جست‌وجوی استاد و پژوهشگر

• Electrical Power Systems
• Electrical Distribution Systems
• Distributed Generation
• +۱۲ مورد دیگر

Rachid Cherkaoui is a Senior Scientist at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering, specifically within the Department of Electrical Engineering. He is actively associated with research units SEL-ENS, EDEY-ENS, and DESL, contributing to the Distributed Electrical Systems Laboratory (DESL). His work focuses on advanced power system optimization, smart grids, and energy market modeling. Ph.D. in Electrical Engineering, EPFL, 1992 M.S. in Electrical Engineering, EPFL, 1983 Dr. Cherkaoui's research interests include electrical power and distribution systems, distributed generation, energy storage, electricity market deregulation, and power system vulnerability mitigation. His work bridges theoretical modeling and real-world applications, particularly in flexibility provision, grid resilience, and market integration of renewable energy. His recent publications (2020–2025) reflect a strong focus on smart grid technologies, energy storage integration, and market mechanisms. Key themes include optimal dispatch of hybrid systems, TSO-DSO coordination, frequency control, and stochastic optimization under uncertainty. His work is frequently published in top-tier journals such as IEEE Transactions on Power Systems and IEEE Transactions on Smart Grid. ABB Swiss Award '83 Senior Member, IEEE Member, CIGRE Task Forces C5-2 IEEE Swiss Chapter Officer since 2005 Dr. Cherkaoui actively supervises doctoral students and collaborates extensively with researchers like Mario Paolone. He has contributed to numerous projects funded by industry, CTI/Innosuisse, and Horizon 2020. His research includes experimental validation and real-time control systems, particularly in hydropower and battery storage applications. He is also involved in national and international energy strategy discussions, including Switzerland's path to carbon neutrality.

LING Chun Kaiمشاهده پروفایل

استادیار

• Artificial Intelligence
• Decision Making & Planning
• Machine Learning
• +۱۳ مورد دیگر

LING Chun Kai is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His research focuses on multiagent systems, computational game theory, and machine learning applications in adversarial real-world domains like cybersecurity and logistics. Educational background includes a PhD in Computer Science (2017-2023) from Carnegie Mellon University and a First Class BEng in Computer Engineering (2015) from NUS. Previously, he was a Postdoctoral Research Scientist at Columbia University. Current research interests span computational game theory, machine learning for multi-agent systems, equilibrium characterization in imperfect information settings, and applications in network security, logistics, and recreational games. Key methodological contributions include scalable algorithms for game solving, differentiable game solvers, and copula-based statistical modeling. Recent publications focus on attacker-defender graph games, language negotiation agents, and modeling games with incomplete information. Collaborations include researchers from Columbia University, Carnegie Mellon, and institutions working on GameSec, AAAI, Neurips, and ICML venues. Scientific Awards: IJCAI 2018 Distinguished Paper Award GameSec 2023 Best Paper Award GameSec 2024 Best Paper Award Singapore Teaching and Academic Research Talent Scheme (2024) Teaching includes courses on AI Planning and Decision Making (CS4246, CS5446) and Advanced Topics in Artificial Intelligence (CS6208).

Tomasz Strzaleckiمشاهده پروفایل

استاد

• Decision Theory
• Behavioral Economics
• Microeconomics
• +۴ مورد دیگر

Tomasz Strzalecki is a Professor in the Department of Economics at Harvard University. His research centers on decision theory, with a focus on ambiguity aversion , temporal preferences , stochastic choice , and bounded rationality . He earned his PhD in Economics from Northwestern University in 2008. Education: PhD in Economics (2008), Northwestern University His scholarly work spans theoretical and applied economics, including key contributions to random utility models , dynamic decision-making , and neuroeconomic modeling . Recent publications, such as Stochastic Choice Theory (2025) and Variational Bayes and non-Bayesian Updating (2024), reflect his ongoing exploration of Bayesian inference and behavioral deviations. Earlier work in Econometrica and American Economic Review established foundational models for choice aversion , time inconsistency , and ambiguity evaluation . Tomasz’s research has been published in top journals like Econometrica , American Economic Review , and Proceedings of the National Academy of Sciences , covering themes such as probabilistic sophistication , decision timing , and collective action in development economics. His co-authors include prominent economists like Drew Fudenberg, Mira Frick, and Larry Epstein.

