جست‌وجوی استاد و پژوهشگر

Veysel Gümüşمشاهده پروفایل

دانشیار

• Turbulence modeling
• Computational Fluid Dynamics
• Hydrological and meteorological drought
• +۳ مورد دیگر

Dr. Veysel Gümüş is an Associate Professor at Harran University's Faculty of Engineering, Department of Civil Engineering, where he has been since 2014. His research focuses on turbulence modeling, computational fluid dynamics, hydrological drought analysis, and time-series trend analysis. Licence (2003), Master's (2006), and Doctorate (2014) in Civil Engineering from Harran and Çukurova Universities. His research interests span hydrological drought , computational fluid dynamics , climate trend analysis , and GIS applications in hydrology . His recent work emphasizes drought risk assessment, wind speed trends, and fluid flow simulations using AI techniques. Publications since 2023 highlight his expertise in Mann-Kendall tests , copula-based drought analysis , and CMIP6 climate projections across Turkey and Morocco. He has supervised over 15 graduate theses and served as an editor/hakem for 10+ journals, including ASCE and Theoretical and Applied Climatology.

Richard Segallمشاهده پروفایل

استاد

• Data Mining
• Text Mining
• Web Mining
• +۶ مورد دیگر

Dr. Richard Segall is a Professor in the Department of Information Systems and Business Analytics at Arkansas State University , affiliated with the Beck College of Sciences & Mathematics . He is also affiliated faculty in the Master of Engineering Management (MEM) Program , the Environmental Sciences Program , and serves on thesis committees at the University of Arkansas at Little Rock (UALR) . Education: Ph.D. in Operations Research, University of Massachusetts at Amherst (1984) M.S. in Operations Research and Statistics, Rensselaer Polytechnic Institute (1975) M.S. in Mathematics, Rensselaer Polytechnic Institute (1973) B.S. in Mathematics, Rensselaer Polytechnic Institute (1971) Dr. Segall's research spans data mining, text mining, web mining, big data analytics, bioinformatics, supercomputing applications, and mathematical modeling . His work bridges business analytics and computational biology , with a focus on transdisciplinary applications in agriculture, healthcare, and space systems. His recent publications emphasize genomic data analysis , plant disease diagnostics , AI-driven healthcare solutions , and space technology forecasting . The integration of machine learning , data visualization , and open-source tools is a recurring theme across domains. Scientific Awards & Grants: Three research awards from the National Research Council (NRC) Software grants from Oracle Corporation and SAS Institute, Inc. Dr. Segall has served on the editorial boards of the International Journal of Data Science , International Journal of Data Mining, Modelling and Management , and International Journal of Fog Computing . He previously contributed to the Arkansas Center for Plant-Powered Production (P3) and currently participates in the Center for No-Boundary Thinking (CNBT) .

• Power Electronics
• Building Automation
• Smart Grids
• +۷ مورد دیگر

Dr. Andrzej Ożadowicz is a University Professor at the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His office is located in room 510, building C-1, with contact details including phone +48 12 617 50 11 and email ozadow@agh.edu.pl. He holds PhD, DSc, and Engineering degrees, reflecting his dual expertise in academic research and practical engineering applications. His research spans Power Electronics, Building Automation, Smart Grids, and IoT-driven energy systems. Key interests include energy efficiency optimization through digital twins and BIM, distributed energy resource integration , and AI-enhanced demand management . Notably, he pioneers applications of deep reinforcement learning in home energy systems and develops frameworks for Smart Readiness Indicator implementation. His work bridges theoretical innovation with practical case studies in building thermal modeling and dynamic façade systems. Recent publications (2021-2025) reveal three dominant trends: (1) Convergence of digital twin technology with building automation for real-time energy management; (2) Critical analysis of IoT security and interoperability in smart infrastructure; (3) Pedagogical innovations in engineering education through blended learning methodologies post-COVID-19. His scholarly output demonstrates consistent focus on energy transition challenges and smart grid evolution. Professor Ożadowicz actively contributes to the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies at AGH. He is instrumental in the AutBudNet initiative —a network of certified laboratories for energy efficiency assessment that implements "learning by doing" principles in building automation education. His work with this consortium emphasizes practical validation of smart grid technologies and demand response systems.

