جست‌وجوی استاد و پژوهشگر

• Systems Biology
• Mathematical Biology
• Control Theory
• +۳ مورد دیگر

Dr. Irene Zorzan is a Research Fellow at the University of Surrey, affiliated with the Section of Molecular and Systems Biology within the School of Biosciences. She is part of the Faculty of Health and Medical Sciences and contributes to the Centre for Mathematical and Computational Biology. Her work bridges systems biology, control theory, and mathematical modeling to study complex biological systems. Dr. Zorzan's research focuses on mathematical modeling of gene regulatory networks, bacterial stress responses, and the application of control theory to biological systems. Specific interests include bistability mechanisms in mycobacteria, robust analysis of biochemical systems, and the design of synthetic biological circuits. She also investigates stabilization strategies for compartmental systems and consensus protocols in multi-agent networks with positivity constraints. Her recent publications highlight contributions to understanding microbial stress adaptation, optimizing control strategies in positive systems, and analyzing spatial emergent behaviors in bacterial cells. Her interdisciplinary approach integrates computational methods with experimental insights from molecular biology and microbiology.

Anastasios Karantouniasمشاهده پروفایل

دانشیار

• Macroeconomics
• Fiscal Policy
• Monetary Policy
• +۴ مورد دیگر

Anastasios Karantounias is an Associate Professor of Economics at the School of Economics, University of Surrey. He also holds several prestigious affiliations including being an Academic Visitor at the Bank of England, an Associate of the Centre for Macroeconomics (LSE branch), a Fellow of the Institute for Sustainability at the University of Surrey, and a member of the Macro Finance Society. Dr. Karantounias received his academic training at New York University, earning his PhD in Economics in 2008 and a Master's degree in Economics in 2004. He completed his undergraduate studies at the Athens University of Economics and Business in Athens, Greece, where he earned his Bachelor's degree in Economics in 2001. His major research interests focus on macroeconomics with particular emphasis on optimal fiscal and monetary policy, macro-finance, ambiguity, imperfect information, and optimal carbon taxation. His work bridges theoretical macroeconomic frameworks with practical policy applications, often incorporating behavioral elements and uncertainty into traditional models. He has published extensively in top journals including the Review of Economic Studies, American Economic Journal: Macroeconomics, Journal of Economic Theory, and Theoretical Economics. Dr. Karantounias' recent publications demonstrate a clear trajectory toward increasingly sophisticated modeling of uncertainty in macroeconomic policy. His work on model uncertainty, fiscal policy under ambiguity, and behavioral factors in macroeconomic outcomes represents cutting-edge research at the intersection of macroeconomics and decision theory. His most recent work extends into climate policy, examining optimal carbon taxation in a global economy context. Dr. Karantounias has been actively involved in the academic community through organizing major workshops including the Surrey Workshop on Macroeconomics (May 2022), the Macroeconomics Network in the Southwest Workshop (November 2023), and the Bristol-Surrey Workshop in Macroeconomics (March 2024). He has also organized multiple contributed sessions at the Annual Meetings of the American Economic Association (2013, 2017, 2019, 2025). Prior to joining the University of Surrey, Dr. Karantounias worked as a research economist in the Research Department of the Federal Reserve Bank of Atlanta. He also gained research experience at the Federal Reserve's Board of Governors and the European Central Bank. He has served as a Visiting Scholar at Northwestern University and as a Visiting Professor at LUISS Guido Carli and the Einaudi Institute for Economics and Finance. His previous teaching appointments include Emory University.

Michael S Landyمشاهده پروفایل

استاد

• Sensory Decision-Making
• Multisensory Integration
• Spatial Vision
• +۵ مورد دیگر

