جست‌وجوی استاد و پژوهشگر

Tony Yangمشاهده پروفایل

استاد

• Structural Engineering
• Earthquake Engineering
• Smart Construction Technologies
• +۳ مورد دیگر

Dr. Tony Yang is a Professor in the Department of Civil Engineering at the University of British Columbia (UBC), affiliated with the Faculty of Applied Science. He leads the UBC Smart Structures research group, focusing on innovative technologies for structural and earthquake engineering. Yang holds a B.Sc. from the University of Buffalo (2001), an M.Sc. (2002), and a Ph.D. from UC Berkeley (2006). His research spans advanced numerical simulations, robotic construction, AI-driven monitoring, and seismic design of resilient infrastructure. Yang is a Fellow of the Canadian Academy of Engineering and serves on 15+ technical committees, including the National Building Code of Canada’s seismic design committee. His work integrates 5G networks, robotics, and AI to advance smart construction technologies. Recent projects include a $812K industrial grant (2024) for 5G-enabled autonomous construction systems, AI inspection robots, and rapid construction methodologies. His research interests include: robotic construction automation, AI-based structural monitoring, performance-based seismic design, and sustainable infrastructure. Key contributions include over 250 publications, 14 patents, and influential roles in high-impact journals like Computer-Aided Civil and Infrastructure Engineering . Yang’s accolades include the EGBC Meritorious Achievement Award (2020), New Zealand Concrete Society Technology Award (2019), and the H.A. Krentz Research Award (2014). His lab develops cutting-edge solutions for autonomous construction sites, advanced structural fuses, and AI-driven damage detection systems.

Matteo Willeitمشاهده پروفایل

پژوهشگر

• Climate Modeling
• Earth System Analysis
• Ice Sheet Dynamics
• +۵ مورد دیگر

Dr. Matteo Willeit is a Senior Scientist at the Potsdam Institute for Climate Impact Research (PIK) in the Department of Earth System Analysis, Working Group Long-Term Trajectories. His research focuses on modeling past and future climate changes using Earth system models of intermediate complexity, particularly the CLIMBER-X model. He has been actively contributing to the German Climate Modeling Initiative PalMod across multiple phases. Dr. Willeit earned his PhD in Physics (Dr. rer. nat.) from the Potsdam Institute for Climate Impact Research and at the University of Potsdam, focusing on vegetation-climate and carbon-cycle feedbacks. Prior to that, he completed his graduation in Physics at the University of Bologna with a focus on climate physics and meteorology. Dr. Willeit's research spans multiple areas of climate science, with particular expertise in: Modeling the stability of Greenland and Antarctic ice sheets Simulating glacial-interglacial cycles throughout the Quaternary period Investigating the Earth's carbon cycle and its interactions with climate Studying climate tipping points and planetary boundaries Developing and applying Earth system models of intermediate complexity Analysis of Dr. Willeit's recent publications (2023-2025) reveals a strong focus on understanding climate system stability, particularly regarding ice sheets, ocean circulation, and carbon cycle feedbacks. His work frequently employs the CLIMBER-X Earth system model to investigate both past climate transitions and future climate scenarios. A significant portion of his recent research addresses climate tipping points, with particular attention to the Atlantic Meridional Overturning Circulation and ice sheet dynamics. His publications demonstrate an interdisciplinary approach that bridges paleoclimatology, climate modeling, and contemporary climate change research. Dr. Willeit has been actively involved in major research initiatives: PalMod Phase III (2024-present): Investigating future stability of Greenland and Antarctic ice sheets PalMod Phase II (2021-2023): Modeling the last glacial cycle PalMod Phase I (2017-2020): Modeling the last glacial cycle DFG-funded project (2014-2016): Studying major transitions in Quaternary climate GREENCYCLES II Initial Training Network (PhD work): Analyzing vegetation-climate and carbon-cycle feedbacks Dr. Willeit works within the Earth System Analysis department at PIK, contributing to the development and application of the CLIMBER-X Earth system model. His research connects with broader efforts at PIK to understand planetary boundaries and climate tipping points, as reflected in PIK's Planetary Health Check initiative.

