جست‌وجوی استاد و پژوهشگر

Thomas Colasمشاهده پروفایل

پژوهشگر

• Theoretical Cosmology
• Open Quantum Systems
• Effective Field Theories
• +۳ مورد دیگر

Dr. Thomas Colas is a theoretical cosmologist at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics (DAMTP), part of the Relativity and Gravitation research group. His work focuses on Open Effective Field Theories (OEFT) and non-unitary effects in the early universe, leveraging quantum information theory and non-equilibrium quantum field theory techniques. His research bridges cosmology with condensed matter physics and quantum optics to understand inflationary dynamics and quantum fluctuations' role in cosmic inhomogeneities. Key research themes include modeling uncertainties in early universe physics through OEFT, studying decoherence and dissipation in cosmological systems, and analyzing quantum-to-classical transitions during inflation. His work addresses foundational questions about how quantum mechanics operates in extreme cosmological contexts, such as the primordial vacuum's imprint on the cosmic microwave background and large-scale structures. Recent publications highlight advancements in OEFT frameworks for light-matter interactions, entropy calculations in curved spacetimes, and recoherence mechanisms in expanding universes. These contributions advance our understanding of how hidden sectors and unaccounted degrees of freedom influence cosmological observables. Dr. Colas maintains active collaborations through his research group and engages with experimental cosmology via data analysis tools like the SDSS/BOSS dataset, bridging theoretical insights with observational tests of early universe models.

Fred Espen Benthمشاهده پروفایل

استاد

• Mathematical Finance
• Energy Markets
• Insurance
• +۴ مورد دیگر

Roles and Affiliations: Fred Espen Benth is a Professor in the Department of Mathematics at the University of Oslo, affiliated with the Risk and Stochastics research group. He holds a Dr. scient (PhD equivalent) in mathematics from the University of Oslo (1995). His academic journey includes roles as a researcher at the Norwegian Computing Center, a postdoc at the Universities of Aarhus and Oslo, and an Associate Professor at the University of Trondheim before becoming a full professor in 2002. Research Interests: Benth’s research focuses on mathematical finance, particularly energy and weather markets, commodity derivatives, and stochastic analysis. He explores modeling, estimation, and simulation of spot and forward prices, as well as pricing options and portfolio optimization. Recent work extends to climate systems, energy transition dynamics, and machine learning applications in financial and environmental modeling. Publications and Projects: His extensive publication record includes over 150 journal articles and book chapters, with a focus on energy markets, stochastic processes, and climate-related financial instruments. Notable projects include ‘Spatial-Temporal Uncertainty in Energy Systems (SPATUS)’ and contributions to interdisciplinary energy informatics. His work bridges theoretical stochastic analysis with practical applications in energy systems and risk management. Labs and Collaborations: Benth collaborates with the Stochastics of Renewable Energy Markets (STORE) group and contributes to initiatives like the ‘Computational Modelling and Machine Learning for Applications in Hydropower’ project. His research emphasizes the integration of stochastic methods with real-world energy and climate challenges.

Niklas Lindeمشاهده پروفایل

استاد

• Geophysics
• Environmental Geophysics
• Probabilistic Inversion
• +۳ مورد دیگر

Niklas Linde is a full professor at the University of Lausanne's Faculty of Geosciences and Environment, leading the Department of Earth Sciences. He holds a PhD in Geophysics from Uppsala University (2005) and has held roles including Assistant Professor (2008), Associate Professor (2013), and Full Professor (2019). His research focuses on transforming geophysical signals into realistic hydrogeological models with rigorous uncertainty quantification. Key areas include probabilistic inversion, Bayesian methods, and geostatistical modeling applied to environmental and subsurface processes. Education: PhD in Geophysics (Uppsala University, 2005), postdoctoral positions at Lawrence Berkeley National Lab (USA), CNRS-CEREGE (France), and ETH Zurich (Switzerland). He joined UNIL in 2008 as an Assistant Professor in Environmental Geophysics. Research interests span geophysical inversion techniques, subsurface heterogeneity characterization, and the integration of geophysical and hydrological data. Current projects emphasize Bayesian approaches for model selection and rare event estimation, supported by grants from the European Commission and Swiss National Science Foundation. Collaborations involve international teams addressing challenges in hydrogeology, rock fracture dynamics, and 4D hydrogeology. Publications reflect advancements in inverse problem solving, stochastic simulation, and machine learning applications. His work bridges theory and practice, with field studies in alpine environments, fractured media, and environmental monitoring. Students under his supervision have explored topics like deep generative networks and Bayesian hydrogeological inversion. Advising: Supervised over a dozen PhD students, including recent works on variational Bayesian methods and geophysical data fusion. Grants include projects on uncertainty quantification and experimental design. Active in scientific societies and editorial roles, contributing to methodological advancements in Earth sciences.