Sheryl Graceمشاهده پروفایل

دانشیار

• Aerodynamics
• Fluid Dynamics
• Acoustics
• +۴ مورد دیگر

Sheryl Grace is an Associate Professor of Mechanical Engineering at Boston University, leading the Unsteady Fluid Mechanics & Acoustics Laboratory (UFMAL). Her primary appointment is in the Department of Mechanical Engineering within the College of Engineering. She holds a PhD from the University of Notre Dame. Her research focuses on unsteady aerodynamics, aeroacoustics, and fluid-structure interactions, with applications in aerospace systems, propulsion technologies, and biological acoustics. Notable projects include NASA-funded work on quieter vertical lift vehicles and computational modeling of gerbil hearing mechanics. Professor Grace’s research interests span aerodynamics, fluid dynamics, and acoustics. She develops analytical and computational models to predict sound and vibration generated by unsteady flows interacting with solid structures. Recent studies include noise reduction in aircraft wings, turbine blade fatigue analysis, and acoustic scattering in gerbil ears. Her work bridges theoretical models with practical engineering solutions, emphasizing cost-effective predictive tools for next-generation systems. Her publications highlight advancements in shock-droplet interactions, cavitation modeling, and machine learning applications in aeroacoustics. Collaborative projects include multi-institutional efforts to address urban air vehicle noise challenges. While no explicit awards are listed, her contributions to computational acoustics and fluid dynamics are recognized through extensive peer-reviewed output. Advising and grants: Professor Grace leads the UFMAL lab and has secured funding from agencies like NASA. Her research integrates fluid mechanics, acoustics, and computational methods to address industrial and environmental noise issues. She collaborates across disciplines, including mechanical engineering, aerospace, and biomedical acoustics.

Vinayak Dixitمشاهده پروفایل

استاد

• Transportation Risk Analysis
• Highway Safety
• Travel Time Uncertainty
• +۶ مورد دیگر

Professor Vinayak Dixit serves as the IAG Chair of Risk in Smart Cities and Director of the Research Centre for Integrated Transport Innovation (rCITI) at the University of New South Wales (UNSW), within the School of Civil and Environmental Engineering. With a distinguished career spanning academia and research leadership, Professor Dixit has established himself as a leading expert in transportation risk analysis and smart city infrastructure. Professor Dixit's research focuses on studying risk in transportation infrastructure systems, with particular emphasis on highway safety, travel time uncertainty, and resilience against natural and man-made disasters. His work integrates cutting-edge approaches including quantum computing applications for transportation network optimization, analysis of connected and automated vehicles, and development of models for transportation resilience. His research interests span multiple disciplines, bridging civil engineering, transportation science, risk analysis, and computational methods. Professor Dixit has secured significant research funding from prestigious organizations including the United States National Science Foundation, Federal Highway Administration, and the Strategic Highway Research Program of the Transportation Research Board. His leadership extends to directing the Research Centre for Integrated Transport Innovation (rCITI), where he oversees a comprehensive research program addressing critical transportation challenges in smart cities through multiple focus areas including Connected Mobility Services, Deep Data and Digitization, Engineering Smart Cities & Logistics, Human-Centred And Automated Systems Design, and Integrated Infrastructure Strategic Planning. Professor Dixit previously served as the Associate Director of Research for the Gulf Coast Centre for Evacuation and Transportation Resiliency at Louisiana State University, where he founded the Driving Simulator Laboratory in collaboration with other faculty members. This demonstrates his longstanding commitment to innovative research infrastructure development and interdisciplinary collaboration across engineering, economics, computer science, and urban planning to address complex transportation challenges in the 21st century.