• Numerical Analysis
• Image Processing
• 3D Reconstruction
• +۵ مورد دیگر

Silvia Tozza is an Associate Professor at the Department of Mathematics, University of Bologna. Her research focuses on numerical analysis, image processing, 3D reconstruction, and mathematical modeling in vision. She has expertise in Hamilton-Jacobi equations, shape-from-shading, and computational geometry. Her recent work emphasizes numerical schemes for PDEs and applications in computer vision, such as image inpainting and photometric stereo. She teaches courses in Mathematics for Environmental Sciences and Architecture-Engineering, with office hours available upon email confirmation. Her articles explore topics like semi-Lagrangian schemes, multi-view normal estimation, and thermal insulation optimization. She actively contributes to interdisciplinary fields linking 3D vision to additive manufacturing and astrophysical imaging.

• Metamaterials
• Liquid Crystals
• Terahertz Technology
• +۵ مورد دیگر

Janusz Parka is a full Professor at Warsaw University of Technology within the Faculty of Advanced Technologies and Chemistry. His research focuses on the intersection of advanced materials and optical technologies, with particular expertise in metamaterials and liquid crystal applications. He maintains an active research program with numerous recent publications in high-impact journals and conference proceedings. Professor Parka's research centers on metamaterials, particularly hyperbolic and epsilon-near-zero varieties, with emphasis on tunable optical properties. His work extensively explores liquid crystal integration with metamaterial structures for applications in terahertz technology, optical modulation, and nanophotonics. Key research areas include electromagnetic wave manipulation, optical singularities, and the development of tunable devices for communication and sensing applications. His interdisciplinary approach bridges physics, materials science, and electrical engineering to create novel optical solutions. Analysis of Professor Parka's recent publications reveals a strong focus on tunable optical devices using liquid crystal-metamaterial hybrids. His research demonstrates consistent innovation in controlling electromagnetic properties through material composition and external stimuli. The work spans fundamental physics investigations to practical device implementations, with particular emphasis on terahertz applications, optical modulation, and nanoscale light manipulation. His collaborations with researchers across Europe indicate an active international research network. Professor Parka maintains an active research group with numerous collaborators including Pianelli Alessandro, Dudek Michał, Kowerdziej Rafał, and others. His work appears in leading optics and materials science journals including Scientific Reports, Optics Express, and Advanced Optical Materials. While specific grant information isn't detailed in the provided text, his extensive publication record suggests successful funding for his research program in metamaterials and liquid crystal technologies. Based on publication patterns and institutional affiliation, Professor Parka likely leads or participates in research teams focused on advanced optical materials at Warsaw University of Technology. His work with liquid crystal-metamaterial hybrids suggests laboratory facilities for optical characterization, material synthesis, and electromagnetic testing, particularly in the terahertz frequency range.

Florentina Nicolauمشاهده پروفایل

دانشیار

• Nonlinear automation
• geometric control
• differential flatness
• +۳ مورد دیگر

Florentina Nicolau is an Associate Professor at the École Nationale Supérieure d'Electronique, d'Electrotechnique, d'Informatique, d'Hydraulique et de Thermique (ENSEA). She is affiliated with the Quartz Laboratory and the Non-Linear Automatic research team. Her expertise lies in nonlinear automation, geometric control, differential flatness, linearization techniques, observers, and fault detection. Her research emphasizes practical applications in control systems and electrical engineering. Dr. Nicolau's work focuses on advancing control methodologies for complex systems, including adaptive cruise control, power electronics, and fault diagnosis. She has supervised multiple research internships, Master’s theses, and PhDs. Her contributions bridge theoretical control principles with real-world engineering challenges. Her publications highlight innovative approaches in flatness-based control, energy management in parallel choppers, and fault detection in grid-connected systems. She actively contributes to the control systems community through peer-reviewed articles and collaborations within the Quartz Laboratory.