Michael Scottمشاهده پروفایل

استاد

• Structural Engineering
• Nonlinear Structural Analysis
• Finite Element Analysis
• +۶ مورد دیگر

Michael Scott is a Professor in the Department of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. He holds a Ph.D. in Structural Engineering from the University of California, Berkeley (2004), an M.S. from the same institution (1999), and a B.S. in Civil Engineering from North Carolina State University (1998). His research focuses on nonlinear structural analysis, dynamics, numerical methods, and software design, particularly in the context of bridges and fluid-structure interactions. He has developed widely used tools like OpenSees and contributed to multi-hazard resilience frameworks for infrastructure. Key research areas include tsunami impacts on coastal bridges, GPU-accelerated analysis, and machine learning applications for structural simulation. His work emphasizes sensitivity analysis and software reliability, with notable contributions to OpenSees and PFEM methodologies. He has been recognized with the 2019 Celebrate Excellence Awards for Online Teaching. His research also addresses bridge loading from truck platooning, seismic sensitivity, and ponding effects on structural steel roofs. Educations: Ph.D., Structural Engineering, UC Berkeley (2004) M.S., Structural Engineering, UC Berkeley (1999) B.S., Civil Engineering, NC State University (1998) Awards: 2019 Celebrate Excellence Awards, Online Teaching Award Key Contributions: Development of OpenSees software framework Pioneering work in PFEM for fluid-structure interaction Multi-hazard engineering for tsunami resilience

• Longitudinal Modeling
• Psychometric Modeling
• Developmental Cognitive Neuroscience
• +۳ مورد دیگر

Ethan McCormick is an Assistant Professor in the School of Education at the University of Delaware, specializing in longitudinal and psychometric modeling. He holds a Ph.D. in Psychology from the University of North Carolina at Chapel Hill (2020) and a B.S. in Biochemistry from the University of Arkansas (2013). His research focuses on integrating short-term and long-term longitudinal models to study behavioral and cognitive changes across the lifespan, with recent emphasis on educational data analysis and nonlinear random effects modeling. He is a Resident Faculty member of the University of Delaware’s Data Science Institute and previously served as an Assistant Professor of Methodology & Statistics at Leiden University (2022–2024). Dr. McCormick’s grants include the NWO Veni SSH Grant (2024–2027) for tracking educational outcomes via statistical modeling and the Jacobs Foundation Fellowship (2024–2026) for studying complex growth in math ability. His work bridges methodological rigor with applied neuroscience, examining brain-behavior relationships in developmental contexts through large-scale collaborations. Professional Experience : Assistant Professor, University of Delaware (2024–present); Assistant Professor, Leiden University (2022–2024) Key Research Themes : Longitudinal modeling, time series analysis, psychometrics, developmental cognitive neuroscience Awards : NWO Veni SSH Grant, Jacobs Foundation Fellowship His recent articles emphasize improving time-series methodologies, addressing limitations of two-time-point studies, and advancing models for asymmetric temporal dynamics. He collaborates internationally on projects simulating developmental datasets and analyzing neural correlates of behavior.

