing in materials science and information processing.

• Software Engineering
• Smart Cities
• Internet of Things
• +۴ مورد دیگر

Siobhán Clarke is a Professor at the School of Computer Science and Statistics, Trinity College Dublin, specializing in software systems for smart urban environments . Her work addresses dynamic software adaptation in large-scale, mobile IoT ecosystems , with a focus on QoS optimization and collaborative agent models . Director, Enable : National SFI IoT Research Programme Director, Future Cities Centre for Smart & Sustainable Cities Co-Lead, ADVANCE : SFI Centre for Advanced Networks Co-PI, CONNECT (Future Networks) and Lero (Software Research) Her research spans smart city infrastructure , edge computing , and multi-agent coordination , informed by 15+ years of publications on service-oriented architectures , QoS prediction , and self-adaptive systems . Key project contributions include DIVERSIFY (2016) and TRANSFoRm (2015). Scientific awards include election to the Royal Irish Academy (2023) and a Best Student Paper at IEEE ICWS 2011. She has supervised 20+ PhD/MSc students, including Fan Li (2020: SLA Negotiation Systems), Gary White (2020: IoT QoS Forecasting), and Andrei Palade (2019: Stigmergic Optimization).

Jackson Craneمشاهده پروفایل

استادیار

• Renewable Energy Conversion
• Electrocatalysis
• Low-Carbon Combustion
• +۳ مورد دیگر

Assistant Professor Jackson Crane at Queen's University (Smith Engineering, Mechanical and Materials Engineering) specializes in renewable energy conversion technologies, electrocatalysis, and low-carbon combustion. His research spans detonation fundamentals for high-efficiency engines and CO2-reduction electrocatalysis for alternative fuel synthesis. Education: SB (MIT), MSc & PhD (Stanford), Postdoc (Queen's University) His research combines electrochemical CO2 conversion with detonation dynamics , focusing on multiphysics modeling and experimental validation. Current projects include: High-pressure CO2 reduction systems Detonation propagation in curved channels Pulse electrolysis for stable CO2 reduction Scientific awards include: Bernard Lewis Fellowship (2024) NSF Graduate Research Fellow (Stanford) Stanford Graduate Fellow

Feng Chenمشاهده پروفایل

دانشیار بالینی

• Operations Management
• Process Analysis
• Supply Chain Management
• +۳ مورد دیگر

Feng Chen is a Clinical Associate Professor at the Marshall School of Business, University of Southern California, affiliated with the Department of Data Sciences and Operations. She teaches courses in operations management and data analytics for decision-making, with a Ph.D. in Business Administration from USC. Education: Ph.D. in Business Administration from University of Southern California Her research focuses on process analysis , supply chain analytics , and behavioral operations decision-making . She has designed and instructed advanced courses on business analytics, statistics, and operations optimization. Recent publications demonstrate expertise in atmospheric data assimilation , satellite meteorology , and weather system modeling . Key methodologies include multi-sensor integration, cloud-dependent observation-error modeling, and numerical prediction systems for tropical weather phenomena. Contact: fchen@marshall.usc.edu | Phone: 213-740-6319