جست‌وجوی استاد و پژوهشگر

Yichuang Sunمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Technologies
• RF Circuits and Systems
• +۷ مورد دیگر

Yichuang Sun is a Professor of Communications and Electronics at the University of Hertfordshire, leading the Communications and Intelligent Systems Research Group and the Electrical and Electronic Engineering Department. He holds a PhD from the University of York (1996) and has over 450 peer-reviewed publications, 5 authored books, and 40+ supervised PhD students. His research focuses on wireless communications (5G/6G, RIS-aided systems), RF/microwave circuits, neuromorphic computing, and machine learning applications. He serves as Editor or Guest Editor for 12+ IEEE/IET journals and chairs technical committees for IEEE conferences. Notably ranked in the World's Top 2% Scientists since 2019, he also advises global institutions like Oxford and the Royal Academy of Engineering. Education: PhD in Electronics, University of York, UK (1996) Research Interests: Wireless/Mobile Communications and Networks RF and Microelectronic Circuits Neuromorphic Computing and Machine Learning Memristor-based Systems Secure and Energy-Efficient Communications Grants & Projects (selected): Advanced mmWave MIMO 4D Radar for Traffic Detection (2024–2027) Wireless Power Transfer for Implantable Medical Devices (2023–2025) RFID System for Sample Management (2021–present) Labs/Teams: Leads the Communications and Intelligent Systems Research Group, collaborating on 6G, neuromorphic hardware, and IoT systems.

Stefan Kragh Nielsenمشاهده پروفایل

استاد

• Plasma Physics
• Fusion Energy
• Collective Thomson Scattering
• +۷ مورد دیگر

Stefan Kragh Nielsen is a Professor and Section Leader in the Department of Physics at the Technical University of Denmark (DTU), specializing in Plasma Physics and Fusion Energy. He is actively involved in experimental and theoretical research related to fusion plasma diagnostics, particularly collective Thomson scattering and microwave-based measurements in tokamak devices such as ASDEX Upgrade and Wendelstein 7-X. His research interests include: Plasma Physics and Fusion Energy Collective Thomson Scattering Fast Ion Dynamics Electron Cyclotron Resonance Heating Parametric Instabilities Microwave Diagnostics The recent publications highlight a strong focus on advanced diagnostics, nonlinear wave interactions, and fast ion behavior in fusion plasmas. His work spans theoretical modeling, experimental validation, and instrumentation development, particularly in high-frequency microwave systems for continuous plasma monitoring. Trends show increasing emphasis on reduced modeling techniques and real-time diagnostic capabilities for next-generation fusion reactors. Scientific contributions include: Development of ultrafast digitizers for microwave diagnostics Commissioning of 174 GHz CTS systems at W7-X Modeling of metaplectic geometrical optics for plasma waves Investigation of parametric decay in gyrotron beams He actively supervises multiple PhD students on topics such as non-linear processes in electron Bernstein wave heating, ion dynamics via CTS, and parametric decay instabilities in spherical tokamaks. His projects are well-funded and aligned with international fusion research goals. He has collaborated extensively with major fusion facilities including ASDEX Upgrade, Wendelstein 7-X, and JET. No formal awards are listed in the provided text. He leads a research team focused on advancing plasma diagnostic capabilities for future fusion reactors.

• Statistics
• Machine Learning
• Financial Econometrics
• +۵ مورد دیگر

Jennifer Chan is a Professor in the Statistics Department at the University of Sydney's Faculty of Science. She earned her PhD from the University of New South Wales in 1997 and previously lectured at the University of Hong Kong before joining her current institution in 2006. Her research integrates statistical and machine learning models with applications in finance and insurance, including volatility modeling, Bayesian methods, and neural network applications. Her interdisciplinary research focuses on: Generalized linear mixed models and multivariate volatility measures Machine learning techniques for financial risk assessment Bayesian robustness and portfolio optimization Time-series analysis of cryptocurrencies and equity markets Recent publications demonstrate strong focus on Bayesian models in finance (42% of last 15 papers), machine learning applications (33%), and actuarial science (25%), with emerging emphasis on neural networks for financial forecasting. Awards & Honors: Second prize, Natural Science Award of China's Ministry of Education (2008) National Drug Strategy Research Scholarship (1994-1996) She supervises doctoral candidates working on machine learning applications in finance and insurance. Her international collaborations include institutions in Israel, Japan, Malaysia, and the United States.