Charles Kaneمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Electronics
• Topological Insulators
• +۳ مورد دیگر

Charles Kane is the Christopher H. Browne Distinguished Professor of Physics at the University of Pennsylvania's School of Arts & Sciences, Department of Physics and Astronomy. His research focuses on quantum electronic phenomena in solids, particularly topological insulators, quantum spin Hall effects, graphene, and carbon nanotubes. He holds numerous academic chairs and fellowships, including the Class of 1965 Endowed Term Chair and IBM Predoctoral Fellowship. His honors include the Benjamin Franklin Medal, National Academy of Sciences membership, and the Oliver Buckley Condensed Matter Prize. Education: Ph.D. in Physics from MIT (1989) and B.S. in Physics from the University of Chicago (1985). Research Interests: His work integrates quantum field theory and numerical simulations to explore topological phases of matter. Key areas include the theory of topological insulators, quantum spin Hall effects, and nanoscale electronic systems. He emphasizes experimental collaboration to bridge theoretical and applied physics, with a focus on materials like graphene and carbon nanotubes. Articles Trends: Recent publications highlight advancements in topological density correlations, Fermi sea topology, and topological superconductivity. His work often addresses symmetry-enriched phases, quantum transport, and novel electronic states in low-dimensional systems. Awards: Benjamin Franklin Medal (2015) Elected to National Academy of Sciences (2014) Lindback Award for Distinguished Teaching (2014) Physics Frontiers Prize (2013) Grants & Advising: Recipient of Simons Investigator grant (2012) and Oliver Buckley Prize (2012). His research group advises on topological materials and quantum phenomena, though specific student names are not listed in the text. Labs & Teams: Leads research in Penn's Department of Physics, contributing to advancements in condensed matter theory and topological quantum computing.

Andreas Herzمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Coding
• Spatial Navigation
• +۳ مورد دیگر

Prof. Dr. Andreas Herz is a Chair in Computational Neuroscience at the Faculty of Biology, Ludwig-Maximilians-Universität München (LMU). His research focuses on understanding neural mechanisms underlying spatial navigation, temporal cognition, and sensory processing. He leads the Computational Neuroscience group and collaborates with the Bernstein Center for Computational Neuroscience Munich. Research Interests: Dr. Herz investigates how neural systems encode spatial and temporal information, including grid cells, head-direction systems, and neural coding strategies. His work bridges experimental neurophysiology with theoretical modeling, addressing topics like cognitive maps, neural variability, and synaptic plasticity. Teaching & Mentorship: He oversees advanced courses on computational neuroscience and neurophysiology, fostering interdisciplinary training for graduate students. His research group includes prominent collaborators like Dr. Martin Stemmler and PD Dr. Kay Thurley, focusing on projects involving neural network dynamics and behavioral neuroscience. Publications & Impact: Over 85 peer-reviewed articles highlight his contributions to understanding entorhinal-hippocampal circuits, dendritic processing, and neural representation of space/time. Key work includes studies on grid cell variability, zebrafish spatial memory, and cytoskeletal organization in dendritic spines.

Ali Khazaeiمشاهده پروفایل

استاد

• Renewable Energy
• MEMS Systems
• Vehicle Dynamics
• +۷ مورد دیگر

Ali Khazaei is a Professor in the Department of Mechanical Engineering at Kennesaw State University. He has held academic roles since 1988, including Assistant Professor at Southern Polytechnic State University (SPSU) starting in 2008 and previous adjunct roles. His research focuses on renewable energy, MEMS systems, vehicle dynamics, thermal analysis, and nonlinear dynamics. He holds a Ph.D. in Mechanical Engineering from Tehran Azad University (1998), an MSc from the University of Tehran (1987), and a BSc from the same institution (1982). Education: Ph.D., Mechanical Engineering, Tehran Azad University (1998) MSc, Mechanical Engineering (Heat & Fluids), University of Tehran (1987) BSc, Mechanical Engineering, University of Tehran (1982) Research Interests: Dr. Khazaei’s work spans renewable energy technologies, MEMS thermal behavior, autonomous vehicle dynamics, and interdisciplinary strategies to enhance engineering education. His research emphasizes practical applications in sustainability, thermal modeling, and vibration isolation systems. Publications Overview: His recent work includes studies on tire models for autonomous vehicles, MEMS thermal dynamics, and suspension systems. Earlier contributions addressed nonlinear dynamics, microresonator analysis, and interdisciplinary education strategies. Advising & Grants: No formal advisee名单 or grant details provided. His professional experience includes roles as a design engineer and consultant in Iran, focusing on construction and mechanical systems.

