جستجوی استاد راهنمای دانشگاهی

Marcelo Lobo Heldweinمشاهده پروفایل

استاد

• Power Electronics
• Sustainable Energy Systems
• Energy Conversion Technologies
• +۳ مورد دیگر

Prof. Marcelo Lobo Heldwein is a Professor and Director of the Chair of High-Performance Converter Systems at the Technical University of Munich (TUM), part of the TUM School of Engineering and Design. His research focuses on power electronic energy converters, addressing challenges in sustainable energy systems through topology design, modeling, and control. He holds a MSc from the Federal University of Santa Catarina (1999) and a PhD from ETH Zurich (2007). Prior to TUM, he was a professor at UFSC (2010–2022). His work emphasizes high-power converter systems, including grid integration, renewable energy, and advanced control strategies like model predictive control. Key contributions include novel topologies for DC transformers, thermal management in subsea systems, and robust control of offshore wind farms. Awards include the Petrobras Inventor Prize (2023) and best paper awards at IEEE conferences (2017, 2015, 2014). Publications span advanced converter design, fault-tolerant systems, and energy transition technologies. Research extends to practical applications like hydrogen electrolyzers and submarine cable systems. He leads a team advancing solid-state transformers and grid-forming converter technologies.

Andreas Stathopoulosمشاهده پروفایل

استاد

• Numerical Linear Algebra
• Scientific Computing
• Parallel Computing
• +۶ مورد دیگر

Overview Andreas Stathopoulos is a Professor in the Department of Computer Science at William & Mary. He specializes in numerical linear algebra, high-performance computing, and scientific computing. His research focuses on eigenvalue methods, iterative solvers, parallel algorithms, and applications in quantum chromodynamics (QCD) and materials science. He developed the PRIMME software package for large-scale eigenvalue problems. Education and Background While his formal education details are not explicitly listed, his academic trajectory aligns with typical roles in computational science, including advanced degrees in computer science or applied mathematics. Research Interests Numerical Linear Algebra: Eigenvalue methods, iterative solvers, preconditioning, and multigrid techniques. Scientific Computing: Applications in QCD, materials science, and kernel-based machine learning. Parallel Computing: Resource management, load balancing, and hybrid computing architectures. Teaching He teaches courses such as CSCI 243 (Discrete Structures), CSCI 653 (Analysis of Algorithms), and CS 780 (Big Data). He also contributed to interdisciplinary courses like UMSA (Undergraduate Modeling, Simulation, and Analysis). Students and Postdocs He has advised numerous PhD and MS students, including Yu Chen (2023), Lingfei Wu (2016), and Jesse Laeuchli (2016), as well as postdoctoral researchers like Konstantinos Liakos (2023–present) and Eloy Romero (2016–2020). Affiliations He collaborates with institutions such as DOE's Jefferson Lab and has contributed to software projects like PRIMME, which addresses large-scale eigenvalue problems in scientific computing.

Amy Dengمشاهده پروفایل

استادیار

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۶ مورد دیگر

Amy Deng is an Assistant Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). Her research focuses on machine learning and data mining applications in social sciences and e-commerce, emphasizing explainable and robust AI techniques for temporal data analysis. She leads the Data Mining research group, contributing to advancements in graph neural networks, domain generalization, and societal event forecasting. Her work integrates causal reasoning, spatiotemporal modeling, and graph-based approaches to address challenges in event prediction and dynamic knowledge representation. Recent projects include developing adaptive normalization techniques for non-stationary time series and contrastive learning methods for graph homophily analysis. Research Interests: Machine Learning, Data Mining, Explainable AI, Temporal Data Analysis, Social Event Forecasting Labs/Teams: Data Mining Group at TU/e Education: Not explicitly listed in available texts, but affiliated with TU/e's academic programs in computer science and data science. Publications highlight contributions to graph neural networks (e.g., SimGCL), causal event modeling, and robust forecasting frameworks. She currently teaches courses on Generative AI Models, aligning with her research in advanced AI techniques.