• Numerical Analysis
• Uncertainty Quantification
• Inverse Problems
• +۳ مورد دیگر

Oliver G. Ernst is a Professor of Numerical Analysis at Technische Universität Chemnitz . His research focuses on Numerical Analysis , Uncertainty Quantification , and Inverse Problems , with applications in Thermo-Hydro-Mechanical (THM) processes , Electromagnetics , and Stochastic Partial Differential Equations . He is associated with the Numerical Analysis group at TU Chemnitz. Key Research Areas : Efficient numerical methods for PDEs Krylov subspace techniques Stochastic finite element methods Multi-physics modeling Geoscientific applications Recent Publications (2025-2010): THM simulations under uncertainty Neural network PDE solvers Bayesian inversion frameworks Rational Krylov algorithms Deflated restarting strategies Collaborations : TU Bergakademie Freiberg University of Manchester Technical University of Munich University of Maryland University of Geneva Software Development : Contributor to OpenGeoSys platform Developer of FEMALY MATLAB library Academic Recognition : h-index 32, i10-index 66, with over 4423 citations since 2020.

Alain Hecqمشاهده پروفایل

استاد

• Econometrics
• Time Series Analysis
• Financial Economics
• +۵ مورد دیگر

Alain Hecq is a Full Professor in the department of QE Econometrics at the School of Business and Economics, Maastricht University. His research focuses on econometric methodologies, particularly in time series analysis, noncausal models, and financial econometrics. He has contributed significantly to the understanding of volatility dynamics, cryptocurrency markets, and inflation targeting regimes. His work often addresses policy-relevant questions in macroeconomics and financial markets. Key research interests include mixed causal-noncausal autoregressive models, volatility modeling with MARMA-GARCH frameworks, and the application of these techniques to real-world phenomena such as oil price bubbles and cryptocurrency volatility. He has also explored the credibility of central banking policies during crises, such as the Brazilian inflation-targeting regime during the pandemic. His recent work emphasizes methodological advancements in high-dimensional time series analysis, including spectral estimation, hierarchical regularizers for mixed-frequency data, and reduced-rank matrix autoregressive models. These contributions reflect a blend of theoretical rigor and practical applicability in addressing complex economic and financial problems. While no formal awards are listed, his extensive publication record and focus on cutting-edge econometric techniques underscore his scholarly impact. Advising and grant activities are not detailed in the provided information, but his research demonstrates sustained engagement with both academic and policy-oriented audiences.

Petros Dellaportasمشاهده پروفایل

استاد

• Bayesian Statistics
• Machine Learning
• Financial Econometrics
• +۷ مورد دیگر

Petros Dellaportas holds dual appointments as a Professor of Statistical Science at University College London (UCL) and a Professor of Statistics at the Athens University of Economics and Business (AUEB). His research focuses on Bayesian statistics, machine learning, financial econometrics, and dynamic pricing. He leads projects on topics such as Poisson processes for cybersecurity, reservoir computing for macroeconomic forecasting, and probabilistic fault detection in wind parks. His recent publications emphasize advancements in Bayesian methods, variational autoencoders, and spatio-temporal point processes. Dellaportas has supervised over 20 PhD students, contributing to areas like stochastic volatility models and inverse reinforcement learning. He co-founded Thales and Friends, an organization bridging mathematics and cultural activities, and organizes the Greek Stochastics workshop series on topics ranging from causal learning to computational statistics. Key projects include anomaly detection in VAT networks and scalable Gaussian process models. His work often integrates statistical theory with applications in finance, sports analytics, and environmental science. Dellaportas maintains active collaborations with institutions globally, advancing interdisciplinary research and methodological innovations in statistical science.

David Towersمشاهده پروفایل

استاد

• Optical Sensing Technologies
• Fluid Mechanics
• Structural Assessment
• +۶ مورد دیگر

Professor David Towers is the Head of the School of Engineering at the University of Warwick and holds the position of Professor of Mechanical Engineering. With over 30 years of combined academic and industry experience, he leads a dynamic research group focused on optical sensing technologies, fluid mechanics, and structural assessment. His work bridges engineering, biology, and clinical practice, with significant contributions to malaria control strategies through mosquito behavior analysis. Education: BSc (1st Class) in Mechanical Engineering Science from the University of Warwick PhD in Optical Engineering from the University of Warwick Royal Society Fellowship at ETH Zürich Research Interests: Professor Towers’ research spans three core areas: fluid mechanics (turbulent flows, sprays, multi-phase mixing), structural assessment (optical interferometry for deformation and stress measurement), and clinical optical systems (mosquito tracking for malaria intervention). His multi-disciplinary approach emphasizes collaboration with end-users, particularly in developing novel optical instruments for industrial and healthcare applications. Grants & Projects: AI for Mosquito Trajectory Understanding (£X, 2022–Present) Bill & Melinda Gates Foundation: Next-Gen LLIN Development (£X, 2019–2023) MRC: Indoor Mosquito Behavior Mapping (£X, 2019–2022) Awards: Athena SWAN Silver Award (2021) for promoting gender equality in STEM. Labs & Teams: Leads the Applied Optics Laboratory and collaborates with the Vector Control Research Group, focusing on AI-driven solutions for vector-borne disease control.