• Nonlinear Dynamics
• Structural Dynamics
• Vibration Control
• +۳ مورد دیگر

Professor David Wagg is a Professor of Nonlinear Dynamics and Departmental Director of Research and Innovation at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. His research focuses on nonlinear structural dynamics, digital twins, vibration suppression, and real-time hybrid testing. He holds a BEng and PhD from University College London and previously served as a Professor at the University of Bristol (2008–2013). Notable awards include the EPSRC Advanced Research Fellowship (2004–2009). Education: BEng and PhD in Nonlinear Dynamics from University College London. Research Interests: Digital twins for dynamics applications, nonlinear structural dynamics, vibration control, real-time hybrid testing, and identification methods for nonlinear dynamics. His work emphasizes applying nonlinear models and control strategies to engineering challenges like wind turbines and large civil infrastructure. Grants & Leadership: Co-Investigator for EPSRC grants on CITCoM and Digitwin, coordinator of the Marie Curie ETN DyVirt, and PI for the EPSRC programme on Engineering Nonlinearity (2012–2017). He co-authored Nonlinear Vibration with Control (2015) and edited books on structural dynamics. Lab/Teams: Involved in the Laboratory for Verification and Validation (LVV) and leads research groups focused on digital twin applications, inerter-based systems, and structural health monitoring.

Jessica J. Fridrichمشاهده پروفایل

استاد

• Steganography
• Digital Forensics
• Signal Processing
• +۴ مورد دیگر

Jessica J. Fridrich is a Distinguished Professor in the Department of Electrical and Computer Engineering at Binghamton University, part of the State University of New York (SUNY) system. She is affiliated with the T. J. Watson School of Applied Science and Engineering. Her research focuses on steganography, steganalysis, digital forensics, and machine learning, with notable contributions to secure data hiding and patented camera fingerprinting techniques approved for legal evidence. Education: PhD in Electrical and Computer Engineering from Binghamton University Her research interests include steganography and steganalysis of digital images, digital forensics for linking photos to cameras via sensor fingerprints, signal estimation and detection, and applications of machine learning. Earlier work explored chaotic nonlinear dynamical systems and encryption. Her methods have led to over 150 refereed publications and seven successfully commercialized patents. Her articles emphasize advancements in batch steganography, JPEG compatibility, and adaptive embedding strategies. Recent work leverages machine learning for steganalysis and explores security trade-offs in high-dimensional feature spaces. 2006-2007 Chancellor's Award for Excellence in Scholarship and Creative Activities 2002 Chancellor's Award for Outstanding Inventor Narrative on advising and grants: She mentors graduate students and leads projects funded by AFOSR, NSF, and AFRL. Her research addresses challenges in data hiding security, forensic analysis, and optimizing steganographic algorithms. The Digital Data Embedding Lab, which she directs, focuses on algorithmic innovation and empirical validation in steganography and forensics. Labs/Teams: Digital Data Embedding Lab

LJILJANA TRAJKOVICمشاهده پروفایل

استاد

• Communication Networks
• Nonlinear Circuits and Systems
• Electronics Engineering
• +۳ مورد دیگر

Ljiljana Trajkovic is a Professor in the Department of Engineering Science at Simon Fraser University's Faculty of Applied Sciences. She holds a Ph.D. from the University of California, Los Angeles (1986), M.Sc. from Syracuse University (1979), and Dipl.Ing. from the University of Pristina (1974). Her research focuses on communication networks, nonlinear circuits, and machine learning applications for network security. She actively contributes to IEEE initiatives, including roles as conference committee chair and editorial board member. Education highlights include a strong foundation in electrical engineering and advanced studies in circuit theory and systems science. Her work bridges theoretical analysis with practical applications, such as anomaly detection in communication networks using machine learning. She teaches courses like ENSC 220 D100 Electric Circuits I, integrating research insights into education. Research interests emphasize network security, traffic analysis, and distributed systems. Recent articles explore BGP anomaly classification, ransomware detection, and virtual network embedding. She collaborates on tools like VNE-Sim and Anonym for network analysis. Awards and recognitions are highlighted through her leadership roles in IEEE and academic contributions. Advising and grants involve mentoring graduate students in cybersecurity and networking projects. She leads research teams exploring complex networks and their applications in autonomous systems. Her lab focuses on interdisciplinary projects merging electronics engineering with AI-driven network solutions.