Michael S Landy is a Professor of Psychology and Neural Science at New York University, affiliated with the College of Arts & Science. He holds a Ph.D. in Computer and Communication Sciences from the University of Michigan (1981) and has been at NYU since 1981, progressing through academic ranks to full Professor in 1997. His research focuses on visual perception, action, and computational modeling, with key areas including sensory decision-making, multisensory integration, spatial vision, depth perception, and motor control. His lab explores how humans combine sensory cues (e.g., visual, tactile, auditory) under uncertainty and how these processes interact with neural mechanisms. Recent work addresses causal inference in multisensory perception, neural coding of motion signals, and Bayesian models of perception. He serves as director of the Landy Lab, advancing interdisciplinary research at the intersection of psychology, neuroscience, and computer science. Education: Ph.D., Computer and Communication Sciences, University of Michigan (1981) M.S., Computer and Communication Sciences, University of Michigan (1976) B.S., Columbia University (1974) Research Interests: Sensory Decision-Making: How humans set perceptual criteria and estimate confidence under uncertainty. Cue Integration: Optimal combination of visual, tactile, and auditory information (e.g., depth cues). Visual Action: Visually guided movements (e.g., eye/limb control under risk and cost constraints). Depth Perception: Neural and computational mechanisms for estimating 3D layout from binocular, motion, and pictorial cues. Neural Models: Linking psychophysics with neural responses in visual cortex (e.g., fMRI studies of texture and motion processing). Lab & Collaborations: The Landy Lab conducts interdisciplinary research with collaborations in neuroscience, computer science, and mathematics. Current projects include studying causal inference in multisensory systems, neural mechanisms of motion perception, and Bayesian models of perception-action cycles.

Sujoy Mukerjiمشاهده پروفایل

استاد

• Decision Making under Ambiguity
• Bounded Rationality
• Economic Theory
• +۳ مورد دیگر

Sujoy Mukerji is a Professor at Queen Mary University of London's School of Economics and Finance. He holds a PhD from Yale University, following undergraduate studies at Presidency College, Calcutta, and an MA from the Delhi School of Economics. His research focuses on decision making under ambiguity, bounded rationality, and their applications in economic contexts, particularly in financial markets and game theory. He has contributed to foundational frameworks like the Smooth Ambiguity Model and explored ambiguity's role in economic cycles and market behaviors. Editorial roles include co-editing Mathematics and Financial Economics and serving as an associate editor for journals such as Econometrica and Theory and Decision . His work bridges theoretical economics with practical applications, addressing challenges like the equity premium puzzle and ambiguity in dynamic games. Recent projects include analyzing portfolio holdings under ambiguity and experimental validations of decision models. Key research trends in his articles emphasize ambiguity's impact on strategic interactions, market allocations, and macroeconomic phenomena. His contributions have advanced understanding of how uncertainty shapes economic decisions and outcomes.

Christopher Tysonمشاهده پروفایل

استاد

• Economic Theory
• Behavioral Economics
• Decision Making
• +۶ مورد دیگر

Christopher Tyson is a Professor in the School of Economics and Finance at Queen Mary University of London. He joined the university in 2006 after completing a postdoctoral fellowship at Nuffield College, Oxford. His research focuses on economic theory, particularly individual decision making, revealed preference analysis, and models of bounded rationality and cognition. Additional interests include game theory, bargaining, intertemporal choice, and evolutionary models. Christopher Tyson holds a Bachelor of Arts (AB) from Princeton University (1998) and a Doctor of Philosophy (PhD) from the Stanford Graduate School of Business (2004). His research interests are centered around economic theory, with a focus on: Individual decision making mechanisms Revealed preference analysis methodologies Models of bounded rationality and cognitive processes Game theory applications Bargaining strategies Intertemporal choice frameworks Evolutionary economic models His publications explore the intersection of decision theory and behavioral economics, with a focus on cognitive heterogeneity, satisficing models, and preference analysis. Recent work emphasizes revealed preference analysis and the application of mathematical models to economic decision-making processes. Christopher Tyson advises students in economic theory and related fields, though specific advisee names are not listed here. He has contributed to various academic grants and research initiatives, though specific details are not provided in the available materials. He is actively involved in the research community at Queen Mary University of London, collaborating with colleagues on interdisciplinary projects within the School of Economics and Finance.

• Market Design
• Auction Theory
• Microeconomic Theory
• +۳ مورد دیگر

Justin Burkett is an Associate Professor and Interim Director of Doctoral Programs at the School of Economics, Ivan Allen College of Liberal Arts, Georgia Institute of Technology. He joined Georgia Tech in 2018 after serving as an Assistant Professor at Wake Forest University and completing his PhD in Economics at the University of Maryland, College Park. His research focuses on microeconomic theory, particularly market design, which aims to improve real-world market institutions like public school seat allocation and Treasury bond markets. His work has been published in journals such as Journal of Economic Theory and Theoretical Economics . His academic background includes a B.A. from Washington University in Saint Louis and a Ph.D. from the University of Maryland. His research interests span auction theory, contract design, and institutional economics, emphasizing practical solutions to market inefficiencies. Dr. Burkett’s recent work explores topics such as intertemporal allocation under uncertainty, data-driven contract mechanisms, and the impact of prosumer duality in energy markets. His experimental studies analyze auction dynamics under endogenous budget constraints. He currently holds no listed scientific awards but has contributed significantly to auction theory and market design through his publications and academic leadership roles.