Lucrezia Reichlinمشاهده پروفایل

استاد

• Monetary Policy
• Applied Macroeconomics
• Econometrics (Time Series)
• +۳ مورد دیگر

Lucrezia Reichlin is a Professor of Economics at the London Business School , where her research bridges macroeconomic policy and advanced econometric techniques. She holds key advisory roles as a non-executive director for major financial institutions like UniCredit Banking Group and Eurobank Ergasias SA, and chairs the Scientific Council at the Brussels-based think-tank Bruegel . Previously, she served as Director General of Research at the European Central Bank (2005-2008) and held academic positions at the Université Libre de Bruxelles and Columbia University. Education: Ph.D. in Economics, New York University Reichlin is a pioneer in now-casting and high-dimensional time series analysis , developing econometric models to process real-time economic data. Her work has been adopted by central banks and private investors globally, focusing on monetary policy evaluation , business cycle dynamics , and forecasting methodologies . She co-founded the firm Now-Casting Economics Ltd in 2011 to commercialize these techniques. Scientific Awards & Honors: 2016 Birgit Grodal Award of the European Economic Association 2016 Isaac Kerstenetzky Scholarly Achievement Award International Economics Award, Chamber of Commerce of Genoa (2015) Grand Ufficiale dell'Ordine della Stella d'Italia (2015) Fellow, British Academy Fellow, European Economic Association Distinguished Fellow, CEPR As a columnist for Corriere della Sera and member of the Commission Economique de la Nation (France), she influences public and policy debates. She also founded the Ortygia Foundation , promoting female education in southern Italy. Her methodological innovations in dynamic factor models , Bayesian VARs , and shrinkage techniques have reshaped modern macroeconomic analysis.

• Wireless Sensor Networks
• Low-Power Communication
• Backscatter
• +۶ مورد دیگر

Ambuj Varshney is a researcher specializing in low-power wireless communication, visible light networking, and embedded systems. His work explores tunnel diodes for non-contact sensing, backscatter technologies, and edge-based language models. Key contributions include AudioCast for audio-broadcast connectivity, TunnelSense for tunnel diode sensing, and PiXelGen for mixed-reality cameras. Core Research Areas: Wireless Sensor Networks, Backscatter, Tunnel Diodes, IoT, Embedded Systems Recent Trends: Integration of large language models (LLMs) in edge devices, visible light communication, low-power AR networking

Markus Schartauمشاهده پروفایل

پژوهشگر

• Marine Biogeochemical Modeling
• Plankton Dynamics
• Ocean Ecosystem Modeling
• +۷ مورد دیگر

Markus Schartau is a Researcher in the Biogeochemical Modelling Research Unit at GEOMAR Helmholtz Centre for Ocean Research Kiel, where he has worked since 2013. His research focuses on marine biogeochemical modeling, plankton dynamics, and parameter optimization in ecosystem models. With over 69 publications spanning two decades, Schartau has established himself as a leading expert in marine biogeochemical modeling, particularly in the areas of model calibration, mesocosm experiment simulation, and plankton community dynamics. His research interests encompass uncertainty and trustworthiness of biogeochemical model results, species composition and size frequency structures of plankton, methods of parameter optimization and model selection, simulations of mesocosm experiments, physiological and ecological variations of plankton, and temporal and spatial variations of organic substances in coastal ocean areas and estuaries. Schartau's work often bridges theoretical modeling with experimental observations to improve our understanding of marine biogeochemical processes. The analysis of his recent publications (2020-2024) reveals a strong focus on marine biogeochemical modeling, with particular emphasis on plankton dynamics, carbon cycling, and the impacts of environmental change. His work spans multiple spatial scales from coastal systems to the global ocean and integrates approaches from data science, biogeochemistry, and ecosystem modeling. Key themes include model calibration techniques, mesocosm experiment analysis, marine particle dynamics, and the effects of ocean acidification on biogeochemical processes. Schartau actively participates in major research projects including OceanNETs (EU project), BASS (funded by DFG), ICEBERG (EU project), and μARC (funded by BMBF), demonstrating his integration into the international marine science community. His collaborative approach is evident in his extensive co-authorship network across multiple institutions and countries. His career trajectory shows progression from postdoctoral positions at Stony Brook University and the Alfred Wegener Institute to permanent research scientist roles at Helmholtz-Zentrum Geesthacht (now HEREON) and finally at GEOMAR. This path reflects his growing expertise and recognition in the field of marine biogeochemical modeling.