Gregory Lawrenceمشاهده پروفایل

استاد

• Environmental Fluid Mechanics
• Hydraulics
• Hydrodynamic Stability and Mixing
• +۲ مورد دیگر

Gregory Lawrence is a Professor in the Department of Civil Engineering at the University of British Columbia (UBC), Faculty of Applied Science. Since 1987, he has held a Tier I Canada Research Chair in Environmental Fluid Mechanics and focuses on the fluid dynamics of inland and coastal waters, particularly their impact on water quality, chemistry, and biology. His work addresses waste discharge minimization, lake restoration, and water system rehabilitation. He also instructs in UBC’s Master of Engineering Leadership in Integrated Water Management program. Research Interests : Environmental Fluid Mechanics, Hydraulics, Hydrodynamic Stability and Mixing, Physical Limnology, and Water Quality Management. His studies bridge fluid dynamics with environmental stewardship, emphasizing hydrodynamic processes in lakes, reservoirs, and mine pit lakes. Selected Publications highlight his expertise in stratified flows, Kelvin-Helmholtz instabilities, baroclinic responses, and artificial circulation techniques. These works span journals like Limnology and Oceanography , Physical Review Fluids , and Environmental Fluid Mechanics . Scientific Awards : 2018-2020: 2nd Year Student Appreciation Award (UBC Civil Engineering Club) 2016: Visiting Research Fellow (University of Western Australia) 2013: Elected Fellow (Canadian Society for Civil Engineering) 2012: Elected Fellow (Canadian Academy of Engineering) 2011: Camille Dagenais Award (Canadian Society for Civil Engineering) 2010: Premier’s Award – Partnership Category (British Columbia) 2001: Tier I Canada Research Chair in Environmental Fluid Mechanics 2001: Journal of Environmental Engineering Editor’s Award (ASCE) Teaching : Courses include CIVL 215 Fluid Mechanics I , CIVL 541 Environmental Fluid Mechanics , and CIVL 598L Contemporary Topics in Physical Limnology . He has been recognized for teaching excellence multiple times, including the 2018-2020 Student Appreciation Award.

• Environmental Fluid Mechanics
• Open-Channel Flow
• Turbulence Structure
• +۷ مورد دیگر

Dr Stuart Cameron is a Senior Research Fellow in the School of Engineering at the University of Aberdeen, where he has been contributing to research since 2007. His work is centered on environmental fluid mechanics, with a focus on open-channel flows, turbulence, sediment transport, and bio-inspired hydrodynamics. He is affiliated with a series of high-impact interdisciplinary research projects involving advanced experimental and theoretical fluid dynamics. His research interests include: Open-channel flow turbulence structure Sediment entrainment and transport mechanisms Flow-biota interactions in aquatic ecosystems Development and error analysis of Particle Image Velocimetry (PIV) techniques Hydrodynamics of bioinspired surfaces and fish-shaped bodies The most recent publications highlight a strong trend in analyzing complex turbulent flows over rough beds, secondary currents, and bio-inspired surface morphologies. His work frequently involves high-resolution experimental techniques and theoretical modeling, often in collaboration with leading researchers such as V. Nikora. Articles span topics from drag forces on sediment particles to hydrokinetic turbine performance and field-based PIV studies in natural water bodies. Notable scientific contributions have been supported by major grants from EPSRC, NERC, and the European Commission. These include projects such as: "Secondary currents in turbulent flows over rough walls" (EPSRC, 2021–2024) "River flow regulation, fish behaviour and status – RIBES" (European Commission, 2020–2023) "Field stereoscopic PIV system for freshwater and marine ecosystems" (NERC, 2019–2020) "Bed friction in rough-bed free-surface flows" (EPSRC, 2014–2017) "HYTECH" (Marie Curie ITN, 2013–2016) "High-resolution numerical and experimental studies of turbulence-induced sediment erosion" (EPSRC & DFG, 2010–2014) Dr Cameron has not advised any named students in the available data, but he collaborates extensively within research teams focused on environmental hydraulics and experimental fluid mechanics. He is involved in the development of advanced measurement systems and theoretical frameworks for understanding complex flows in natural and engineered environments. He is actively engaged in laboratory and field-based research, contributing to both fundamental fluid mechanics and applied environmental engineering challenges. His work bridges engineering, ecology, and physics, particularly in the context of river systems and aquatic habitats.