Malintha Fernandoمشاهده پروفایل

پژوهشگر ارشد

• Multi-Robot Systems
• Distributed Control
• Autonomous Systems
• +۴ مورد دیگر

Malintha Fernando is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology in Stockholm, Sweden. His current project focuses on Designing Interaction-Aware Heterogeneous Multi-Robot Systems , aiming to develop scalable distributed control policies for multi-robot systems in dynamic environments. He holds a PhD from Indiana University (2023) and an undergraduate degree from the University of Moratuwa, Sri Lanka. Prior to KTH, he served as a visiting lecturer in Machine Learning at Indiana University and completed an internship at Open Robotics. Education: PhD in Robotics/Control Systems, Indiana University, Bloomington, USA (2023) Bachelor’s degree in Engineering, University of Moratuwa, Sri Lanka Research Interests: Malintha’s work emphasizes cooperative control policies for multi-drone systems, particularly in scenarios with communication failures or dynamic environments. His research addresses challenges in humanitarian aid, disaster response, and urban air mobility (UAM) applications. He explores frameworks to balance task prioritization in real-time, minimizing human bias in system design. Key areas include: Decentralized decision-making in multi-agent systems Swarm intelligence and UAV coordination Robust control under uncertainty Grants & Supervision: His fellowship is hosted by KTH’s Department of Mathematics, under the supervision of Assistant Professor Silun Zhang (Optimization and System Theory) and Professor Petter Ögren (Robotics, Perception and Learning). The project aligns with Digital Futures’ mission to address societal challenges through digital innovation. Labs & Teams: Malintha is affiliated with the Division of Optimization and System Theory and the Robotics, Perception and Learning (RPL) group at KTH, contributing to cross-disciplinary research in robotics and control systems.

David Mguniمشاهده پروفایل

مدرس

• Multi-Agent Systems
• Reinforcement Learning
• Game Theory
• +۳ مورد دیگر

Dr. David Mguni is a Lecturer in Computer Science at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. His research focuses on multi-agent systems, reinforcement learning, game theory, and decision-making under uncertainty. He holds a PhD in applied mathematics from University College London and prior degrees from the University of Cambridge and the University of London. Before academia, he was a Principal Scientist at Huawei, leading the Multi-Agent Systems team in London. His work bridges theoretical foundations with practical applications, particularly in strategic decision-making and autonomous systems. He teaches the ECS656U/ECS796P Distributed Systems course and supervises students in reinforcement learning, game theory, and optimization. Research interests include non-zero-sum game frameworks, safe reinforcement learning (e.g., SAUTE RL), and reward shaping techniques. His publications span venues like AAMAS, NeurIPS, and IJCAI, addressing challenges in multi-agent coordination, adversarial environments, and algorithmic efficiency. Collaborations involve designing scalable methods for large systems and integrating language models into decision-making processes. David is part of Queen Mary’s Centre for Multimodal AI, contributing to projects on socially-attentive policies, risk-aware systems, and distributed optimization. His recent work emphasizes safety in multi-agent learning (e.g., SAUTE RL), variance reduction in estimator models, and frameworks for managing adversarial scenarios. He actively seeks PhD candidates to explore reinforcement learning and game-theoretic applications.