Alison Ramageمشاهده پروفایل

دانشیار

• Numerical Linear Algebra
• Scientific Computation
• Partial Differential Equations
• +۶ مورد دیگر

Alison Ramage is a Reader in Applied and Industrial Mathematics at the University of Strathclyde's Department of Mathematics and Statistics. Her research focuses on numerical linear algebra, preconditioning techniques for partial differential equations, and applications in liquid crystal modeling, geotechnical engineering, and data assimilation. She holds prestigious fellowships from the Leverhulme Trust and EPSRC, and has led numerous grants and collaborations with industry partners like Hewlett-Packard and Oasys Ltd. Education: PhD in Preconditioned Conjugate Gradient Methods from the University of Bristol (1991), BSc from the University of St Andrews (1987). Research Interests : Numerical Linear Algebra, Scientific Computing, Preconditioning, Liquid Crystals, Data Assimilation, Computational Fluid Dynamics. Her work bridges theoretical mathematics with practical industrial applications, emphasizing efficient algorithms and iterative solvers. Grants and Awards : Multiple EPSRC grants, including a £43K Leverhulme Fellowship (2017) for data assimilation research. Active in editorial roles for SIAM journals and professional societies like SIAM and EMS. Academic Service : Long-standing roles in SIAM, including Board of Trustees and editorial boards. Organized international conferences and workshops on numerical analysis and applied mathematics. Labs/Teams : Co-developed the IFISS software package for incompressible flow simulations, collaborating with global researchers in numerical methods and data science.

• Epidemiology
• Applied Statistics
• Sociology of Inequalities
• +۲ مورد دیگر

Stephen Jivraj is an Associate Professor in Quantitative Social Science at University College London's Department of Epidemiology and Public Health. With a PhD in Social Statistics from the University of Manchester, he leads research on inequalities using quantitative methods and serves as a member of the UCL Q-Step Centre. His expertise spans spatial inequality, life course epidemiology, and statistical methods for social sciences. His research examines neighborhood effects on health across the life course, ethnic density dynamics, and socioeconomic determinants of health using longitudinal datasets like UKHLS and ELSA. Work emphasizes geospatial modeling of deprivation, cross-national comparisons of welfare systems, and methodological innovations in measuring inequality. Publication analyses reveal consistent focus on multilevel modeling, residential mobility effects, and policy-relevant metrics for health disparities. Recent work expands to coastal health impacts and ethnic deprivation indices, showcasing methodological versatility in handling complex spatial and longitudinal data.

• Power Electronics
• Solid-State Transformers
• Medium Voltage Applications
• +۷ مورد دیگر

Andrea Cervone is a Professor at KU Leuven, specializing in power electronics and electrical engineering with a focus on solid-state transformers and power conversion systems. Based at the Thor Park 8310 campus in Genk, Belgium, Cervone conducts research at the intersection of medium voltage applications and power system integration. The research group is actively involved in multiple projects including the ADVANCED SOLID-STATE ELECTRONIC TRANSFORMER (ASSET) initiative and the Solid-State Transformers for Medium Voltage Applications PhD project supervised for Marina Vitali. Dr. Cervone's research interests span power electronics, solid-state transformers, medium voltage applications, electrical power systems, power converters, grid integration, electric drives, multiphase machines, DC-DC converters, and renewable energy systems. The work emphasizes practical applications in power distribution networks, with particular attention to harmonic analysis, stability considerations, and efficiency optimization in modern power conversion systems. Current research demonstrates strong focus on addressing challenges in grid integration of renewable energy sources and improving power quality in hybrid AC-DC networks. The publication record shows a clear trend toward solid-state transformer technology, with numerous papers on input-series-output-parallel configurations, harmonic compensation techniques, and stability analysis. Recent work has expanded into grid impedance estimation, DC data center power supplies, and modulation strategies for dual-port converters. The research consistently addresses practical engineering challenges in power conversion while maintaining strong theoretical foundations in control systems and power electronics. As an academic supervisor, Dr. Cervone currently mentors PhD student Marina Vitali on solid-state transformers for medium voltage applications. The research group maintains strong industry connections through collaborative projects focused on practical power electronics applications, particularly in the energy sector. The group's work spans both theoretical analysis and experimental validation of novel power conversion topologies.

