جست‌وجوی استاد و پژوهشگر

Kousha Etessamiمشاهده پروفایل

استاد

• Theoretical Computer Science
• Automated Verification
• Logic
• +۱۱ مورد دیگر

Kousha Etessami is a Professor in the Laboratory for Foundations of Computer Science within the School of Informatics at the University of Edinburgh . His research spans theoretical computer science with a focus on automated verification, logic, algorithms and computational complexity, algorithmic game theory, stochastic systems, automata theory and model checking. Research Interests: Automated verification and model checking Logic and computational complexity Algorithmic game theory and equilibrium computation Analysis of probabilistic systems, Markov decision processes and stochastic games Automata theory and infinite-state systems Finite model theory and descriptive complexity His publications reveal a strong profile in algorithmic game theory, stochastic modelling, and verification of complex systems. Recent work focuses on equilibrium computation complexity, reachability in stochastic games, and fixed-point methods for probabilistic models. He has contributed extensively to both foundational theory and practical algorithms, with journal publications in top venues including SIAM Journal on Computing , Journal of the ACM , Information and Computation , and Games and Economic Behavior . Students & Collaborators: PhD graduates: Thomas Webster (2024), Emanuel Martinov (2021), Alistair Stewart (2014), Dominik Wojtczak (2009) Postdoc: Václav Brožek (Newton Fellow, now at Google-Munich) Teaching Contributions: Professor Etessami teaches and has taught courses on Algorithmic Game Theory, Randomized Algorithms, Discrete Mathematics, Stochastic Modelling and Simulation, and Compiling Techniques at the University of Edinburgh. Contact: Email: kousha@inf.ed.ac.uk Office: Informatics Forum, Room 5.20, 10 Crichton Street, Edinburgh EH8 9AB, Scotland, UK Telephone: +44 (0)131 650 5197

Ute Ebertمشاهده پروفایل

استاد

• Plasma Physics
• Gas Discharges
• Lightning Physics
• +۴ مورد دیگر

Ute Ebert serves as a Full Professor (Part-time) in the Elementary Processes in Gas Discharges group at Eindhoven University of Technology (TU/e), with her primary affiliation at the Centrum Wiskunde & Informatica (CWI) in Amsterdam where she leads the Multiscale Dynamics research group. Her work bridges theoretical modeling at CWI with experimental research at TU/e, focusing on fundamental plasma processes and their applications. Her research interests center on Plasma Physics and Gas Discharges , with particular expertise in lightning physics, high voltage technology for electricity networks, and applications of pulsed plasmas in agriculture and combustion engines. Her work combines analytical and computational modeling approaches to understand complex discharge phenomena across multiple scales. Analysis of her publications reveals a strong focus on streamer discharges as the primary mode of electric breakdown in thunderstorms and high voltage systems. Her research has demonstrated unconventional phenomena such as streamers propagating perpendicularly to background electric fields and investigated x-ray emissions from meter-scale discharges, contributing significantly to our understanding of atmospheric electricity and plasma applications. Her collaborative projects are currently financed by the EU and NWO, reflecting the international significance of her work in connecting fundamental plasma physics with practical engineering applications.

• Information Economics
• Game Theory
• Economic Theory

Alexander Frug serves as an Associate Professor at Pompeu Fabra University and holds an Affiliated Professor position at the Barcelona School of Economics. Based at the Jaume I building (office 20.2E08) in Barcelona, he maintains active research and teaching responsibilities with contact via alexander.frug@upf.edu. His Ramon y Cajal researcher status reflects Spain's recognition of his scholarly contributions. His academic focus spans: Information Economics Game Theory Economic Theory Frug's research program investigates strategic interactions under information asymmetry, with particular emphasis on communication dynamics, contract design, and incentive structures. His theoretical frameworks address real-world economic phenomena including boycott coordination, task scheduling, and organizational hierarchies. The consistent application of game-theoretic methods across his publication record demonstrates deep expertise in modeling strategic behavior in dynamic environments where information evolves gradually or arrives stochastically.

