جست‌وجوی استاد و پژوهشگر

Roman Liesenfeldمشاهده پروفایل

استاد

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

Roman Liesenfeld is a Professor for Statistics and Econometrics at the University of Cologne since 2013, affiliated with the Faculty of Economics and Social Sciences and the Department of Economic and Social Statistics. Previously, he served as Professor of Statistics at the University of Kiel (2003-2013) where he was Dean of the Department of Business, Economic and Social Science (2011-2012), and held positions at the University of Pittsburgh and University of Tübingen. His educational background includes a Doctoral degree (Dr. rer. pol.) from the University of Tübingen (1998) following research assistant work there (1993-1998), and a Diploma (Diplom-Volkswirt) from the University of Mannheim (1993). He completed his Habilitation in statistics and econometrics at the University of Tübingen in 2002. Liesenfeld's research focuses on econometrics and statistical methods with applications in financial markets. His work spans time series analysis, volatility modeling, Bayesian statistics, and computational statistics. He has made significant contributions to understanding stock market volatility, portfolio optimization, and state-space representations in econometric models, addressing methodological challenges while maintaining connections to practical applications in finance and economics. His research publications demonstrate a consistent focus on innovative statistical methods for complex economic problems, particularly in volatility modeling and Bayesian computation, appearing in top-tier journals including the Journal of Econometrics, Journal of Business & Economic Statistics, and The Review of Economic Studies. Professor Liesenfeld is a member of the German Economic Association and the German Statistical Society. Since 2013, he has served as an Associate Editor of Empirical Economics. He has maintained international research collaborations through visiting positions at the Universidade Federal de Santa Catarina in Brazil (2018, 2023) and the University of Pittsburgh in the United States (2007, 2015, 2000), reflecting the global impact of his work.

Andreas Boeckerمشاهده پروفایل

دانشیار

• Consumer Response to Food-borne Risks
• Food Marketing
• Traceability in Agricultural Supply Chains
• +۳ مورد دیگر

Andreas Boecker is an Associate Professor and Chair of the Department of Food, Agricultural and Resource Economics at the University of Guelph's Ontario Agricultural College. He holds a PhD from Kiel University (Germany) and has held academic roles in Germany before joining Canada in 2005. His research focuses on three core areas: consumer perception of novel agricultural technologies, traceability systems in food supply chains, and communication strategies for emerging technologies like biotechnology. Methodologically, he employs survey research and case studies, often involving undergraduate students in projects such as analyzing media coverage of GMO foods. As Undergraduate Coordinator, he oversees outreach to prospective students and academic advising. His work bridges theoretical research and practical industry challenges, addressing topics like functional foods, risk communication, and policy impacts on agricultural businesses. Publications span journals like Journal of Risk Research and Food Control , with a focus on empirical studies of consumer behavior, agricultural innovation, and supply chain dynamics. His research highlights the interplay between technology adoption, policy frameworks, and market responses to food safety concerns. Notable contributions include analyzing GMO risk perception on social media, evaluating traceability costs for fisheries, and modeling consumer preferences for certified animal-friendly products.

• Numerical Analysis
• Computational Mathematics
• Partial Differential Equations
• +۷ مورد دیگر

Nicola Ferro is a Researcher in the Department of Molecular Sciences and Nanosystems at Ca' Foscari University of Venice, specializing in numerical analysis and computational mathematics. He actively contributes to teaching and research, with a strong focus on numerical methods for PDEs, optimization, and mesh adaptation. His research interests lie at the intersection of applied mathematics and engineering, particularly in numerical methods for partial differential equations , topology optimization , mesh adaptation , and their applications in biomedical engineering , solid mechanics , and sustainable technologies . His work bridges theoretical developments with real-world applications in medical devices and environmental monitoring. The recent publications highlight a consistent trend in computational modeling, particularly in developing advanced numerical techniques for biomedical applications (e.g., vascular stents) and data-efficient simulation (e.g., mesh adaptation and data compression). His research integrates high-performance computing with multiphysics modeling to solve complex engineering challenges. Editor’s Choice (2024) for a paper in Mathematical and Computational Applications PhD Olympiad Winner (2021) – ECCOMAS Congress Research Scholarship (2021) – Istituto Nazionale di Alta Matematica (INdAM) Research Scholarship (2020) – Fondazione Fratelli Confalonieri Premio Cercignani (2016) – Best Master's Thesis in Computational Science and Engineering, Politecnico di Milano Nicola Ferro has secured multiple research grants, including as Principal Investigator in GNCS INdAM projects (2023, 2025) and the Finanziamento Giovani Ricercatori (2019). He is involved in national projects such as PRIN P2022JLNPJ (RESET) and PRIN 20204LN5N5, and collaborates with industry partners like Thales Alenia Space Italia. He mentors students and contributes to academic service as a guest editor and reviewer for top journals. He is part of a vibrant research group focused on computational mathematics and numerical methods, collaborating closely with researchers such as Simona Perotto, Umberto Morbiducci, and Claudio Chiastra. His work is embedded in interdisciplinary teams tackling challenges in biomedical engineering and sustainable technology development.