• Power Electronics
• Renewable Energy Systems
• Energy Storage
• +۳ مورد دیگر

Prof. Dylan Lu is a Professor and Head of Discipline for Electrical Power and Energy Systems at the School of Electrical and Data Engineering, University of Technology Sydney (UTS). He holds a Ph.D. in Electronic and Information Engineering from The Hong Kong Polytechnic University (2004). Previously, he served as academic staff at the University of Sydney from 2006 to 2016, progressing from Lecturer to Associate Professor. His research focuses on power electronics, renewable energy systems, and grid integration, with an emphasis on converter topologies, control techniques, and power quality solutions for microgrids and energy storage systems. Prof. Lu's academic leadership includes roles as Associate Editor for IEEE Transactions on Industrial Electronics and IEEE Journal of Emerging and Selected Topics in Power Electronics. He chairs the IEEE NSW Joint Chapter PEL/IES/IAS and is a Senior Member of the IEEE. His teaching contributions include coordinating Renewable Energy Systems studios and supervising graduate projects in areas like electro-thermal modeling of power devices and three-port DC-DC converter synthesis. Research highlights include advancements in cascaded H-bridge converters, battery management systems, and grid-connected inverter control strategies. His work addresses challenges in high-efficiency power conversion, renewable integration, and energy storage reliability. Current projects explore fault-tolerant converter designs and predictive control algorithms for electric vehicle chargers.

Yam Siwakotiمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy Systems
• Multilevel Converters
• +۵ مورد دیگر

Associate Professor Yam Siwakoti holds a position at the University of Technology Sydney (UTS), leading research in power electronics and renewable energy systems. He has affiliations with the School of Electrical and Data Engineering and has collaborated with institutions like Fraunhofer ISE and the University of Oxford. Education: B.Tech in Electrical Engineering from National Institute of Technology, Hamirpur (2005) MEng in Electrical Power Engineering from Norwegian University of Science and Technology and Kathmandu University (2010) PhD in Electronic Engineering from Macquarie University (2014) Research focuses on high-efficiency power converters, multilevel inverters, and sustainable energy systems. Key interests include transformerless grid-connected inverters, battery management systems, and wide bandgap semiconductor applications. Notable achievements include the Friedrich Wilhelm Bessel Research Award (2022) and Green Talent Award (2016). He has supervised over 15 students and holds editorial roles in IEEE journals. His funded research projects focus on extending battery lifetimes and high-frequency magnetics design. Labs/Teams: Active in UTS' Power Electronics and Renewable Energy research groups, collaborating with industry partners like Re:Start on EV charging solutions.

• Food Security
• Statistical Analysis
• Ocean Resources Management
• +۳ مورد دیگر

Helani Kottage is a Research Fellow at the Australian National Centre for Ocean Resources and Security (ANCORS), University of Wollongong, within the Faculty of Business and Law. She holds an Associate Research Fellow position since August 2020 and currently serves as a Research Fellow from January 2024. Additionally, she acts as a Statistical Consultant for The Pacific Community (SPC) since August 2020. Her work bridges statistical methodologies with food systems and ocean resource management, focusing on multilevel data analysis and sustainable development in the Pacific region. Research interests include integrating statistical techniques like missing data imputation with food security challenges, particularly in Timor-Leste and the Pacific. Her recent publications address categorical data analysis and value chain frameworks for improved food system outcomes. She contributes to interdisciplinary projects, such as the ACIAR-funded grant (2023–2026) enhancing food system resilience in the region. Funding: Leading in the ACIAR grant on integrated food system analysis. Advising/Grants: Collaborates on projects linking statistical methods to development challenges, though specific student advisees are not listed. Labs/Teams: ANCORS serves as her primary research hub, focusing on ocean governance and sustainable resource management.

Friedrich Götzمشاهده پروفایل

دانشیار

• Geographical Psychology
• Regional Personality Differences
• Big Data Analysis
• +۶ مورد دیگر