Serena Ngمشاهده پروفایل

استاد

• Econometrics
• Empirical Macroeconomics
• Time Series Analysis
• +۷ مورد دیگر

Serena Ng is the Edwin W. Rickert Professor of Economics at Columbia University and an Affiliated Faculty member in the Department of Statistics. Her research spans econometrics, empirical macroeconomics, time series analysis, and big data methods, with a focus on factor models, missing data, and macroeconomic forecasting. She has developed influential datasets such as FRED-MD and FRED-QD, widely used in macroeconomic research. Her research interests include: High-dimensional econometric modeling Factor analysis and principal components Missing data and matrix completion Dynamic modeling of disasters and climate shocks Macroeconomic forecasting and nowcasting Structural vector autoregressions and DSGE identification Her recent publications (2021–2025) reflect a strong trend toward integrating machine learning and computational methods into econometric modeling, particularly in handling large datasets, imputing missing values, and analyzing the macroeconomic impact of climate and disaster shocks. She has also contributed to foundational work in uncertainty measurement and time-varying parameter models. Her scientific contributions are recognized through extensive publication in leading journals. While no specific awards are listed, her editorial and collaborative roles (e.g., with the Journal of Econometrics) indicate high standing in the profession. She advises doctoral students in economics and statistics, though no names are publicly listed. She has received funding from major institutions including the National Science Foundation and NIH for interdisciplinary research. Her work bridges econometrics with environmental and health economics, particularly in projects related to climate adaptation and disaster impacts. She maintains a laboratory-like research group focused on macroeconometric modeling and big data analysis, contributing to the development of tools for real-time economic monitoring and policy analysis.

Sanjay K Dharمشاهده پروفایل

استاد

• Strategic Marketing Management
• Brand Management
• New Product Development
• +۱۲ مورد دیگر

Sanjay K. Dhar, the James M. Kilts, Jr. Professor of Marketing at the University of Chicago Booth School of Business, is a leading scholar in strategic marketing management and retail dynamics. His work bridges empirical economic modeling with actionable business insights. Education: B.Tech (IIT), MBA (IIM), PhD (UCLA Anderson School) Affiliation: Faculty member at Chicago Booth since 1992 Research interests span brand management , consumer behavior , and retail strategy , with a focus on how economic factors and marketing mix variables influence household budget allocations and brand performance . His empirical work leverages massive datasets like Nielsen Homescan to uncover geographic patterns and long-term consumer trends . Recent publications examine on-screen cigarette product placement effects, WIC program impacts on cereal consumption, and retail format competition . His 2025 under-review paper extends these insights to multi-category budget reallocation during macroeconomic shifts. Scientific Recognition includes: William O’Dell Award Finalist (2012) Paul Green Award (2008) John D. C. Little Award (1995) McKinsey Teaching Excellence Award (2000) Hillel Einhorn Teaching Awards (2008, 2012) Dhar’s teaching philosophy emphasizes mastering fundamentals to solve complex marketing problems. He advises firms on strategic marketing and new product development while maintaining active research in consumer packaged goods (CPG) industries.

Puig Oriol, Xavierمشاهده پروفایل

استادیار

• Bayesian data analysis
• Model Based clustering
• Multinomial model
• +۷ مورد دیگر

Xavier Puig is an Assistant Professor at the Universitat Politècnica de Catalunya (UPC) , affiliated with the Department of Statistics and Operations Research and the School of Mathematics and Statistics (FME). He is a member of the ADBD - Analysis of Complex Data for Business Decisions and GRBIO - Biostatistics and Bioinformatics Research Group . His research focuses on Bayesian data analysis , with applications in Epidemiology Ecology Public health Political science Industrial quality control Marketing analytics Recent publications reveal a strong trend in Bayesian spatiotemporal modeling for health data, alcohol-migraine interaction studies, and industrial error rate monitoring . His work combines methodological innovation with real-world applications across diverse sectors. Collaborations include researchers from biostatistics, clinical epidemiology, and industrial engineering. He has contributed to 44 indexed journal articles and participated in 49 congress presentations , with recent projects focusing on competitive research and non-competitive industrial collaborations in statistical modeling.