Noel T. Clemensمشاهده پروفایل

استاد

• Aerothermodynamics
• Fluid Mechanics
• Hypersonics
• +۷ مورد دیگر

Noel T. Clemens serves as a Professor and holds the prestigious Clare Cockrell Williams Centennial Chair in Engineering within the Aerospace Engineering and Engineering Mechanics Department at the University of Texas at Austin's Cockrell School of Engineering. He has been a faculty member since 1993 and served as department chair from 2012 to 2020. His research laboratory is part of the Center for Aeromechanics Research (CAR) where he directs the Flowfield Imaging Laboratory. Dr. Clemens' research focuses on experimental investigations of hypersonic flows, turbulent combustion, and advanced optical diagnostic techniques. His current work emphasizes 3D shock wave/boundary layer interactions, inlet unstart control, flashback in high-pressure combustors, turbulent combustion with non-equilibrium effects, and high-temperature ablation phenomena. He has pioneered laser-based measurement techniques for extreme environments, particularly for hypersonic flight applications where conventional measurement approaches fail. His recent publication record through 2025 demonstrates continued leadership in experimental fluid dynamics, with particular emphasis on plasma diagnostics for ablation studies, shock/boundary layer interaction physics, and advanced optical measurement techniques for extreme environments. The research spans fundamental fluid mechanics investigations to applied aerospace engineering problems relevant to hypersonic vehicle development. Elected to National Academy of Engineering (2024) AIAA Aerodynamic Measurement Technology Award (2022) Elected AIAA Fellow (2019) National Science Foundation Presidential Faculty Fellow (1996) Editor-in-Chief of Experiments in Fluids (2009-2013) Fellow of the American Physical Society Dr. Clemens has secured substantial research funding for his experimental investigations in hypersonics and combustion, leading multiple major research projects with government and industry partners. His laboratory facilities include advanced wind tunnels and state-of-the-art optical diagnostic systems for high-speed flow visualization. The Flowfield Imaging Laboratory at UT Austin serves as a national resource for advanced flow measurement techniques development. As an educator, he teaches core courses in compressible flow, viscous flow, combustion, experimental methods, and laser diagnostic techniques, training the next generation of aerospace engineers in both fundamental principles and cutting-edge measurement technologies.

Jaime Peraireمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Finite Element Methods
• Aerodynamics
• +۷ مورد دیگر

Jaime Peraire is the H.N. Slater Professor of Aeronautics and Astronautics at MIT, affiliated with the School of Engineering. He leads research in computational mechanics, aerodynamics, and numerical methods for partial differential equations, with key roles as former Department Head (2011-2018) and Director of the Aerospace Computational Design Lab (1993-2011). His expertise spans finite element methods, shock capturing algorithms, and high-order numerical techniques applied to hypersonic flows, space weather, and metamaterials. Education includes a Ph.D. from the University of Wales (1986) and engineering degrees from the University of Barcelona (1983, 1987). He holds prestigious awards like the T.J. Hughes Medal (2015) and the Ildefons Cerdá Medal (2015). His work bridges computational science and engineering, with contributions to discontinuous Galerkin methods, mesh adaptivity, and GPU-accelerated simulations. Research interests emphasize high-fidelity modeling of compressible flows, plasma dynamics, and terahertz spectroscopy. Notable projects include MIT’s space weather modeling initiative and metamaterial fabrication using atomic layer lithography. His labs collaborate across MIT’s Schwarzman College of Computing, IDSS, and CCSE to advance computational tools for aerospace and environmental systems. Awards: Over 10 major prizes, including NASA Exceptional Achievement (1997) and IACM Young Researchers Award (1998). Grants/Advising: Led NSF-funded space weather projects and advised numerous PhD students in computational engineering. Labs: Aerospace Computational Design Lab, MIT Schwarzman College of Computing collaborations.