Hao Yangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Transportation Safety
• Transportation Equity
• +۴ مورد دیگر

Hao Yang is an Assistant Professor in the Department of Civil and Systems Engineering at Johns Hopkins University, with dual affiliations at the Johns Hopkins Data Science and AI Institute and the Johns Hopkins Institute for Assured Autonomy. His research develops Trustworthy Machine Learning methods to enhance urban mobility systems, focusing on traffic safety, equity, and sustainability through ethical AI and human-machine cooperative systems. Yang earned dual bachelor's degrees in Electrical and Computer Engineering from Beijing University of Posts and Telecommunications and the University of London, followed by a Ph.D. in Civil Engineering (Transportation) from the University of Washington. His educational background bridges telecommunications, electrical engineering, and transportation systems. His research integrates spatio-temporal modeling, assured autonomous systems, and multimodal representation learning to address transportation equity and safety. Key projects include edge-AI-powered traffic surveillance, real-time crash identification, and cooperative signal assistance for vulnerable road users. His work emphasizes ethical AI deployment in cyber-physical infrastructure to create sustainable urban mobility solutions. Recent publications reveal a strategic shift toward large language models and multimodal AI for transportation challenges, with strong emphasis on explainability, reliability, and equity in traffic crash prediction, flow forecasting, and autonomous driving systems. This evolution demonstrates his commitment to adapting cutting-edge AI for real-world transportation problems. Yang's scientific contributions have earned significant recognition: Michael Kyte Outstanding Student of the Year Award (2022) High-Value Research Award from AASHTO (2022) Best Paper Award from TRB Information Systems Committee (2023) Best and Outstanding Dissertation Awards (2024) IEEE DTPI Outstanding Paper Award (2022) TRANSFOR22 Data Competition 2nd place (2022) ASCE Bridges Photo Contest First Place (2021) He actively mentors graduate researchers and seeks 2-3 PhD students for Fall 2025 to advance trustworthy AI in transportation. His research is supported by NSF, USDOT, and AASHTO grants including the Real-Time Truck Parking Information System project that received the High-Value Research Award. Current work focuses on edge-AI for traffic safety and multimodal data integration. Yang leads research within Johns Hopkins' Data Science and AI Institute and Institute for Assured Autonomy, collaborating with Transportation Research Board committees. His lab develops real-time perception systems using edge computing and representation learning, with active projects on non-motorized user safety and equitable traffic management for people with disabilities.

Panagiotis Papapetrouمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Time Series Analysis
• +۵ مورد دیگر

Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)

Christopher Rothمشاهده پروفایل

استاد

• Behavioral Economics
• Macroeconomic Expectations
• Beliefs and Attention
• +۳ مورد دیگر

Prof. Dr. Christopher Roth serves as a Professor of Economics and Management at the Faculty of Management, Economics and Social Sciences , University of Cologne (since 2021). He is affiliated with multiple prestigious institutions, including the ECONtribute Cluster of Excellence (since 2021), the Center for Social and Economic Behavior (C-SEB) (since 2021), and the Max Planck Institute for Collective Goods (Senior Research Fellow, since 2021). His previous roles include Assistant Professor at the University of Warwick (2019–2021) and postdoctoral positions at briq and CESifo. Education: DPhil in Economics (Edgeworth Prize, University of Oxford, 2014–2018), MPhil in Economics (with distinction, University of Oxford, 2012–2014), BSc in Psychology (University of Hagen, 2010–2013), BSc in Economics (First Class Honours, University of Warwick, 2009–2012) Roth’s research focuses on Behavioral Economics , Macroeconomic Expectations , and Beliefs & Attention . His work examines how subjective beliefs about public debt, racial discrimination, and macroeconomic trends influence household behavior and policy preferences. He uses experimental methods to study information dissemination, fact-checking demand, and political engagement dynamics. Recent publications address information frictions , political polarization , redistribution preferences , and macroeconomic perception . His work has appeared in top journals like the Quarterly Journal of Economics , Review of Economic Studies , and American Economic Review . Roth received the Edgeworth Prize for his PhD research. Awards & Affiliations : Edgeworth Prize (University of Oxford); Member of ECONtribute Cluster of Excellence, C-SEB, and Max Planck Institute Teaching : Offers courses on Experimental Methods (MSc, University of Cologne), Experimental Economics (MSc, Warwick), and macroeconomic beliefs (PhD, Copenhagen)

Lionel Truquetمشاهده پروفایل

مدرس

• Statistics for dependent data
• Time series analysis
• Markov chains
• +۲ مورد دیگر

Lionel Truquet is a Lecturer-Researcher in Statistics at ENSAI (École Nationale de la Statistique et de l'Administration Économique), where he focuses on Statistics for dependent data and Time series analysis . He serves as a Director of Research and has contributed significantly to fields like Markov chains and nonlinear dynamics . Research Interests: Time series models for ecological and economic data Statistical inference for categorical and discrete-valued processes Ergodic properties of Markov chains in random environments Mixing conditions for nonstationary processes Perturbation techniques in stochastic modeling Recent Publications: His work spans nearest neighbor sampling , multivariate autoregressive models , and mixing properties of count processes , with applications in ecology and econometrics. Key trends include nonparametric methods for high-dimensional data and stationarity analysis in time-varying systems. Scientific Awards: TJALLING C. KOOPMANS ECONOMETRIC THEORY PRIZE (2021–2023) for groundbreaking work on multivariate count autoregressions.