Friedrich Götz is an Associate Professor of Psychology in the Department of Psychology within the Faculty of Arts at the University of British Columbia. He holds a PhD (2021) and MPhil (2017) from the University of Cambridge and a BSc (2016) from the University of Konstanz. PhD, University of Cambridge (UK), 2021 MPhil, University of Cambridge (UK), 2017 BSc, University of Konstanz (Germany), 2016 Dr. Götz leads the Personality and Geographical Ambiance (PANGEA) Lab, focusing on geographical psychology and regional personality differences through interdisciplinary Big Data approaches. His research integrates social and personality psychology with behavioral science to examine real-world outcomes, including pandemic behavior, cultural shifts, and person-environment interactions. Additional interests span mobility/migration, wanderlust, courage, entrepreneurship, and experience sampling methods. He collaborates with TIME Magazine on large-scale surveys involving over 3 million participants. His publication trends reveal consistent contributions to top journals like Nature Human Behaviour and Journal of Personality and Social Psychology , with recent work emphasizing methodological rigor, geographical influences on behavior, and pandemic-related psychological responses. Key themes include spatial analysis techniques, personality-environment interactions, and the societal implications of psychological research. Rising Star Award (Association for Psychological Science), 2025 SAGE Emerging Scholar Award (Society for Personality and Social Psychology), 2025 Top 40 under 40 – Germany (CAPITAL Magazine), 2024 President’s New Researcher Award (Canadian Psychological Association), 2024 Best Dissertation Prize (German Psychological Society), 2021 Leading Scholar (Green College), 2021 Dr. Götz advises students through UBC's Psychology graduate programs and teaches undergraduate courses (PSYC 305A: Personality Psychology) and graduate courses (PSYC 528: Methods in Social Psychology and Personality; PSYC 569: Contemporary Conceptual Issues). His TIME Magazine collaboration represents a significant grant-adjacent initiative. The PANGEA Lab operates on principles of inclusivity and diversity, acknowledging its location on the unceded territory of the xʷməθkʷəy̓əm (Musqueam) people, and focuses on how humans and environments mutually shape each other.

Isabella Verdinelliمشاهده پروفایل

استاد

• Nonparametric Methods
• High-Dimensional Statistics
• Bayesian Experimental Design
• +۵ مورد دیگر

Isabella Verdinelli is a dual-affiliated professor serving as Professor in Residence at Carnegie Mellon University's Department of Statistics (Dietrich College of Humanities and Social Sciences) and as Full Professor at Sapienza University of Rome's Department of Statistical Sciences. She splits her academic year between Pittsburgh (fall) and Rome (spring), maintaining active research collaborations at both institutions. Her education includes a Master's degree from University College London and a PhD from Carnegie Mellon University. Her career spans postdoctoral work, assistant/associate positions, and professorship roles since her student days in Rome. Verdinelli's research focuses on: Nonparametric and high-dimensional methods for uncovering latent structures in complex datasets Bayesian experimental design with applications in medicine and engineering Manifold/filament estimation and minimax convergence theory Monte Carlo Markov Chains and hypothesis testing using Bayes factors Multiple testing procedures (FDR control) Her publications demonstrate sustained focus on Bayesian methodologies, nonparametric inference, and optimization techniques. Recent work (2007-2010) emphasizes high-dimensional data structures and theoretical statistics, while earlier contributions center on experimental design and Bayesian model selection.

• Dynamic Testing
• Complex Problem Solving
• Cognitive Flexibility
• +۳ مورد دیگر

Professor Jens Beckmann is a leading academic in Educational Psychology at Durham University's School of Education, where he has held the position since 2011. Prior roles include Director of the Accelerated Learning Laboratory at the University of New South Wales and research positions at Yale University, the University of Sydney, and institutions in Germany. He is a Fellow of the Wolfson Research Institute at Durham. His research focuses on three core areas: Dynamic Testing (assessing intellectual potential), Complex Problem Solving (knowledge acquisition in dynamic systems), and Cognitive Flexibility (measuring adaptability and novel problem-solving abilities). He has developed innovative assessment tools, such as the Adaptive Computer-Based Learning Test Battery (ACIL), and contributed to frameworks like the MicroDYN simulation for problem-solving analysis. Beckmann has authored/co-authored numerous books and articles, including Managerial Problem Solving: Frameworks, Tools & Techniques and Zur Validierung des Konstrukts des intellektuellen Veränderungspotentials . His work bridges educational theory and practice, emphasizing the application of dynamic assessment in real-world settings. He serves on editorial boards for journals like Frontiers in Psychology: Cognitive Science and Journal of Dynamic Decision Making . His supervision includes postgraduate students exploring topics like language learning aptitude, self-regulation in online education, and cross-cultural educational practices. Key contributions include pioneering methods to measure cognitive flexibility and challenging traditional intelligence-testing paradigms. Current work addresses the impact of global crises (e.g., pandemic school closures) on educational outcomes and language development.