• Semiconductor Devices
• Nanotechnology
• Computational Electronics
• +۵ مورد دیگر

Umberto Ravaioli is a Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, holding positions in the Coordinated Science Lab and Micro and Nanotechnology Lab. He serves as Director of Academic Programs for the ZJU-Illinois Joint Institute, part of the Grainger College of Engineering. His research focuses on semiconductor devices, nanotechnology, computational electronics, and thermal/phonon transport phenomena. Ravaioli is an IEEE Fellow (2003) and has contributed to over 210 peer-reviewed publications, including works on Monte Carlo simulations, machine learning applications in imaging, and nanostructured materials. His research integrates computational modeling with experimental studies to advance electronics and energy-efficient technologies. Research Interests: Monte Carlo simulation of semiconductor transport Thermal and phonon dissipation in nanoscale devices Machine learning for biomedical and materials science applications Quantum and nanoelectronics device design Computational modeling of 2D materials and nanowires Recent Research Trends: Recent articles emphasize interdisciplinary approaches, combining machine learning with imaging (e.g., MR fingerprinting) and advancing thermal management in semiconductor devices. His work bridges computational methods with experimental validation in nanomaterials and energy-efficient electronics. Awards: IEEE Fellow (2003) Labs & Teams: Leads the Micro and Nanotechnology Lab’s academic programs, fostering collaboration in nanotechnology and computational engineering. Engaged with the ZJU-Illinois Joint Institute for interdisciplinary research.

• Monetary Economics
• Payment Systems
• Fiscal Policy
• +۳ مورد دیگر

Ayushi Bajaj serves as Senior Lecturer in the Department of Economics at Monash University, where her research bridges theoretical monetary models with contemporary policy challenges including demonetization impacts, pandemic fiscal responses, and liquidity dynamics in global markets. Her scholarly profile reflects active engagement in high-impact economic research with consistent publications in premier journals. Dr. Bajaj's research program centers on monetary economics and payment systems, examining how institutional changes like India's demonetization affect consumer behavior and how monetary frameworks function under adverse selection. Her work extends to fiscal policy innovation, particularly pragmatic financing mechanisms for pandemic responses, demonstrating strong connections between theoretical modeling and real-world economic phenomena. This dual focus on foundational monetary theory and urgent policy applications defines her scholarly contributions. Analysis of her publication trajectory (2017-2023) reveals deepening specialization in payment system dynamics and monetary policy transmission, with increasing emphasis on data-driven analysis of major economic disruptions. The progression from theoretical model refinements toward policy-relevant studies of demonetization and pandemic responses highlights her adaptive research agenda addressing evolving global economic challenges. As Primary Chief Investigator for the externally funded project "Global Economic Uncertainty, Liquidity and Monetary Policy in Australia" (2021-2025), Dr. Bajaj demonstrates significant research leadership. This five-year initiative examines how international economic volatility affects Australian monetary policy implementation, positioning her at the forefront of applied monetary economics research with direct relevance to central bank operations.

Yuqiong Wangمشاهده پروفایل

استادیار

• Stochastic Control
• Optimal Stopping
• Stochastic Games
• +۱ مورد دیگر

Yuqiong Wang is a Byrne Research Assistant Professor in Mathematics at the University of Michigan, mentored by Erhan Bayraktar. Her research focuses on stochastic control systems, optimal stopping problems, and stochastic game theory with applications in mathematical finance. She earned her Ph.D. from Uppsala University in 2023, where she developed Bayesian frameworks for sequential decision-making under uncertainty. Her publication record demonstrates consistent focus on refining stochastic modeling techniques, particularly through Bayesian approaches to sequential analysis. Recent theoretical advances include novel formulations of asymmetric Dynkin games and nonlocal parabolic operators derived from game-theoretic principles.

Anne Draelosمشاهده پروفایل

استادیار

• Real-time neural data analysis
• Machine learning for neuroscience
• Adaptive experimental designs
• +۷ مورد دیگر