• Finance
• Corporate Governance
• Market Microstructure
• +۶ مورد دیگر

Prof. Dr. Erik Theissen is a full-time faculty member at the University of Mannheim, holding the Chair in Business Administration and Finance. His research focuses on market microstructure, corporate governance, and information-based trading in equity markets. University of Mannheim, Department of Business Administration Research areas: Finance, Market Microstructure, Corporate Governance His work compares auction and dealer markets, analyzes insider trading regulations, and evaluates the impact of trader anonymity on market liquidity. He has explored competition between exchanges (e.g., Euronext vs. Xetra) and the role of internalized trading under MiFID. His publications include Organizational Forms of Securities Trading (1998), with over 15 major peer-reviewed articles since 2001. Key journals include the Review of Financial Studies, European Financial Management, and Journal of Corporate Finance. 2001 Financial Innovation Award of Bethmann Bank 2001 Best Paper Award (Association of University Professors of Business Administration) 1998 Dissertation Award of the German Stock Institute His research spans experimental economics (e.g., market design, risk attitude estimation) and empirical analysis of German capital markets, including IPO pricing and mutual fund performance.

Ann Bostromمشاهده پروفایل

استاد

• Risk Perception
• Risk Communication
• Risk Management
• +۷ مورد دیگر

Ann Bostrom is the Weyerhaeuser Endowed Professor in Environmental Policy at the Evans School of Public Policy & Governance, University of Washington, where she joined the faculty in 2007 after serving as Associate Dean for Research and Professor at Georgia Tech's Ivan Allen College. She co-directed the NSF Decision Risk and Management Science Program and serves on the AAAS and Washington State Academy of Sciences boards. Her educational background includes: Ph.D. in Public Policy Analysis, Carnegie Mellon University M.B.A., Western Washington University B.A. in English, University of Washington Postdoctoral studies in Engineering and Public Policy, Carnegie Mellon University Postdoctoral studies in cognitive survey methodology, Bureau of Labor Statistics Bostrom's research centers on risk perception, communication, and management in environmental policy and uncertain decision contexts. She investigates causal misconceptions about climate change, earthquake risk awareness, and pandemic risk communication, bridging social/behavioral sciences with weather and climate risk management through efficacy-focused frameworks. Her 2017-2021 publications reveal concentrated work on climate change communication, natural hazards, and pandemic risks. Key themes include causal thinking's impact on policy support, risk message design efficacy, and cross-cultural risk perception comparisons, frequently contributing to National Academies reports on science communication and hazard management. Major scientific recognitions include: 2020 Distinguished Educator Award (Society for Risk Analysis) 1997 Chauncey Starr Award Elected fellow of AAAS, WSAS, and Society for Risk Analysis ASA/NSF/BLS Research Associateship (1991-92) Fulbright Fellowship (1989-90) Patricia Roberts Harris Fellowship (1988-89) She has secured major funding from NSF, EPA, and NIH, currently co-leading the Cascadia Coastlines and Peoples Hazards Research Hub and NSF AI Institute for Trustworthy AI in Weather/Climate. Advisory roles include National Renewable Energy Laboratory Decision Science Committee and Earthquake Hazards Reduction Advisory Committee. At UW, Bostrom co-chairs Environments and Populations research in the Center for Studies in Demography and Ecology, serves on EarthLab's steering committee, and participates in the Program on Climate Change Governing Board, while maintaining affiliations with Carnegie Mellon's Center for Climate and Energy Decision Making.