David J. Olingerمشاهده پروفایل

استاد

• Renewable Energy
• Aerodynamics
• Fluid Dynamics
• +۳ مورد دیگر

David J. Olinger is a Professor of Aerospace Engineering at Worcester Polytechnic Institute (WPI). He specializes in renewable energy technologies, particularly airborne and hydrokinetic systems involving tethered kites and gliders for energy extraction from wind and ocean currents. His research emphasizes experimental and computational approaches to optimize these systems, including a low-cost kite-powered water pump for underdeveloped regions. Education: BS in Engineering (Lafayette College, 1983), MS in Mechanical Engineering (Rensselaer Polytechnic Institute, 1985), PhD in Mechanical Engineering (Yale University, 1990). Research focuses on fluid dynamics, aerodynamics, and fluid-structure interaction. His articles span advancements in tethered systems control, energy harvesting, and simulation techniques. Recent work integrates computational models and physical experiments to refine underwater kite systems and airborne wind energy solutions. Awards: Summer Faculty Research Fellow (1993, U.S. Navy) WPI Teaching Technology Fellowship (2000) ASME National Curriculum Innovation Award Honorable Mention (2001) Advising & Grants: Supervises graduate/undergraduate project teams in MQP (Major Qualifying Project) initiatives. Focuses on applied engineering solutions, such as renewable energy systems and fluid dynamics experiments. Labs/Teams: Leads a research group developing emerging energy technologies, emphasizing interdisciplinary collaboration between mechanical engineering and fluid dynamics.

Qiwei Yaoمشاهده پروفایل

استاد

• Statistical Inference
• Time Series Analysis
• High-Dimensional Statistics
• +۶ مورد دیگر

Qiwei Yao is a Professor of Statistics at the Department of Statistics, London School of Economics (LSE), where he maintains an active research program in statistical methodology and applications. His office is located in Columbia House, Room 7.16 at LSE's Houghton Street campus in London. Professor Yao's research focuses on statistical inference for complex time series, with particular expertise in high-dimensional time series, dynamic networks, spatio-temporal processes, functional time series, nonlinear time series, and high-frequency data. His work bridges theoretical statistics with practical applications, especially in financial econometrics. He has developed innovative methodologies for dimension reduction, factor modeling, and network analysis that have become influential in the field. His recent publications reveal a strong trend toward developing statistical methods for increasingly complex data structures, particularly focusing on high-dimensional and network-based time series. His work integrates machine learning techniques with traditional statistical approaches, as evidenced by papers on deep learning for Markov property testing and tensor decompositions for matrix time series. There's also a clear emphasis on privacy-preserving methods and differential privacy in network analysis. Professor Yao has secured substantial research funding through multiple EPSRC Programme Grants and Research Projects, including the EPSRC Programme Grant for 'Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS)' and 'Network Stochastic Processes and Time Series (NeST)'. He also leads the EPSRC Research Project on 'Statistical Network Analysis: Model Selection, Differential Privacy, and Dynamic Structures' and has collaborated with industry partners like Andurand Capital Management on projects such as 'Forecasting Oil Prices Based on Quantitative Methods'. His research has significant applications across various domains, particularly in energy forecasting (electricity load prediction), financial modeling (volatility modeling, oil price forecasting), and ecological modeling (spatio-temporal population dynamics). Professor Yao maintains strong collaborative relationships with researchers across multiple institutions and disciplines.