Anne Draelos, Ph.D. is an Assistant Professor with dual appointments in the Department of Biomedical Engineering and the Department of Computational Medicine & Bioinformatics at the University of Michigan. She is also affiliated with the Michigan Neuroscience Institute, the Michigan Institute for Data Science, and the Michigan Institute for Computational Discovery and Engineering. Her research focuses on developing statistically efficient methods for real-time and adaptive neuroscience experiments. Dr. Draelos received her Ph.D. in Physics and M.S. in Electrical & Computer Engineering from Duke University, followed by undergraduate degrees in Physics and Computer Science from North Carolina State University. Her academic journey spans quantum physics, electrical engineering, and neuroscience, reflecting her interdisciplinary approach to complex scientific problems. Her research interests center on real-time analysis of neural and behavioral data using machine learning and statistical techniques. The Draelos Lab develops methods for adaptive stimulation of neural dynamics, multimodal latent space modeling, real-time brain-computer interfaces with neural stimulations, and Bayesian optimization for visual stimuli. Her work bridges the gap between simplistic and complex stimulus spaces to provide new insights into how sensory stimuli are represented in the brains of behaving animals. Analysis of her recent publications reveals a strong focus on developing computational methods that enable real-time analysis and intervention in neural systems. Her work spans from low-dimensional neural manifold modeling to large-scale neural connectivity estimation, with applications ranging from larval zebrafish to non-human primates. She has pioneered approaches that combine streaming data analysis with adaptive experimental designs to accelerate neuroscience discovery. Sloan Fellowship in Neuroscience (2024) Career Award at the Scientific Interface from Burroughs Wellcome Fund (2021) Swartz Foundation Fellow for Theory in Neuroscience (2020) Best Poster Award, IEEE Brain Workshop on Advanced NeuroTechnologies (2020) Ruth K. Broad Postdoctoral Fellowship (2019-2020) Dr. Draelos actively mentors students across multiple levels, including undergraduate, master's, and Ph.D. candidates. Her lab has received funding from multiple prestigious sources including the University of Michigan Research Scout Award, Sloan Fellowship, Burroughs Wellcome Fund, and the National Institute on Aging. Her research philosophy emphasizes tight integration between computational models and experimental neuroscience, creating a feedback loop where models inform experiments and experimental results refine models. The Draelos Lab is located at the North Campus Research Complex (NCRC) at the University of Michigan, where they develop and implement cutting-edge methods for real-time neural data analysis and adaptive experimentation. The lab maintains strong collaborations with several other research groups including the Kaczorowski Lab, Chestek Lab, Savier Lab, Burgess Lab, and Naumann Lab.

Matthew R. Stonekingمشاهده پروفایل

استاد

• Plasma Physics
• Magnetic Confinement
• Non-neutral Plasmas
• +۴ مورد دیگر

Matthew R. Stoneking is the Alice G. Chapman Professor of Physics at Lawrence University, where he has served since 1997. His research focuses on experimental plasma physics, particularly the magnetic confinement of pure electron plasmas and the creation of electron-positron pair plasmas. He leads the APEX collaboration, developing advanced levitated dipole traps and collaborating internationally with institutions like the Max Planck Institute for Plasma Physics. His work integrates superconducting magnet technology, FPGA stabilization, and positron beam manipulation to explore fundamental plasma behaviors. Education: BA in Physics from Carleton College and PhD in Physics from the University of Wisconsin-Madison. His research interests span non-neutral plasmas, magnetic confinement engineering, and laboratory astrophysics. Key projects include the construction of the APEX-LD trap and the development of diagnostic techniques using gamma-ray annihilation signatures. Research trends in his articles emphasize advancing pair plasma confinement, optimizing magnetic trap designs, and understanding plasma behavior under extreme conditions. Collaborations with global teams aim to bridge theoretical models with experimental validation. His work contributes to both plasma physics and astrophysics by simulating conditions found in cosmic environments. Despite no explicit awards listed, his sustained contributions to experimental plasma physics highlight significant academic impact. Advising emphasizes student involvement in cutting-edge experiments, while grants likely support APEX infrastructure and international collaborations. His laboratory at Lawrence University serves as a hub for innovative plasma research, complemented by advanced facilities at partner institutions. Current projects include refining superconducting coil levitation, improving positron injection efficiency, and exploring thermal equilibrium dynamics in curved magnetic fields. Future work aims to achieve long-lived electron-positron plasmas, with potential applications in fundamental physics and energy research.