Junzhao Maمشاهده پروفایل

مدرس ارشد

• Technology Adoption
• E-commerce
• Real Estate
• +۵ مورد دیگر

Junzhao Ma is a Senior Lecturer in the Department of Marketing at Monash University. He holds a BA in Economics from Yale University and a PhD in Marketing from the Kellogg School of Management, Northwestern University. Previously, he worked as a marketing analyst at Capital One Financial Corporation and JP Morgan and Co. Education: BA Economics (Yale University), PhD Marketing (Kellogg School, Northwestern University) His research focuses on technology adoption, e-commerce, real estate, and media's social impact, employing novel methodologies and data sources. He has contributed to journals like Journal of Retailing , International Journal of Research in Marketing , and Journal of Business Ethics . His work aligns with UN Sustainable Development Goals related to reduced inequalities and responsible consumption. Recent research highlights include studies on service robot anthropomorphism (2023), sex robots acceptance (2022), and media-driven consumption trends (2020). He has received Dean's Letters for Teaching Excellence in 2020 and 2021. Scientific Awards: Dean's Letter for Teaching Excellence (2020, 2021) Junzhao actively engages in academic service, including peer reviews for Asia Pacific Journal of Marketing and Logistics and presentations at the INFORMS Marketing Science Conference and Australian & New Zealand Marketing Academy Conference. He has served as Chief Investigator in projects like "Bridging the Intention-Behaviour Gap in the Australian Tourism Industry" (2022-2024) and "eBabies: Forecast and Implications for Society" (2020-2021).

Alexandre Kohlhasمشاهده پروفایل

دانشیار

• Macroeconomics
• Monetary Policy
• Economic Uncertainty
• +۳ مورد دیگر

Alexandre Kohlhas is a University of Oxford Associate Professor in the Department of Economics and a William R Miller Fellow at St Edmund Hall . Previously an Assistant Professor at Stockholm University's Institute for International Economic Studies, his research bridges macroeconomics , monetary policy , and information economics with a focus on expectation formation and uncertainty. Doctorate from Pembroke College, University of Cambridge His work explores economic uncertainty and information asymmetry , analyzing how heterogeneous expectations and asymmetric attention shape macroeconomic outcomes. Recent publications examine data-driven macroeconomic modeling , wealth heterogeneity , and higher-order beliefs in monetary policy contexts. Key research trends include expectation formation in uncertain environments, monetary transmission mechanisms , and information aggregation in markets. His 14 most recent articles demonstrate consistent engagement with theoretical and applied macroeconomics through behavioral and informational lenses. William R Miller Fellow Tutorial Fellow in Economics Governing Body Fellow Reach Alexandre via email for academic collaboration or supervision inquiries.

Matteo Fasioloمشاهده پروفایل

مدرس ارشد

• Generalized Additive Models
• Electricity Demand Forecasting
• Covariance Matrix Modeling
• +۳ مورد دیگر

Dr. Matteo Fasiolo is a Senior Lecturer in the School of Mathematics at the University of Bristol, specializing in Statistical Science. His research focuses on advanced statistical modeling with significant applications in electricity demand forecasting and medical statistics, leveraging Generalized Additive Models (GAMs) as a core methodology. His primary research interests span: Generalized Additive Models and their extensions for complex data structures Covariance matrix modeling for high-dimensional energy forecasting Probabilistic forecasting techniques for uncertainty quantification Statistical machine learning including variational inference and contrastive learning Applications in electricity grid management and medical diagnostics Recent publications (2023-2025) reveal a dual focus: developing scalable statistical methods for electricity net-demand prediction in Great Britain using additive covariance models, and applying distributional regression to medical challenges like kidney function decline and cardiovascular risk prediction. His work on SoftCVI demonstrates innovation in variational inference, while extensions to GAMs address both mean modeling and full distributional forecasting. Dr. Fasiolo has supervised at least one student as indicated by university records. His research outputs include 16 publications and 2 publicly available datasets, reflecting active contributions to methodological statistics and domain-specific applications in energy systems.

Asha Weinstein Agrawalمشاهده پروفایل

استاد

• Transportation Planning and Policy
• Transportation Revenue
• Equity in Transportation
• +۴ مورد دیگر

Asha Weinstein Agrawal is a Professor at the School of Planning, Policy, and Environmental Studies within San Jose State University's College of Social Sciences. Her work centers on transportation planning and policy with a focus on sustainability and equity, actively engaging policymakers and communities to address contemporary mobility challenges through evidence-based solutions. Professor Agrawal's research spans transportation revenue systems, equity implications in mobility access, sustainable transportation frameworks, travel behavior analysis, survey methodology innovation, and historical transportation policy evolution. She investigates how planning tools can promote environmentally friendly travel and improve accessibility for disadvantaged populations, with current projects examining electric vehicle impacts on transportation funding, transit safety for vulnerable users, and community engagement in open streets initiatives. Analysis of her recent publications reveals dominant themes in transportation funding alternatives—particularly mileage-based user fees and zero-emission vehicle revenue impacts—and equity-focused studies on transit safety, workforce diversity, and accessibility for older adults and low-income communities. Her work consistently bridges academic research with real-world policy applications through rigorous survey methodologies and multi-stakeholder engagement. Scientific Awards: No specific awards are documented in the provided materials. Advising and Professional Engagement: Professor Agrawal regularly presents findings to federal and state decision-makers including U.S. Senate committees, the California Transportation Commission, and local transportation authorities. She serves on key advisory bodies such as the Metropolitan Transportation Commission's Regional Means-Based Transit Fare Pricing Study committee, Santa Clara County Traffic Safe Communities Network, and Valley Transportation Authority's Pedestrian Access Task Force. Her research has been supported through multiple policy-relevant projects with transportation agencies across California and nationally.