• Economics
• Labor Economics
• Education Policy
• +۴ مورد دیگر

Tyler Ransom is an Assistant Professor of Economics at the University of Oklahoma and a Research Affiliate at the Institute for the Study of Labor (IZA) . He focuses on economics, education policy, labor markets, and migration studies. Institutional Affiliations: University of Oklahoma, IZA, Duke University, London School of Economics & Political Science (LSE), Federal Reserve Bank of New York His research explores college attrition , wage returns to schooling , geographic labor mobility , and Covid-19 impacts on education . He has published extensively on topics like admissions preferences , STEM education , and economic policy . His recent work on vegetable seed oils and obesity (2024) highlights intersections of public policy, nutritional biochemistry, and economic behavior. Over 15 years, his publications span labor economics, educational dynamics, and migration economics.

Felix Eggersمشاهده پروفایل

استاد

• Digitalization
• Generative AI
• Corporate Digital Responsibility
• +۸ مورد دیگر

Felix Eggers is a Professor of Marketing at Copenhagen Business School (since 2021), leading research in digitalization, AI, and quantitative methods. He previously held roles at the University of Groningen and was a visiting scholar at institutions like MIT Sloan and the University of New South Wales. His work bridges academic rigor with practical consulting experience. Education: PhD in Marketing from the University of Hamburg. Teaching qualifications include the University Teaching Qualification (BKO) from Groningen. Research focuses on digital business models, Generative AI, Corporate Digital Responsibility, pricing, and branding. Methodologically, he specializes in conjoint analysis and discrete choice experiments. Collaborations include the Measuring the Digital Economy initiative and GDP-B development. Publications appear in top journals like Marketing Science and Journal of Marketing . Recent work explores privacy calculus (PRICAL index), cultural differences in data sharing, and AI adoption dynamics. Supervises Master’s theses with a quantitative focus. Engages in external projects like co-supervising PhD students and advising Kwantum Analytics. Active in developing my.preferencelab.com for preference measurement tools. Contributions span academic conferences (e.g., Quantitative Marketing Research Conference) and industry partnerships, emphasizing applied research in digital transformation and consumer behavior.

Piotr Dniestrzańskiمشاهده پروفایل

استاد

• Political Science
• European Union Studies
• Mathematical Economics
• +۳ مورد دیگر

Dr. hab. Piotr Dniestrzański, professor at Wrocław University of Economics, specializes in mathematical and political science approaches to fair division problems, particularly in the context of degressively proportional allocation systems. He holds an academic position in the Department of Mathematics and Cybernetics. His research focuses on optimizing seat distributions in institutions like the European Parliament, addressing paradoxes in proportional representation, and applying mathematical models to political and economic challenges. Key research areas include: Apportionment methods and divisor-based allocation systems EU parliamentary configuration dynamics Optimization theory for fair resource distribution Statistical measures of inequality and disproportionality Recent work analyzes Brexit's impact on European Parliament structure, critiques the Cambridge Compromise framework, and explores entropy-based allocation strategies. His methodologies bridge mathematical rigor with practical governance applications. Consultation hours in 2024/2025: Thursdays 12:45-13:15 via Microsoft Teams (code rs9b0dy).

