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Christine EckertView profile

Professor

• Marketing Analytics
• Quantitative Modeling
• Consumer Financial Decisions
• +4 more

Christine Eckert is a Professor of Marketing Analytics at the TUM School of Management (Technische Universität München). She holds a doctorate in economics from Goethe University Frankfurt am Main and has previously held academic positions at University of Technology Sydney and EBS University of Business and Law. Education: Mathematics (Johannes Gutenberg University Mainz, Christian-Albrechts University Kiel); Economics (Goethe University Frankfurt am Main) Her research focuses on quantitative modeling of market participants' decisions, spanning consumer financial behavior, strategic innovation decisions, and corporate social responsibility. She also explores methodological advancements in management research, particularly causal inference techniques. Notable contributions include serving as co-editor for Big Data and Business Analytics (Journal of Business Research) and receiving an Australian Research Council Discovery Grant (2019-2021). Her work has been recognized with the Center for Financial Planning's Best Paper Award (2021). Key journals: Journal of the Academy of Marketing Science, Journal of Management, Journal of Marketing Research She contributes to academic governance through roles like Panel Member for New Zealand's Performance Based Research Fund (2018) and advisory board membership with Super Consumers Australia (since 2022).

Vasant DharView profile

Professor

• Artificial Intelligence
• Data Science
• Machine Learning
• +5 more

Vasant Dhar is the Robert A Miller Professor of Business and Professor of Data Science at the Leonard N. Stern School of Business at New York University. He serves as Director of Industry Relations and specializes in Technology, Operations, and Statistics. Joining Stern in 1983, Professor Dhar has established himself as a leading expert in artificial intelligence, data science, and financial technology. Professor Dhar's educational background includes: Ph.D. in Artificial Intelligence from the University of Pittsburgh (1984) M.Phil. from the University of Pittsburgh (1982) B.Tech. in Chemical Engineering from the Indian Institute of Technology, Delhi (1978) His research focuses on how risk influences our trust in AI systems, demonstrating the existence of an "automation frontier" that expresses a tradeoff between how often machines will be wrong and the consequences of their errors. Professor Dhar examines how innovations such as Artificial Intelligence impact our lives, and how we can create technology and policy for a better future in a world of increasingly intelligent machines. His work spans financial applications of AI, where he was among the first to bring machine learning to Wall Street in the 1990s, founding the machine-learning-based hedge fund SCT Capital Management. Professor Dhar's recent publications reveal a strong focus on the practical applications and societal implications of AI. His work addresses critical issues including AI reliability in financial document analysis, the governance of AI companies, ethical considerations in biometric payments, and the evolving relationship between humans and increasingly intelligent machines. His research demonstrates how AI is transforming various sectors while raising important questions about trust, accountability, and the future of work. Among his notable recognitions is the Robert A Miller Professorship, an endowed chair position at NYU Stern. His research has been funded by grants from industry and government agencies such as the National Science Foundation. Professor Dhar teaches courses on Systematic Investing, Data Science, Prediction, and Tech Innovation. He has written over 100 research articles and is the host of the "Brave New World" podcast, which explores how technology and virtualization in the post-COVID era is transforming humanity. He publishes fortnightly at vasantdhar.substack.com and is a frequent speaker in academic and industrial forums.

• Digital Marketing
• Human-Computer Interaction
• Behavioral Marketing
• +5 more