Asuman Ozdaglarمشاهده پروفایل

استاد

• Optimization
• Machine Learning
• Game Theory
• +۷ مورد دیگر

Asuman Ozdaglar is the MathWorks Professor of Electrical Engineering and Computer Science and Department Head of EECS at MIT. She also serves as Deputy Dean of Academics for the MIT Stephen A. Schwarzman College of Computing. Her research focuses on large-scale networked systems, including optimization, game theory, social networks, and distributed algorithms. Education: BS in Electrical and Electronics Engineering from Middle East Technical University (1996), SM (1998) and PhD (2003) in Electrical Engineering and Computer Science from MIT. Research emphasizes nonlinear optimization, machine learning, and network economics. She leads work on robust algorithms, misinformation dynamics, and networked systems. Affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Operations Research Center (ORC). Her contributions span theoretical and applied domains, including distributed optimization methods, social network analysis, and privacy-preserving data mechanisms. Active in shaping academic policy through her roles in the College of Computing.

• Computational Fluid Dynamics
• Scientific Machine Learning
• Data-Driven Modeling
• +۳ مورد دیگر

Shaowu Pan is an Assistant Professor of Aerospace Engineering at Rensselaer Polytechnic Institute (RPI), affiliated with the Future of Computing Institute (FOCI) and the Scientific Computation Research Center (SCOREC). He holds a Ph.D. in Aerospace Engineering and Scientific Computing from the University of Michigan and completed a postdoctoral fellowship at the University of Washington’s AI Institute in Dynamic Systems. Education: Ph.D., University of Michigan, 2021 M.S., University of Michigan, 2015 B.E. & B.S., Beihang University, 2013 Research Interests: His work focuses on the intersection of computational fluid dynamics, data-driven modeling, and scientific machine learning. Key areas include operator-theoretic modeling of fluid flows, generative AI for physical systems, and physics-informed neural networks. He develops novel algorithms for reduced-order modeling and stability-preserving surrogate models, with applications in turbulence, plasma physics, and aerodynamics. Key Contributions: Developed PyKoopman , an open-source Python package for Koopman operator approximation. Pioneered mesh-agnostic representation methods like Neural Implicit Flow for spatio-temporal data. Advanced physics-informed neural networks for solving Grad-Shafranov equations and plasma equilibrium problems. Awards & Recognition: John Tichy Junior Faculty Travel Grant (2024) Chinese Outstanding Student Abroad Award (2021) Richard and Eleanor Towner Prize Nominee (2019) Teaching & Mentorship: He teaches courses like MANE 2110: Numerical Methods and Programming for Engineers and mentors multiple Ph.D., master’s, and undergraduate students. His doctoral committee involvement spans interdisciplinary projects in fluid dynamics and AI. Grants & Software: Lead PI for NSF-funded projects on neural representation learning for turbulent flows. Developed software tools like spKDMD and Warp-DG for dynamics analysis and CFD simulations. Labs & Collaborations: Collaborates with institutions like Los Alamos National Laboratory and actively participates in conferences (e.g., AIAA SciTech, SIAM). His research bridges computational science, machine learning, and fluid dynamics to address complex nonlinear systems.

Salem Lahlouمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• GFlowNets
• +۷ مورد دیگر