Wietse van de Lagewegمشاهده پروفایل

پژوهشگر

• Coastal Systems
• Fluvial Morphodynamics
• Estuarine Dynamics
• +۳ مورد دیگر

Wietse van de Lageweg is a researcher at HZ University of Applied Sciences, specializing in fluvial, estuarine, and coastal systems. His expertise includes sediment dynamics, numerical modeling, and field observations to predict environmental impacts on society. He holds a PhD from Utrecht University (2013), with postdoctoral research at the University of Hull, UK, focusing on climate change adaptation in coastal systems. Prior roles include a coastal morphology expert at AnteaGroup Belgium (2018), where he applied UNIBEST-CL+ models for shoreline change simulations. His research integrates biophysical processes and human dimensions, addressing challenges like flood protection through projects such as C-SCAPE and 'No Sea Too High.' Education: PhD in Earth Sciences, Utrecht University, 2013 Postdoctoral Research, University of Hull, UK (Climate Change & Coastal Systems) Research Interests: His work spans sediment transport modeling, managed realignment, sand nourishment efficacy, and ecosystem service valuation. Key areas include tidal bar sedimentology, biofilm effects on substrate stability, and the socio-technical feasibility of nature-based solutions. He employs tools like Delft3D and UNIBEST-CL+ to simulate morphodynamic processes in dynamic coastal environments. Projects: C-SCAPE : Optimizing sand nourishments for multifunctional coastal resilience No Sea Too High : Spatial strategies for water safety beyond traditional dikes Underwater Laboratory : Experimental studies at NIOZ Yerseke Awards & Grants: Though no specific awards are listed, his involvement in EU Hydralab+ highlights collaborative research excellence. His work has informed policy through projects like Perkpolder managed realignment and Belgian coastal nourishment strategies. Labs & Collaborations: Associated with HZ's Water research spearhead and Joint Research Center Zeeland. Engages in interdisciplinary teams addressing climate adaptation and ecosystem dynamics.

• Transportation Systems
• Discrete Choice Modeling
• Causal Inference
• +۴ مورد دیگر

Prateek Bansal serves as an Academic Visitor and postdoctoral research associate at the Transport Strategy Centre (TSC) within the Centre for Transport Studies (CTS) at Imperial College London's Department of Civil and Environmental Engineering. He has been affiliated with Professor Dan Graham's research group since August 2019, contributing to transportation systems analysis through advanced statistical methodologies. Education: PhD in Transportation from Cornell University MS in Transportation Engineering from University of Texas at Austin B.Tech in Civil Engineering from Indian Institute of Technology (IIT) Delhi His research focuses on advancing discrete choice modeling with applications in transportation behavior. Key innovations include variational Bayes for fast inference, causal frameworks for transit systems with structural correlations, and entropy-based solutions for endogeneity. His doctoral work pioneered semi-parametric heterogeneity modeling, t-distributed error kernels, minorization-maximization algorithms, and quadrature methods for multi-dimensional integrals in choice experiments. Analysis of his 15 most recent publications (2019-2022) reveals a strong emphasis on Indian transportation contexts, including electric vehicle adoption, two-wheeler markets, and vaccine hesitancy. Methodologically, he integrates spatial statistics, Bayesian computation, and causal inference to address metro system vulnerability, crowd dynamics, and traffic flow relationships. His work consistently bridges econometric theory with real-world transit data from London, Hong Kong, and Indian cities. As part of the Centre for Transport Studies, Bansal collaborates within Imperial's Transport Strategy Centre on projects involving large-scale transit data analysis. His research outputs appear in leading journals including Transportation Research Part B, Journal of the Royal Statistical Society, and Transportation.

Hannah Barkerمشاهده پروفایل

پژوهشگر ارشد

• Health Workforce and Systems
• Health and Wellbeing
• Behavior Change
• +۳ مورد دیگر

Dr. Hannah Barker is a Research Fellow at the University of Southampton's School of Health Sciences, affiliated with the Faculty of Environmental and Life Sciences. Her work focuses on improving healthcare workforce systems, nurse shift patterns, and behavior change interventions related to wellbeing and sustainability. She employs mixed-methods approaches, combining qualitative and quantitative data. Current research includes discrete choice experiments to optimize nursing shift designs and studies on household food waste reduction. Barker has contributed to policy research on safe staffing in NHS trusts and compassionate care programs for older patients. She is part of the Health Work & Systems Research Group, leveraging their expertise in analyzing routinely collected healthcare data. Her interdisciplinary background spans health sciences and geography, with publications in journals like Sustainability and Journal of Clinical Nursing . Research Interests: Health workforce dynamics, patient-centered care, sustainable food systems, and behavior change strategies. Recent work includes validating tools for long-term condition management and evaluating nudge techniques to reduce food waste. Her articles explore topics ranging from nurse workload analysis to environmental sustainability, reflecting a focus on both healthcare operational efficiency and broader societal challenges. Collaborations with groups like the CLECC programme highlight her commitment to translational research improving patient-staff interactions and systemic healthcare policies.