Christopher W. Brownمشاهده پروفایل

استاد

• Computer Algebra
• Quantifier Elimination
• Cylindrical Algebraic Decomposition
• +۴ مورد دیگر

Christopher W. Brown is a Professor in the Department of Computer Science at the United States Naval Academy, specializing in computational methods for semi-algebraic sets and computer science education. His research bridges theoretical computer algebra with practical applications in epidemic modeling and pedagogical tools, maintaining active contributions to symbolic computation since the late 1990s. His primary research focuses on cylindrical algebraic decomposition (CAD) and quantifier elimination, with significant extensions to projection operators, bi-equational constraints, and truth-invariant decompositions. He also develops educational software like RegeXeX for teaching regular expressions, demonstrating his dual commitment to theoretical advancement and practical pedagogy in computer science education. Analysis of his 13 publications (1998-2007) reveals sustained innovation in CAD efficiency, including reduced projection operators and complexity analysis, while expanding applications to epidemiological modeling and educational systems. His work consistently targets real-world usability, exemplified by the QEPCAD B software suite for industrial/scientific deployment of quantifier elimination. No scientific awards are documented in the provided materials. As a professor, Brown advises students and leads research projects, though specific mentoring details are absent. His development of RegeXeX demonstrates direct classroom integration of research, with studies confirming its effectiveness in reducing instructor intervention while improving student outcomes in formal language theory. Brown directs the QEPCAD project and associated tools (Tarski, webCal), creating an ecosystem for semi-algebraic set computation. These systems form the core of his research group's work, emphasizing both theoretical refinement (e.g., projection-definable CADs) and practical deployment in scientific computing contexts.

Leili Tafaghodiمشاهده پروفایل

دانشیار

• Sustainable Materials Processing
• Metallurgy
• Thermodynamics
• +۳ مورد دیگر

Dr. Leili Tafaghodi is an Associate Professor and Associate Graduate Chair in the Department of Materials Science and Engineering at McMaster University's Faculty of Engineering. Her research focuses on sustainable materials processing, particularly in metallurgy, thermodynamics, and recycling of industrial waste. She holds a BEng from Sharif University of Technology, and MASc and PhD from the University of Toronto, with a PEng license. Her research emphasizes reducing environmental impact through innovative metal production methods and waste utilization. She has received notable awards including the 2024 Brian Ives Lectureship Award and the 2022 Brimacombe Award. She teaches MATLS 3F03: High-Temperature Materials Production and actively advises graduate students. Dr. Tafaghodi’s work spans pyrometallurgical processes, hydrogen-based reduction strategies, and material microstructural analysis. Her publications address challenges in nickel extraction, sulfur management in calcination, and alloy refining. Her group aims to advance sustainable practices in resource-intensive industries.

Yves Breitmoserمشاهده پروفایل

استاد

• Behavioral Economics
• Econometrics
• Game Theory
• +۳ مورد دیگر

Prof. Dr. Yves Breitmoser is a Professor of Behavioral Economics at the Faculty of Business Administration and Economics at Universität Bielefeld. He holds the Chair of Behavioral Economics (Lehrstuhl für VWL) and is affiliated with the Center for Mathematical Economics and the JICE - Joint Institute for Individualisation in a Changing Environment. His research focuses on behavioral economics, game theory, experimental economics, and social preferences, with notable work on fairness, altruism, decision-making under uncertainty, and strategic interactions in repeated games. He is actively involved in academic governance, serving as a member of the Commission for the Development of the University and in module design roles such as Module Designee for Behavioral Economics. His research explores interdisciplinary perspectives on individual behavior in complex environments, with a particular emphasis on understanding how social preferences and cognitive biases influence economic decisions. Key research themes include experimental investigations of fairness-based altruism, inequity aversion in repeated interactions, and the strategic implications of presentation effects in decision-making. His work bridges theoretical models with empirical evidence, often employing controlled experiments to validate hypotheses about human behavior in economic contexts. Prof. Breitmoser collaborates across disciplines, contributing to the understanding of individualization processes in changing environments through his affiliation with JICE. His publications span topics from voting mechanisms and committee dynamics to auction behavior and welfare-based decision-making frameworks.

Oriol Carbonell-Nicolauمشاهده پروفایل

استاد

• Public Economics
• Game Theory
• Income Inequality
• +۱ مورد دیگر

Oriol Carbonell-Nicolau is a Professor in the Department of Economics at Rutgers University. He holds a B.S. from Universitat Pompeu Fabra and a Ph.D. from New York University. His research focuses on public economic theory and game theory, with specific interests in characterizing tax structures that reduce income inequality and polarization, as well as studying equilibrium concepts in games with general type and action spaces. His work examines how progressive tax schedules affect income distribution and economic polarization under different economic conditions. Professor Carbonell-Nicolau's publications primarily explore themes of economic inequality, tax policy, game theory equilibrium, and regulatory economics. Recent work shows a strong focus on mathematical modeling of taxation systems and their societal impacts. He maintains an active research profile with consistent publications in top economics journals exploring the intersection of economic theory and social policy.