Salem Lahlou is an Assistant Professor in the Machine Learning Department at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), having joined in September 2024. He previously served as a Senior Researcher at the Technology Innovation Institute (TII) in 2024. His academic background includes a PhD from Mila and Université de Montréal (UdeM) under Yoshua Bengio (2023), with prior studies in applied mathematics at École Polytechnique and statistical learning at École Normale Supérieure Paris-Saclay. His research focuses on developing more capable and reliable AI systems through three interconnected pillars: Novel Method Development : Core contributions to Generative Flow Networks (GFlowNets), uncertainty estimation techniques (DEUP), and curriculum learning frameworks Large Language Model Advancement : Enhancing reasoning capabilities and alignment through preference optimization and trace-based learning Community Tooling : Creation of torchgfn library for GFlowNets and benchmarks including BabyAI, FinChain, and LLM-BabyBench Core research areas span Machine Learning, GFlowNets, Uncertainty Estimation, LLM Reasoning, Reinforcement Learning, and AI for Science. Recent publications (2023-2025) demonstrate strong emphasis on GFlowNet theory/improvements (8+ papers), LLM reasoning evaluation (FinChain, LLM-BabyBench), uncertainty quantification, and societal AI impacts. Key application domains include mathematical reasoning, financial systems, privacy preservation, and cognitive science. He currently advises graduate students including Junyi (privacy risks in SNNs) and Abhijith (LLM reasoning). His group collaborates with MBZUAI faculty (Nils Lukas, Alham Fikri, Mingming Gong, Martin Takac) and industry partners on projects involving Conversational AI, Personalization, and Affective AI.

Mark Crowleyمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +۶ مورد دیگر

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

• Macroeconomic modeling of health disorders
• Infectious disease economics
• Computable General Equilibrium (CGE) Modeling
• +۷ مورد دیگر

Dr Marcus Keogh-Brown is an Associate Professor in the Department of Global Health and Development within the Faculty of Public Health and Policy at the London School of Hygiene & Tropical Medicine (LSHTM). His position is split between research focusing on macroeconomic modeling of health and serving as Deputy Programme Director for the school's public health distance learning program. Education: BSc in Mathematics and Statistics, Queen Mary University of London (1995-1998) MSc in Computer Studies, University of Essex (1998-1999) PhD in "A Statistical Model of Internet Traffic," Queen Mary University of London (1999-2004) PGCILT Modules 1 and 2, London School of Hygiene and Tropical Medicine (2008-2012) Dr Keogh-Brown's research focuses on analyzing the macro-economic impact of health disorders and developing macro-economic models in health contexts. His areas of interest include infectious diseases (SARS, influenza, COVID-19, tuberculosis, malaria) and non-communicable diseases (Alzheimer's Disease, Dementia). He specializes in health-related applications of Computable General Equilibrium (CGE) Modeling with GAMS, with current work on health and macroeconomic modeling of COVID-19, tuberculosis, child labor, and health-related food policies. His publication record shows a strong trend toward integrated macroeconomic-epidemiological modeling, particularly for infectious disease outbreaks and public health interventions. Recent work focuses on tuberculosis in India, Covid-19 impacts in Pakistan, and food policy interventions like the UK Soft Drinks Industry Levy. His research consistently applies economic modeling frameworks to evaluate the health and economic impacts of disease and health policies across multiple countries including Ghana, India, Thailand, Myanmar, UK, and China. Grants: Current: "Modelling the health social care and macroeconomic impacts of dementia policies in the UK" (NIHR, 2025-2026) Current: "Co-designing food system fiscal policy for healthy people and planet" (University of Oxford, 2022-2025) Completed: "COVID-19 vaccine scenario analysis for health economic and social impacts" (WHO, 2022) Completed: "Evaluation of the impact of the UK industry levy of sugar-sweetened beverages" (University of Cambridge, 2017-2023) Completed: "Macroeconomic Burden of Alzheimers in China" (Jansen Global Services LLC, 2014-2015) Dr Keogh-Brown is affiliated with several research centers at LSHTM including the Malaria Centre, Global Health Economics Centre, and Centre for Mathematical Modelling of Infectious Diseases. His collaborative work spans multiple countries and addresses critical intersections between health, economics, and policy.