Joanne Turnbullمشاهده پروفایل

دانشیار

• Ethnography
• Mixed Methods
• Qualitative Methods
• +۷ مورد دیگر

Joanne Turnbull is an Associate Professor at the University of Southampton's School of Health Sciences, specializing in ethnography, mixed methods, and qualitative research. She serves as Doctoral Programmes Director and focuses on urgent/emergency care systems, patient access to healthcare, and nursing workforce dynamics. Avenue Campus Highfield Campus Her research investigates: Service user experiences (geographical/telephone access, help-seeking behaviors) Organization and delivery of urgent/emergency care Technology implementation in healthcare (e.g., computer decision support systems) Nurse recruitment and retention strategies Recent publications highlight her work on: TAT feeding practices in neonatal care eHealth literacy and urgent care access NHS nurse retention factors Paramedic end-of-life care delivery She leads the MRes Qualitative Research Design and Methods module and has secured NIHR Health Services & Delivery Programme funding for studies on NHS 111 services, trans-anastomotic feeding, and nurse retention.

Zoé Ejebuمشاهده پروفایل

عضو هیئت علمی

• Applied Economics
• Nursing
• Health Workforce Retention
• +۳ مورد دیگر

Zoé Ejebu is a Senior Research Fellow at the University of Southampton, affiliated with the Health Workforce and Systems research group. She joined the university in 2020 and focuses on applied economics methods to study nurse retention, workforce performance, and healthcare resource allocation. Her work emphasizes analyzing large datasets and conducting discrete choice experiments to understand job preferences. Education: PGCAP (2024), University of Southampton FHEA (2023), Higher Education Academy PhD in Economics (2010–2014), University of Aberdeen MSc in Financial Economics (2009–2010), University of Glasgow MA in Economics (2008–2009), University of Aberdeen Licence Économique, Monnaie et Finance (2007–2008), Université Paris II, France Research Interests: Zoé’s work centers on applied economics in healthcare, including nurse retention strategies, workforce performance metrics, and the impact of working conditions. She explores topics such as shift patterns, burnout prevention, and cost-effectiveness of nurse staffing. Her recent studies address NHS nurse retention through discrete choice experiments and policy analysis. Articles Trends: Her publications focus on nurse staffing, shift work impacts, and healthcare workforce dynamics. Recent work highlights cost-benefit analysis of nurse deployment, frailty in adult populations, and frameworks for evidence-based staffing decisions. Awards: Dean’s List Award (2024) Dean’s List Award (2024) Teaching & Grants: She teaches 'Developing Research Skills: Practice-Based Learning' and 'Applied Quantitative Research Methods.' She leads the Evaluation of the N50k Programme and collaborates on projects like understanding NHS nurse retention factors. She accepts PhD students and has no listed grant details. Labs/Teams: Active in the Health Workforce and Systems research group, contributing to interdisciplinary projects on healthcare labor economics and policy.

• Operations Research
• Operations Management
• Dynamic Resource Allocation
• +۷ مورد دیگر

Yehua Wei is an Associate Professor in the Decision Sciences area at Duke University's Fuqua School of Business. He holds a Ph.D. in Operations Research from MIT and an undergraduate degree in Combinatorics and Optimization from the University of Waterloo. His research focuses on complex decision-making under uncertainty, including dynamic resource allocation, process flexibility, vehicle routing, and queueing networks. He has been recognized with awards such as the George Nicholson Paper Competition and the Daniel H. Wagner Prize. His teaching spans business analytics and operations research courses at both master's and doctoral levels, earning him the 2023 MQM Teaching Award for Innovation and Excellence. Education: Ph.D. in Operations Research Center (ORC), MIT Bachelor's in Combinatorics and Optimization and Pure Math, University of Waterloo Research emphasizes developing methodologies for managing uncertainties through convex optimization, stochastic networks, and game theory. Notable contributions include work on fulfillment flexibility in e-commerce, vehicle routing with stochastic demand, and strategic service network design. Articles frequently explore intersections of operations research with real-world applications like supply chain resilience and inventory systems. Awards include the 2023 TSL Intelligent Transportation Systems SIG Paper Award and the 2019 MSOM Service Management SIG Best Paper Prize. He has advised on multiple doctoral and master's theses, though specific advisee names are not listed. His work addresses challenges in logistics, manufacturing, and service industries, often employing advanced analytical frameworks to enhance system efficiency and robustness.