Michele Cucuzzellaمشاهده پروفایل

دانشیار

• Power Systems
• Control Systems
• DC Microgrids
• +۳ مورد دیگر

Prof. Michele Cucuzzella is an Associate Professor at the University of Groningen’s Faculty of Science and Engineering, Department of Discrete Technology and Production Automation. He holds a visiting professorship at Hiroshima University. His research focuses on control systems, DC microgrids, and renewable energy integration. He has contributed to over 65 publications, with notable work in IEEE Transactions on Control Systems Technology and Automatica. His research addresses challenges in distributed control, passivity-based methods, and robust stability of power networks. He received the IEEE Outstanding Paper Award (2020) for his work on consensus algorithms in DC microgrids. His work bridges theoretical control advancements with practical applications in smart grids and district heating systems. Research Interests: - DC Microgrid Control (voltage regulation, distributed optimization) - Passivity-Based Control (for nonlinear systems, sampled-data stabilization) - Energy Systems (district heating, renewable integration) - Robust Control (sliding mode techniques, uncertain dynamics) - Networked Systems (multi-agent consensus, game-theoretic approaches) Awards: IEEE Transactions on Control Systems Technology Outstanding Paper Award (2020) Key Contributions: Prof. Cucuzzella’s research emphasizes scalable solutions for modern energy networks. He has developed frameworks for voltage control in DC microgrids, robust stability under ZIP loads, and adaptive control for district heating systems. His work on passivity and sliding mode control addresses practical challenges in energy systems, balancing theoretical rigor with real-world applicability.

Scott J. McCormackمشاهده پروفایل

استادیار

• Materials Science
• Crystallography
• Thermodynamics
• +۵ مورد دیگر

Scott J. McCormack is an Assistant Professor in the Department of Materials Science and Engineering at the University of California, Davis. His research focuses on materials in extreme environments, with an emphasis on crystallography, thermodynamics, and synthesis of complex oxides, carbides, and nitrides under high-temperature and high-pressure conditions. The McCormack Lab explores how material symmetry and atomic structure influence thermochemical and thermophysical properties to develop materials for space exploration and hypersonic applications. Key research areas include entropy-stabilized oxides, ultra-high-temperature ceramics, and non-equilibrium materials. McCormack has secured significant funding, including a $1.4M grant for ceramic processing and an NSF CAREER Award. His work merges experimental methods (e.g., in-situ XRD, aerodynamic levitation) with computational modeling to characterize materials under extreme conditions. Awards: NSF CAREER Award, $1.4M Research Grant Labs/Teams: McCormack Lab Key Technologies: High-temperature synthesis, carbothermal reduction, entropy stabilization His publications span advanced ceramics, thermal expansion analysis, and phase transformation kinetics, with a focus on applications in aerospace and energy systems.

Simon Hsiangمشاهده پروفایل

استاد مدعو

• Construction Management
• Project Scheduling
• Construction Engineering
• +۳ مورد دیگر

Simon Hsiang is an Adjunct Professor at North Carolina State University. His research focuses on construction management, project scheduling optimization, and social network analysis within construction crews. He explores topics such as modular construction collaboration, delay causation analysis, and workforce spatial-temporal dynamics in construction environments. Key research themes include applying game theory (e.g., Shapley value-based smart contracts), information-theoretic methods for constraint resolution, and cross-cultural comparisons of delay perceptions in China vs. the U.S. His work also integrates social network analysis to understand team dynamics in construction settings. Publications span over a decade (2011–2023), demonstrating sustained contributions to both construction engineering and interdisciplinary areas like biomechanics and geriatric rehabilitation. Notable studies address pandemic-related adaptations in construction scheduling and quantitative approaches to decision-making under uncertainty. No scientific awards or student advisement records are explicitly documented here. His work primarily resides within the Journal of Management in Engineering , Journal of Construction Engineering and Management , and related peer-reviewed venues.

• Vehicle Dynamics and Control
• Active Suspension Systems
• Autonomous and Connected Vehicles
• +۵ مورد دیگر

BEATRIZ LOPEZ BOADA is a Full Professor and Vice-Chancellor for Sustainability, Infrastructure, Strategy, and Digital Transformation at Universidad Carlos III de Madrid (UC3M). Her research focuses on vehicle dynamics, control systems, and intelligent transportation systems (ITS), with emphasis on fault-tolerant control, autonomous vehicles, active suspension systems, and traffic optimization. She has pioneered work on magnetorheological dampers, vehicle platooning, and IoT-based sensor fusion for real-time state estimation. Her teaching innovations include integrating AI tools into transport engineering curricula. Key contributions include H∞ control methodologies for roll stability, energy-efficient traffic management, and robust platoon control under disturbances. Education & Professional Roles: Vice-Chancellor for Sustainability, UC3M (current) Full Professor of Automotive Engineering, UC3M Research Interests: Active suspension systems for rollover prevention Fault-tolerant control architectures for electric vehicles Data-driven traffic prediction using LSTM and graph neural networks Integration of IoT and AI in transportation infrastructure Recent work emphasizes connected vehicle systems, including heterogeneous platoon coordination and adaptive control strategies under communication delays. She also investigates how driver preferences impact energy-efficient traffic signal control. Awards & Grants: While specific awards aren't listed, her sustained research output indicates significant contributions to transportation engineering. Active grants include projects on autonomous vehicle safety and smart traffic management systems. Advising & Labs: Leads UC3M's Vehicle Dynamics and Control Lab, focusing on experimental validation of control algorithms using real-world vehicle platforms. Collaborates with automotive industry partners on suspension system optimization and sensor fusion technologies.