Dubravko Radicمشاهده پروفایل

استاد

• Service Management
• Price Management
• Applied Microeconometrics
• +۵ مورد دیگر

Dubravko Radic serves as Professor of Service Management at the University of Leipzig's Faculty of Business and Economics since 2009, while simultaneously holding the position of Deputy Head of the Price and Service Management group at the Fraunhofer Center for International Management and Knowledge Economics IMW since 2013. His academic career spans multiple institutions including the University of Wuppertal where he completed his habilitation, and the University of Frankfurt am Main where he earned his doctorate in statistics and econometrics. Doctorate (Dr. rer. pol. summa cum laude): Johann Wolfgang Goethe-Universität Frankfurt a.M. (2004) Habilitation: Bergische Universität Wuppertal (2009) Diplom-Volkswirt: Johann Wolfgang Goethe-Universität Frankfurt a.M. (1999) Research Stay: University of California Davis (2008) Professor Radic's research centers on the intersection of empirical methods and business management, with particular emphasis on service pricing modeling, applied microeconometrics, and social interactions in service contexts. His work bridges theoretical econometric approaches with practical business applications, especially in the healthcare sector where he has led multiple Fraunhofer IMW projects including ASARob, NurMut, and ATMoSPHÄRE. His research methodology combines quantitative modeling with real-world case studies to address strategic and operational decisions in service organizations. His recent publications demonstrate a consistent focus on discrete choice modeling, game theory applications in marketing, and service innovation frameworks. The 2025 paper "Discrete Games in Marketing Research" presented at the Global Marketing Conference in Hong Kong exemplifies his approach of applying advanced econometric techniques to practical marketing problems, particularly in digital service contexts. His work shows an evolving trajectory from foundational service management concepts toward increasingly sophisticated modeling of strategic interactions in service markets. Professor Radic has extensive experience advising major corporations including Metro AG, Lilly Deutschland, IMS Health, Berlin Chemie, and Augustinum gGmbH. His practical projects at Fraunhofer IMW focus on translating academic research into actionable business solutions, particularly in healthcare digitization and service innovation. He has led the TRAIN@MINE project developing training tools for Vietnam's mining sector and contributed to studies on Big Data applications in health insurance. At the University of Leipzig, he leads research activities through the Institute for Service and Relationship Management, supervising multiple research projects that connect academic inquiry with industry applications. His team collaborates with international partners including the University of California Davis, University of Maryland, Northwestern University, and the Technion Israel Institute of Technology, creating a robust research ecosystem focused on service management innovation.

Lakshmi Balasubramanyanمشاهده پروفایل

دانشیار

• Credit Risk Management
• Operational Risk Modeling
• Fintech
• +۴ مورد دیگر

Lakshmi Balasubramanyan is an Associate Professor in the Department of Banking & Finance at Case Western Reserve University's Weatherhead School of Management, joining in 2017. She holds a PhD and MS from Penn State University in quantitative banking analytics, alongside BA/MA degrees from the National University of Singapore. Specializes in AI integration in commercial banking Focuses on credit/operational risk modeling Expert in regulatory frameworks (Dodd-Frank Act) Active media commentator on financial trends Her research bridges traditional banking practices with emerging technologies, particularly through RegTech and FinTech innovations. Key contributions include analyzing bank balance sheet dynamics under liquidity regulations and developing entropy-based approaches to risk heterogeneity. Recent publications explore causal relationships between risk oversight and bank stability, syndicated loan market information asymmetry, and credit market feedback mechanisms. Current projects involve NSF-funded AI-enabled financial ecosystems. Recipient of two CSWEP Research Fellowships Multiple teaching award nominations (2020-2023) 2021 Weatherhead Intramural Grant recipient 2019 UCITE NORD Grant awardee Active in institutional service as Faculty Senate Committee member and Women in Finance advisor. Collaborates with Federal Reserve institutions on banking supervision research.