• Control Engineering
• Dynamical Systems
• Electrical Engineering
• +۱ مورد دیگر

Kåre Bjørvik is an Assistant Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. His work spans control engineering, dynamical systems, and electrical filter design. Research Interests Control Engineering and Cybernetics Dynamical Systems and Nonlinear Modeling Applied Mathematics in Electrical Engineering Publications Authored textbooks and compendiums on control systems and dynamical systems Academic lectures on electrical filter design using complex numbers

Ning Ningمشاهده پروفایل

استادیار

• Stochastic Processes
• Markov Chains
• Time Series Analysis
• +۴ مورد دیگر

Ning Ning is an Assistant Professor in the Department of Statistics at Texas A&M University, affiliated with the Institute of Data Science and the Institute for Quantum Science and Engineering. She co-founded the Stochastic Processes Seminar in the Department of Mathematics. Her research focuses on stochastic processes, Markov chains, machine learning, and quantum computing. Prior to her academic career, she worked as a software developer and database architect in Los Angeles for four years, specializing in data analysis and parallel computing. Education: B.S. in Math from Shandong University (China Math Base), M.S. in Math from the University of Southern California, and Ph.D. in Statistics and Applied Probability from UCSB. She held postdoctoral positions at the University of Washington (Applied Math) and the University of Michigan (Statistics). Research interests include stochastic algorithms, Monte Carlo methods, hidden Markov models, and quantum counterparts of classical methods. She is an Associate Editor for Bayesian Analysis (since 2025), Journal of Computational and Graphical Statistics (since 2024), and Statistics and Computing (since 2023). Recent talks and contributions include invited sessions at the Bayes Comp 2025 conference and the KAUST Stochastic Numerics Workshop. Her work spans theoretical advancements and computational innovations in statistical methods, with applications to large-scale data analysis and machine learning.

Jonathan Poterjoyمشاهده پروفایل

دانشیار

• Data Assimilation
• Numerical Weather Prediction
• Atmospheric Dynamics
• +۳ مورد دیگر

Jonathan Poterjoy is an Associate Professor in the Department of Atmospheric and Oceanic Science at the University of Maryland, serving as Graduate Program Director. He holds a Ph.D. in Meteorology from Pennsylvania State University and a BS in Meteorology and Applied Mathematics from Millersville University. His research focuses on advancing data assimilation techniques for Earth system models, particularly addressing challenges in probabilistic forecasting of hazardous weather like tropical cyclones and severe storms. He has held postdoctoral positions at NOAA’s Hurricane Research Division and NCAR’s Mesoscale and Microscale Meteorology Laboratory. His current projects include improving NOAA’s Global Forecast System through enhanced parameterization and sea ice data assimilation, as well as developing methods for quantifying uncertainty in novel atmospheric measurements. Notable grants include NSF CAREER Award AGS1848363 and NOAA grants NA19NES432000 and NA22OAR4590184. His work emphasizes interdisciplinary collaboration with modelers, observation specialists, and uncertainty quantification experts to enhance environmental prediction systems.

Igor Cialencoمشاهده پروفایل

استاد

• Quantitative Finance
• Statistical Inference for Stochastic PDEs
• Stochastic Control
• +۳ مورد دیگر

Igor Cialenco is a Full Professor in the Department of Applied Mathematics at Illinois Institute of Technology (College of Computing). He holds a Ph.D. in Applied Mathematics from the University of Southern California (2007). Research Interests : Quantitative Finance, Statistical Inference for Stochastic PDEs, Stochastic Control, Environmental Finance, and Functional Analysis. Professional Roles : Managing Editor for the International Journal of Theoretical and Applied Finance, and editorial board member of multiple journals including SIAM Journal on Financial Mathematics. Research Trends : His recent publications focus on stochastic modeling in environmental finance (e.g., groundwater markets), robust control under model uncertainty, and statistical inference for SPDEs. The keywords span Financial Mathematics, Stochastic Processes, Environmental Modeling, and Statistical Learning. Scientific Awards : 2024 Researcher to Know (ISTC), 2024 College of Computing Dean's Excellence Award for Research, multiple Dean's Excellence awards in teaching and research. Mentorship & Funding : Mentored numerous PhD and MS students in quantitative finance and SPDEs. Current NSF grant DMS-2407549 supports research on stochastic modeling for water rights management. Past NSF grants include DMS-1907568 and DMS-0908099.