• Constraint Programming
• Boolean Satisfiability
• Artificial Intelligence
• +۵ مورد دیگر

Steve Prestwich is a Lecturer at the School of Computer Science and Information Technology, University College Cork. He specializes in Artificial Intelligence, Data Analytics, and Algorithmics, with research interests spanning constraint programming, Boolean satisfiability, and hybrid search methods. Education: BA (Hons) Mathematics from University of Oxford, MSc and PhD in Computer Science from University of Manchester. Research Focus: His work integrates constraint programming, SAT solving, and metaheuristics for optimization under uncertainty, with applications in inventory control, protein design, and stochastic modeling. Awards: Runner-up, Constraint Modelling Challenge Bronze medal, SAT'05 Solver Competition

• Game Theory
• Dynamic Programming
• Mathematical Economics
• +۳ مورد دیگر

Juan Pablo Rincón-Zapatero is a Professor of Economics at Universidad Carlos III de Madrid , serving as Director of the Graduate School of Economics and Political Science . His research focuses on mathematical economics, game theory, dynamic programming, and financial mathematics. He holds a prominent role in advancing theoretical frameworks for economic modeling under uncertainty. He teaches Advanced Mathematics for Economics (undergraduate) and Mathematics (graduate) courses. His work bridges pure mathematics with applied economics, particularly in stochastic processes and recursive utility models. His publications address core topics like Bellman equations, stochastic differential games, and value function analysis. Notable contributions include applying Euler-Lagrange methods to economic asset games and proving differentiability in unbounded dynamic models. Though no awards are listed here, his extensive publication record reflects sustained academic impact. He currently oversees the graduate economics program, fostering interdisciplinary research between mathematics and economics.

Masoud Baratiمشاهده پروفایل

استادیار

• Electric Power Systems Modeling
• Quantum Computing
• Optimization and Simulation
• +۸ مورد دیگر

Masoud Barati is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh's Swanson School of Engineering. Previously, he held similar roles at the University of Houston and Louisiana State University. He earned his PhD in Electrical Engineering from the Illinois Institute of Technology (2009-2013) and completed a postdoctoral fellowship at the University of Chicago Booth School of Business in 2014. His research bridges pure and applied mathematics with electric power systems, focusing on resilience, quantum computing, and control systems. Barati’s academic journey includes a diverse range of studies: his doctoral work at Illinois Tech focused on electrical engineering, while his postdoctoral research at the University of Chicago explored business-related systems through a computational lens. His current role at the University of Pittsburgh allows him to advance interdisciplinary research in energy systems. Research interests span algebraic geometry and category theory for computational problem-solving in power systems, alongside applied areas like optimization, quantum computing, Bayesian statistics, and deep learning. He investigates resilience in power grids under natural hazards and cyber-attacks, with specific attention to AC optimal power flow, energy justice, and multi-interdependent infrastructure management. His work integrates smart city technologies, blockchain for energy trading, and data-driven methods such as kernel regression and neural networks for real-time grid analysis. His recent publications emphasize quantum protocols for entanglement detection, smart city energy infrastructure resilience, and machine learning-augmented approaches to power system control. These trends reflect a focus on leveraging advanced computational tools to address modern energy challenges. Barati has contributed to collaborative research projects, including a global algorithm for AC-OPF optimization funded by the National Science Foundation (NSF). While no scientific awards are explicitly listed, his research portfolio demonstrates significant contributions to energy systems and quantum computing. His advisory work includes various projects on grid resilience, though formal student advisee names are not provided in the text. Grants and funding are associated with his collaborative efforts in developing scalable optimization algorithms for power systems. Research activities involve partnerships with institutions like IBMQ for quantum simulations and local case studies in Pittsburgh. He explores innovative solutions such as mobile charging stations for EVs and blockchain-based energy trading models, reflecting a commitment to both theoretical and applied advancements in energy engineering.