Debopam Bhattacharyaمشاهده پروفایل

استاد

• Empirical Microeconomics
• Micro-econometrics
• Welfare Analysis
• +۳ مورد دیگر

Professor Debopam Bhattacharya is a Professor of Econometrics at the University of Cambridge's Faculty of Economics. His research focuses on empirical microeconomics, micro-econometrics, and welfare analysis, with particular attention to discrete choice models and institutional analyses such as university admissions. He has held significant grants, including the European Research Council (ERC) Grant (2016-2021) and an Economic and Social Research Council (ESRC) Grant (2022-2026). Education: Background in economics and econometrics (details not explicitly provided). His research interests span welfare economics, program evaluation, and academic fairness in university admissions. He has supervised PhD student Shu Feng Wei and contributes to the development of empirical methodologies in econometrics. His work frequently intersects with policy analysis, particularly in education and social welfare. Key research themes include the empirical content of binary choice models, demand analysis under social interactions, and nonparametric welfare analysis. Notable contributions include studies on Cambridge University admissions and the academic fairness of elite institutions. Awards/Grants: ERC Grant (2016-2021), ESRC Grant (2022-2026).

Laurence Alesمشاهده پروفایل

دانشیار

• Macroeconomics
• Economic Policy
• Technology and Labor Markets
• +۷ مورد دیگر

Laurence Ales is an Associate Professor of Economics at the Tepper School of Business, Carnegie Mellon University, where he has been teaching since 2008. He holds a PhD in Economics from the University of Minnesota and an undergraduate degree in Physics from the University of Rome, Tor Vergata. He teaches courses in macroeconomics, including 'Emerging Markets' for undergraduates and 'Global Economics' for MBAs, and is recognized for his innovative teaching methods, such as using Twitter to engage students with real-time economic news. University: Carnegie Mellon University School: Tepper School of Business Department: Economics Academic Rank: Associate Professor Since: 2008 His research focuses on macroeconomic policy, technological change, labor markets, innovation, and taxation. He has published in top journals including The American Economic Review , with recent work on generative AI, automation, innovation tournaments, and optimal taxation. His interdisciplinary approach integrates modeling with data analytics, reflecting his physics background. His recent publications (2021–2024) highlight a strong focus on how technological change—particularly automation and AI—affects labor demand, task structure, and income distribution. He also investigates innovation mechanisms such as crowdsourcing and tournaments, as well as optimal tax policies in the presence of discrete choices and income-generating behavior. University-wide Teaching Award, Carnegie Mellon University Ales advises on policy responses to regional economic shocks and the evolution of manufacturing. He values student engagement and has been praised for transforming macroeconomics education. He emphasizes excitement in learning as a key to academic success and is known for his dynamic classroom presence. He collaborates across campus to study manufacturing trends and their policy implications, advocating for tighter integration between business and other academic disciplines. He leads no named lab or team in the text but partners with other campus units on research. His future goals include maintaining his passion for research and teaching over the next decade.

Tomasz Radzikمشاهده پروفایل

استاد

• Algorithm design
• Network optimization
• Wireless communication algorithms
• +۵ مورد دیگر

Professor Tomasz Radzik is a Professor of Computer Science at King's College London's Department of Informatics, within the Faculty of Natural, Mathematical & Engineering Sciences. His research focuses on algorithm design, network optimization, wireless communication algorithms, and data structures. He holds a PhD from Stanford University and an MSc from the University of Warsaw. Education: Doctor of Philosophy, Algorithms for Some Linear and Fractional Combinatorial Optimization Problems, Stanford University (1992) Master of Science, Communication and Routing in Synchronous Parallel Machines, University of Warsaw (1985) Research Interests: Radzik's work spans algorithm design for network protocols, distributed systems, and wireless communication. He explores practical implementations of algorithms and their experimental evaluation. His current projects include the Finance Hub (FinTech), Machine Learning, and Algorithms and Data Analysis groups. Grants & Projects: Concept drift in distributed IIoT networks (Toshiba Research Europe, 2021–2025) Randomized Algorithms for Computer Networks (EPSRC, 2014–2017) Expander and Random Walks research (EPSRC, 2011–2014) Collaborations & Labs: Radzik leads King's College's Algorithms and Data Analysis group. His work intersects with the Finance Hub and Machine Learning initiatives, focusing on FinTech and distributed computing challenges.