Meeko Oishiمشاهده پروفایل

استاد

• Autonomous Cyber-Physical Systems
• Human-Centered Control Systems
• Stochastic Reachability Analysis
• +۳ مورد دیگر

Dr. Meeko Oishi is a Professor in the Department of Electrical and Computer Engineering at the University of New Mexico. She holds a PhD in Mechanical Engineering from Stanford University (2004) with a minor in Electrical Engineering, and undergraduate degrees from Princeton University (BS, 1998). Her research focuses on ensuring safety in autonomous cyber-physical systems through stochastic reachability analysis, human-in-the-loop control, and probabilistic methods. Key areas include human-centric system design, motor control in Parkinson's disease, and resilient autonomous systems. Education: PhD, Mechanical Engineering, Stanford University, 2004 MS, Mechanical Engineering, Stanford University, 2000 BS, Mechanical Engineering, Princeton University, 1998 Research Interests: Stochastic reachability and optimal control Human-in-the-loop system design Non-parametric learning and control Cyber-physical system safety Applications in robotics, aerospace, and healthcare Awards & Recognition: NSF BRITE Fellow (2023-2028) Senior Faculty Research Excellence Award (UNM School of Engineering, 2020) NSF CAREER Award (2013) UNM Regents' Lecturer (2015-2018) Truman Fellowship (2005) Advising & Labs: Advises ~30 graduate and undergraduate students in control systems and autonomy Directs the Hybrid Systems and Controls Lab Leads NSF CPS Frontier on Cognitive Autonomy Key Collaborations: NSF RAISE Traineeship (Resilient AI for Autonomous Systems) Clinical testbeds for circadian rhythm research Industry partnerships with Sandia National Labs, AFRL, and aerospace firms

• Topological Data Analysis
• Machine Learning
• Biomedical Engineering
• +۳ مورد دیگر

Dhananjay Bhaskar is a Research Fellow in the Department of Genetics at Yale School of Medicine, Yale University. His research integrates topological data analysis, machine learning, and mathematical modeling to address problems in biophysics and biomedical research. He holds a PhD in Biomedical Engineering and Sc.M. in Data Science from Brown University, and degrees in Computer Science and Applied Mathematics from the University of British Columbia. His work spans applications such as immune response analysis, epidermal regeneration, IVF embryo selection, and cancer cell migration. Education: PhD Brown University (2021), ScM Data Science (2021), MSc Applied Mathematics (2017, UBC), BSc Computer Science (2015, UBC). Research interests focus on leveraging interdisciplinary methods to understand complex biological systems. Key areas include topological analysis of single-cell data, machine learning for medical diagnostics, and computational modeling of cellular dynamics. His work on glial scar formation and calcium signaling in epidermis regeneration has advanced understanding of tissue repair mechanisms. Notable recognition includes the 2024 Kavli Postdoctoral Fellowship for his project on neuroenergetic principles in C. elegans neural circuitry. Collaborations include work with Smita Krishnaswamy on immune response prediction and Valentina Greco on epithelial regeneration. Publications highlight contributions across neuroscience, immunology, and cell biology, with recent focus on multimodal AI for psychiatry and geometric scattering methods for molecular analysis.

Guannan Zhangمشاهده پروفایل

استاد

• Machine Learning
• Uncertainty Quantification
• Stochastic Optimization and Control
• +۶ مورد دیگر

Guannan Zhang is a Distinguished Staff Scientist at Oak Ridge National Laboratory (ORNL) and holds joint professorships in the Department of Mathematics and Statistics at Auburn University and the Department of Mathematics at the University of Tennessee. He earned his Ph.D. in applied mathematics from Florida State University (2012) and holds degrees from Shandong University (B.Sc. 2007, M.Sc. 2009). His research focuses on machine learning, uncertainty quantification, stochastic optimization, and nonlinear data assimilation with applications in high-dimensional systems. Key achievements include the DOE Early Career Award (2022), lead PI of the DOE-ASCR-AI4Science grant (2024), and a best paper award at SC24 (2024). He has supervised numerous interns from leading universities and collaborates on projects like diffusion models for scientific computing and generative AI. Professional roles include editorial board membership of the SIAM Journal on Scientific Computing and involvement with SIAM committees. His work bridges applied mathematics and computational science, emphasizing interdisciplinary applications in climate modeling and fusion energy research.