Gheorghe Craciunمشاهده پروفایل

استاد

• Mathematical Biology
• Dynamical Systems
• Chemical Reaction Networks
• +۳ مورد دیگر

Gheorghe Craciun is a Professor in the Department of Mathematics and the Department of Biomolecular Chemistry at the University of Wisconsin-Madison. His research focuses on mathematical and computational models in biology and medicine, particularly dynamical systems models of biological interaction networks. He has been a visiting researcher at the Max Planck Institute for Mathematics in the Sciences during the 2019-2020 academic year and has organized the Madison Workshops on Mathematics of Reaction Networks. Craciun's primary research interests include Mathematical Biology, Dynamical Systems, Chemical Reaction Networks, Computational Biology, Systems Biology, and Algebraic Geometry. He investigates systems of differential equations with polynomial right-hand sides, which are common in biochemical reaction networks, ecological interactions, and epidemiological models. His work often involves proving global stability, analyzing multistability, and characterizing steady states using tools from algebraic geometry and combinatorics. Recent publications demonstrate his focus on toric differential inclusions, endotactic networks, and the global attractor conjecture, extending to applications in biochemical networks and discrete Boltzmann equations. His extensive publication record reveals a strong trend toward algebraic and geometric methods for analyzing complex biological networks, with significant contributions to reaction network theory, stability analysis, and parameter characterization. Craciun's work bridges abstract mathematical concepts with practical applications in biochemistry, ecology, and medicine, including modeling vitellogenin production in trout and peptide mass distributions. He has collaborated extensively with international researchers including Alicia Dickenstein, Anne Shiu, Bernd Sturmfels, Casian Pantea, and Miruna-Stefana Sorea. In education, Craciun teaches graduate courses such as Math 703 and mentors students through the Madison Math Circle and Putnam Club, while organizing specialized workshops that foster collaboration in reaction network theory.

Alexander Westkampمشاهده پروفایل

استاد

• Matching Markets
• Mechanism Design
• Behavioral Economics
• +۲ مورد دیگر

Alexander Westkamp is a Professor in Economics at the University of Cologne since 2018. His research focuses on matching markets , mechanism design , and behavioral economics , with significant contributions to understanding stability, strategy-proofness, and exchange mechanisms in complex market structures. Current position: Associate Professor (W2) with tenure , University of Cologne Prior roles: Assistant Professor , Maastricht University (2013–2015); Visiting Scholar , Stanford University (2012–2013) Affiliated with interdisciplinary research clusters like ECONtribute: Markets & Public Policy , Germany’s first Cluster of Excellence in economics. His work has been published in top journals including the Journal of Political Economy , Games and Economic Behavior , and Theoretical Economics . Recent articles explore topics such as: Generalized matching with contracts and networks Stability and strategy-proofness in trading networks Tie-breaking mechanisms in priority-based matching systems Westkamp’s research often intersects with quantum computing and social behavior through collaborations at the University of Cologne’s Key Profile Area: Social and Economic Behaviour .

Joseph Francoisمشاهده پروفایل

استاد

• International Economics
• Trade Policy
• Globalization
• +۴ مورد دیگر

Joseph Francois is a Professor of Economics and Director at the World Trade Institute (WTI) , affiliated with the Economic Institute at the University of Bern. He previously served as Deputy Director of the NCCR Trade Regulation (2015–2017) and held professorships at Johannes Kepler Universität Linz, Erasmus University Rotterdam, and other institutions. His research spans international economics, trade policy, globalization, environmental economics, and computable general equilibrium (CGE) modeling. Key focus areas include cross-border production chains, trade in services, open economy competition policy, financial market integration, and the interplay between trade agreements and sustainability goals. Scientific distinctions include a Fellowship at the Centre for Economic Policy Research (London). His methodological expertise includes CGE modeling, econometric estimation of large nonlinear systems, and policy analysis of trade disputes, carbon border adjustments, and non-tariff measures. Education: Ph.D. in Economics, University of Maryland BA in Economics and History, University of Virginia He has contributed extensively to policy briefs and technical reports, particularly in analyzing trade impacts on employment, economic development, and environmental outcomes.