John Moriartyمشاهده پروفایل

مدرس

• Workplace Wellbeing
• Mental Health
• Role Clarity
• +۵ مورد دیگر

John Moriarty is a Lecturer in the School of Social Sciences, Education and Social Work at Queen's University Belfast. His research focuses on workplace wellbeing, mental health, and the impact of social roles on individuals' wellbeing. He leads modules such as Digital Society and Advanced Quantitative Methods, emphasizing technology's societal influence and statistical analysis techniques. His work addresses burnout, role clarity, and interventions for mental health in occupational settings. Research Interests: Workplace wellbeing and role ambiguity Mental health in healthcare/social care professions Impact of aging on workforce participation Informal caregiver and volunteer wellbeing Use of linked administrative data for policy insights Notable Projects: Principal Investigator in Northern Ireland Longitudinal Study (NILS) projects analyzing health and social care workforce wellbeing during the pandemic Collaborative studies on pandemic effects across UK healthcare professions Recognition: 2021 European Social Work Research Association Award for Outstanding Publication Engagement: Advisory roles in workforce wellbeing initiatives Public lectures on pandemic-related worker challenges Contributions to policy discussions on caregiver roles

Christian Leuprechtمشاهده پروفایل

استاد

• Security and Defense
• Political Demography
• Comparative Federalism
• +۵ مورد دیگر

Christian Leuprecht is the Class of 1965 Professor in Leadership at Queen's University, cross-appointed between the Department of Political Studies and the School of Policy Studies. He holds additional roles as Eisenhower Fellow at the NATO Defence College and Adjunct Research Professor at Charles Sturt University and Flinders University. His research focuses on security, defense, political demography, and federalism, with recent work addressing transnational crime, cybersecurity, and intelligence accountability. Leuprecht has authored 12 books and numerous articles, including groundbreaking studies on NATO's Enhanced Forward Presence and RCMP governance reforms. He received the Cowan Prize for Excellence in Research and is a member of the Royal Society of Canada's College of New Scholars. Leuprecht earned a PhD from Queen's University (2003), MA/BA from the University of Toronto (1998-1999), and a D.É.A. from Université Pierre-Mendès France (1997). He has held visiting positions at Yale, Flinders University, and multiple European institutions. His leadership roles include serving on NSERC's governing council (2015-2018) and as past-president of the International Sociological Association’s Research Committee 01 on Armed Forces and Conflict Resolution. His current projects at the Comparative National Security and Defence Lab explore social network analysis for counterterrorism, data analytics in security policy, and border integrity strategies. Leuprecht frequently testifies before parliamentary committees and advises governments on defense, policing, and cybersecurity. He leads editorial boards for journals like Armed Forces & Society and contributes regularly to Canadian national media on security issues.

Rachel Baconمشاهده پروفایل

پژوهشگر ارشد

• Sociology
• Demography
• Religious Studies
• +۳ مورد دیگر

Rachel Bacon, Ph.D., is a Research Fellow at the Center for Mind and Culture, affiliated with Pennsylvania State University’s Social Science Research Institute (SSRI). Her work focuses on the intersection of religion, demography, and social structures, with particular emphasis on secularization processes, caregiving dynamics in rural communities, and quantitative modeling techniques. She holds a Ph.D. and utilizes mixed-methods approaches to address complex societal challenges. Her research interests include analyzing religious ecologies, the impact of education on religious decline, and the challenges faced by rural caregivers of individuals with Alzheimer’s disease. She has pioneered the use of microsimulation models to forecast population dynamics and evaluate policy impacts, contributing to both demographic science and public health strategies. Bacon has published extensively on topics such as Amish settlement demographics, Norwegian secularization through auto-biographical studies, and the cost-benefit analysis of population modeling approaches. Her work on caregiving often integrates community-level data with individual experiences, emphasizing multi-level analytical frameworks. Supported by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), her research bridges academic inquiry with practical applications in social policy and healthcare. She collaborates with institutions like the Population Research Institute (PRI) and has developed tools to assess rural caregiver needs, including validated survey instruments for diverse populations. Bacon’s contributions to demographic modeling are notable for addressing methodological gaps between cohort-component models and microsimulation techniques. Her interdisciplinary approach combines sociology, gerontology, and computational science to advance understanding of population trends and social structures.