• Statistical Mechanics
• Mathematical Physics
• Probability Theory
• +۴ مورد دیگر

Claudio Giberti is a Full Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering Sciences and Methods. His academic roles include teaching advanced courses in Rational Mechanics, Applied Mathematics, Stochastic Methods for Simulations, and Mathematical Physics. He holds a permanent faculty position with expertise spanning theoretical physics, applied mathematics, and interdisciplinary research in healthcare analytics. Research Interests: His work focuses on statistical mechanics, non-equilibrium thermodynamics, and complex systems. Key areas include anomalous transport in low-dimensional systems, phase transitions in spin models, and applications of stochastic methods to biomedical problems such as electrocardiogram (ECG)-based mortality risk assessment. He also explores interdisciplinary topics like queueing models for logistics optimization. Publications: Over 15 recent articles (2015–2025) address topics ranging from uphill diffusion phenomena in Ising models to machine learning applications in cardiology. Notable contributions include studies on microscopic state equations for oscillator chains and annealed Ising models on random graphs, highlighting his dual expertise in theoretical physics and applied mathematics. Teaching: Courses include Rational Mechanics for Mechatronics Engineering, Stochastic Simulation Methods for Mathematics students, and Applied Mathematics for Management Engineering. He emphasizes hands-on learning with practical exercises and software tools for structural analysis. Future Work: Current projects involve refining ECG-based predictive models for cardiovascular risk and extending studies on non-equilibrium dynamics in multi-component systems. Collaborations with biomedical researchers and engineers underscore his commitment to bridging theoretical and applied research.

Falk Herwigمشاهده پروفایل

استاد

• Stellar Hydrodynamics
• Nuclear Astrophysics
• Stellar Evolution
• +۳ مورد دیگر

Falk Herwig is a Professor and Director of the Astrophysical Research Center (ARC) at the University of Victoria's Department of Physics and Astronomy. His research focuses on stellar hydrodynamics, nucleosynthesis, and the origin of elements. He leads the Computational Stellar Astrophysics (CSA) group, which conducts large-scale 3D hydrodynamics simulations of stellar convection and nucleosynthesis processes. The CSA group collaborates with the NSF Physics Frontier Center Joint Institute for Nuclear Astrophysics (JINA-CEE) and the NuGrid collaboration, leveraging high-performance computing resources like the Niagara supercomputer. Herwig's work includes studying convection-nuclear burning interactions in massive and binary stars, nucleosynthesis in diverse astrophysical environments, and the chemical evolution of galaxies. He has pioneered methods to model stellar yields and integrate computational models with observational data. His research spans topics from core convection in massive stars to the physics of merging white dwarfs and nova explosions. Herwig has contributed significantly to advancing computational infrastructure for astrophysics, including the development of tools like SYGMA for galactic chemical evolution modeling. His projects are supported by Compute Canada and involve collaborations with international institutions. Recent research highlights include investigating the role of neutron capture processes in element formation and refining models of white dwarf cooling and stellar evolution.

Dimitrije Stamenovicمشاهده پروفایل

استاد

• Cellular Mechanics
• Tissue Rheology
• Cytoskeletal Dynamics
• +۲ مورد دیگر

Dimitrije Stamenovic is a Professor of Biomedical Engineering and Materials Science at Boston University. His research investigates cellular mechanics, cytoskeletal dynamics, and tensional homeostasis using theoretical and experimental approaches. Key contributions include models linking cytoskeletal prestress to cell stiffness and developing knee braces for osteoarthritis. He studies mechanotransduction in endothelial cells and cancer progression, with recent work on E-cadherin dysfunction and integrin-mediated adhesion. Awards include membership in the American Institute for Medical and Biological Engineering. Dr. Stamenovic collaborates globally on pulmonary biomechanics and cellular rheology projects. He teaches courses in biorheology and biomechanics, mentoring students in quantitative cell imaging and soft-tissue engineering. His lab develops computational models to predict cellular responses to mechanical stimuli across scales.