Felipe Espinosa Zapataمشاهده پروفایل

استاد

• Control Systems
• Robotics
• Smart Cities
• +۳ مورد دیگر

Felipe Espinosa Zapata is a Full Professor in the Electronics Department at the University of Alcala, Spain. He holds a Ph.D. in Telecommunications from the University of Alcala (1998) and an M.S. from the Polytechnic University of Madrid (1992). His research focuses on electronic and network control systems applied to intelligent transportation, smart cities, and industrial automation. He has led 18 publicly funded projects and 22 industry-funded initiatives, contributing to 9 patents. He is a co-author of 5 book chapters and over 40 journal articles, with extensive contributions to international conferences. Research interests include adaptive control for autonomous vehicles, event-based sensor networks, and robotic trajectory tracking. He has supervised 7 PhD theses and serves on the editorial boards of two international journals. Notable projects include the GEINTRA group’s work on intelligent transport systems and the ALCOR project optimizing remote robot guidance. He also pioneered the Cuadrelec Chair in railway electronic control systems, collaborating with industry partners like Cuadrelec S.L. His work bridges theoretical control engineering with practical applications, emphasizing energy efficiency in IoT nodes, multi-AGV transportation systems, and self-triggered control mechanisms. Publications span robotics navigation, sensor fusion, and smart city infrastructure, reflecting his interdisciplinary approach to solving complex automation challenges. Education: Ph.D. in Telecommunications (University of Alcala, 1998) M.S. in Telecommunications (Polytechnic University of Madrid, 1992) Key Roles: Full Professor (since 2016), University of Alcala Head of Cuadrelec Chair of Electronic Control Awards and Recognition: Recipient of international collaborative grants and industry partnerships Grants and Projects: 18 public-funded research projects 22 industry-sponsored initiatives Labs and Teams: GEINTRA Research Group: Electronic Engineering Applied to Intelligent Spaces and Transport Cuadrelec Chair: Railway Electronic Control Systems

Adam H. Monahanمشاهده پروفایل

استاد

• Meteorology
• Climate Modeling
• Atmospheric Variability
• +۵ مورد دیگر

Dr. Adam H. Monahan is a Professor in the School of Earth and Ocean Sciences at the University of Victoria. His research focuses on atmospheric and oceanic processes, including stochastic dynamics, boundary layer meteorology, climate variability, and renewable energy meteorology. He is a member of the UVic Climate Modelling Group and has contributed to studies on wind energy, large-scale atmospheric variability, and Arctic climate dynamics. His work integrates statistical methods, stochastic parameterization, and numerical modeling to understand climate systems. Dr. Monahan has advised numerous graduate students and post-doctoral researchers, including current students in BSc, MSc, and PhD programs. His research spans interdisciplinary collaborations, with publications in journals such as Journal of Climate , Journal of Applied Meteorology and Climatology , and Nonlinear Processes in Geophysics . He teaches courses on Earth System Modelling, Atmospheric Sciences, and Dynamic Meteorology. His recent work emphasizes stochastic processes in climate models, Arctic sea ice dynamics, and the impact of boundary layer variability on wind energy systems. He has explored observational constraints on climate projections and the influence of anthropogenic factors on climate extremes.

Keith Blowمشاهده پروفایل

استاد

• Photonics
• Optical Networks
• Optical Processing
• +۴ مورد دیگر

Keith Blow is a Professor in Electronic Engineering at Aston University, leading the Photonics Research Group and the Adaptive Networks Communications Research Group. He holds a BA (First Class Honours) in Physics and Theoretical Physics from Cambridge University (1978) and a PhD in Solid State Physics from the Cavendish Laboratory (1981). Prior to joining Aston in 1999, he worked at BT Research Laboratories, focusing on optical fiber technologies and nonlinear effects. His research spans photonics, optical networks, adaptive communication systems, and energy-efficient protocols. Key areas include soliton-based transmission, nonlinear optical processing, and wireless sensor networks. He has supervised 6 students and contributed to over 99 publications, with notable work on soliton crystals, optical frequency combs, and FSO channel optimization. Blow serves on the editorial board of the Journal of Modern Optics and reviews for conferences like the Advanced Photonics Congress. His labs focus on advancing optical communication systems, network efficiency, and sensor network applications, emphasizing practical implementations of theoretical findings.