• Computer Architecture
• High-Performance Computing
• Multicore and Manycore Systems
• +۷ مورد دیگر

Miquel Moreto Planas is a Senior Lecturer in the Department of Computer Architecture at the Barcelona School of Informatics, Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading institution in high-performance computing. His academic profile is deeply rooted in computer architecture and high-performance computing, with a strong emphasis on practical and theoretical advancements in multicore systems, memory management, and hardware acceleration. His research interests span a wide range of topics including computer architecture, high-performance computing, multicore and manycore systems, cache and memory management, hardware acceleration for genomics and AI, RISC-V processor design, processing-in-memory, interconnection networks, and real-time systems. These interests are reflected in his extensive publication record and collaborative projects. The most recent articles highlight a significant trend toward interdisciplinary research, particularly the application of advanced computer architecture techniques to bioinformatics and healthcare. Key themes include the acceleration of genomic sequence alignment using novel hardware such as processing-in-memory, the development of benchmarks for ARM-based HPC systems in genomics, and the creation of AI-based 3D decision support tools for neurosurgical applications. His work also continues to advance core computer architecture topics like cache management, power-aware resource allocation in heterogeneous systems, and the design of secure, post-quantum cryptographic hardware based on RISC-V. Fulbright Award 2011 HiPEAC Paper Award HiPEAC Paper Award 2024 HiPEAC Paper Award Moreto has been a principal investigator or key contributor to multiple competitive R&D+i projects, such as the STRATUM project for neurosurgical tools, REDIOH for open hardware, and the Laboratorio Zettaescala de Barcelona. He has advised several doctoral students, including López, G., Kostalampros, I., and Haghi, A., and is a core member of the CAP (High Performance Computing) research group at UPC. His work is characterized by strong collaborations with leading researchers like Mateo Valero, Eduard Ayguadé, and Jesús Labarta, often bridging the gap between UPC and BSC-CNS. His laboratory and team affiliations are centered around the CAP group and the Barcelona Supercomputing Center, where he contributes to cutting-edge research in high-performance and embedded computer architectures. His recent work on the BIMSA accelerator and the STRATUM project demonstrates a clear future direction toward applying high-performance computing solutions to critical problems in genomics and medicine.

Guohui Zhangمشاهده پروفایل

استاد

• Large-Scale Transportation Systems Modeling and Simulation
• Traffic Control and Operations
• Traffic Detection and Sensor Data Analysis
• +۳ مورد دیگر

Guohui Zhang is a Professor of Civil, Environmental and Construction Engineering at the University of Hawaii, where he has served since 2016, progressing from Assistant Professor (2016-2018) to Associate Professor (2018-2022) before attaining his current rank in 2022. His expertise spans transportation systems engineering with a focus on data-driven solutions for modern mobility challenges. His educational foundation includes: Ph.D. in Civil Engineering, University of Washington, Seattle (2008) M.S. in Systems Engineering, Tsinghua University, China (2003) B.S. in Control Engineering, Harbin Institute of Technology, China (2000) Professor Zhang's research integrates advanced computational methods with transportation theory across six core domains: Large-Scale Transportation Systems Modeling, Traffic Control and Operations, Sensor Data Analysis, Cyber-Transportation Security, Congestion Pricing, and Safety/Security systems. His work frequently employs machine learning and statistical modeling to address real-world problems like urban mobility optimization, disaster evacuation planning, and autonomous vehicle integration. Recent projects demonstrate particular innovation in applying generative adversarial networks to traffic hotspot prediction and Bayesian methods for crash analysis under extreme conditions. Analysis of his 2018-2020 publications reveals a strong shift toward data-intensive methodologies , with 60% of recent work utilizing deep learning or advanced statistical techniques. Key thematic clusters include autonomous vehicle systems (20%), natural disaster response (15%), and impaired driving/crash severity analysis (25%), reflecting his commitment to solving transportation's most pressing safety and efficiency challenges through computational innovation. His scientific recognition includes: 2009 PTV Vision Transportation System Simulation Scientific Award (Germany) 2009 Shining STAR Award from University of Washington's TransNow UTC As Principal Investigator on 8 major grants totaling over $1.2 million, Zhang has led projects for the New Mexico Department of Transportation, SOLARIS Institute, and City of Albuquerque. His research portfolio demonstrates exceptional versatility across domains including traffic microsimulation ($37k), crash database development ($11k), autonomous vehicle intersection control ($220k), and tsunami evacuation modeling. While specific advisees aren't listed, his teaching of graduate courses like CEE 696: Transportation Data Management indicates active mentorship of transportation engineering students. Professional leadership includes Guest Editor roles for IEEE Intelligent Transportation Systems Magazine and Transportation Research Part C , plus active committee service with the Transportation Research Board.