Dr. Yu-Ting Lin is a Senior Lecturer and Postgraduate Research Coordinator at the School of Marketing, The University of New South Wales (UNSW) . With a PhD in Marketing from Imperial College London , an MS in Management Information Systems from National Chengchi University , and a BBA in Management Information Systems from National Chiayi University , she bridges human-computer interaction and digital marketing through innovative research. Education: BBA, National Chiayi University MS, National Chengchi University PhD, Imperial College London Her research focuses on the intersection of digital technology and consumer behavior , particularly in emotional ad design , immersive media , and real-time marketing . She also explores mHealth applications for behavioral change. Dr. Lin’s work spans Journal of Marketing , Journal of Service Research , and other high-impact venues. Her recent Google Scholar publications highlight themes in branding psychology , digital interventions , and user experience analytics . Scientific Awards: 2024 ANZMAC Best Paper in Track Artificial Intelligence and Innovation 2024 Research Impact Award, UNSW Business School 2024 Research Supervisor Award, UNSW 2022 Dean's Research Fellowship, UNSW Business School 2021 Research Excellence Award – Early Career Researcher, UNSW Business School 2021 AMA TechSIG Lazaridis Prize for Best Paper on Marketing Innovation 2020 Finalist MSI Paul Root Award 2019 Technologies Incubation Scholarship, MOE (Taiwan) 2018 Case Centre Fellowship, Imperial College Business School 2017 Tutorial Fellowship, Imperial College Business School Dr. Lin’s grants include over AUD 400,000 in funding from ARC Discovery Projects , Australian Marketing Institute , and Taiwanese Overseas Pioneers Grant . She contributes to the Media Engagement and Analytics Lab (MEAL) at UNSW Business School.

• Digital Marketing
• Consumer Behavior
• Brand Strategy
• +5 more

Dr Denitsa Dineva is a Senior Lecturer in Marketing and Strategy at Cardiff Business School , specializing in digital marketing , consumer behavior , and brand strategy . With a PhD in Digital Marketing from Aberystwyth University, she brings both academic expertise and practical experience from commercial and non-profit sector marketing roles. Her research focuses on the complexities of digital and social media , particularly examining uncivil consumer interactions , brand content moderation , and digital brand engagement . Denitsa employs mixed methods , social media text analysis , and experimental research to understand brand-consumer dynamics in digital spaces. 2025: Brand-to-brand social media engagement analysis 2025: Communication accommodation in brand communities 2025: Schadenfreude in service recovery 2024: Brand engagement typology 2023: Platform moderation strategies 2023: Brand advertising withdrawal cases She has received multiple accolades including the IAA Impact Award (2025) and SIM Conference Best Paper (2024), while also securing £133,878 in research funding across projects on digital marketing and public value initiatives. Denitsa teaches Digital Marketing modules at BSc, MSc, and executive education levels, and currently supervises PhD research related to online brand communities , social media content moderation , and consumer engagement dynamics . She serves as Senior Personal Tutor and External Examiner at multiple universities.

• Machine Learning
• Deep Learning
• Graph Analysis
• +6 more

Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.

• Differential Privacy
• Machine Learning
• Privacy-Preserving Data Analysis
• +3 more

Daniel Kifer is a Professor in the Computer Science and Engineering department at Pennsylvania State University, with affiliations to the Huck Institutes of the Life Sciences. His work bridges computer science, privacy-preserving machine learning, and geoscience applications. With over 10,000 citations and a high h-index, he focuses on methods to unify theoretical and applied research. Research Interests: Differential Privacy, Privacy-Preserving Machine Learning, Physics-Informed Neural Networks, Landslide Prediction, and Formal Verification of Privacy Systems. Recent projects include grants from the National Science Foundation: SaTC: CORE: Small (2024): privacy-preserving user data embedding in machine learning pipelines. SaTC: CORE: Medium (2017-2023): formal methods for differential privacy and accuracy optimization. His research outputs span domains like geoscience, database systems, and policy analysis, emphasizing precision and scalability of privacy-preserving algorithms.

Michael D. SmithView profile

Professor

• Information Systems
• Digital Economics
• Consumer Behavior in Online Markets
• +4 more

Michael D. Smith is a Professor of Information Technology and Public Policy at Carnegie Mellon University, with joint appointments at Heinz College and Tepper School of Business. His research employs economic and statistical methods to analyze digital markets, focusing on firm and consumer behavior in online environments. Education: B.Sc. in Electrical Engineering (Summa Cum Laude), University of Maryland M.Sc. in Telecommunications Science, University of Maryland Ph.D. in Management Science and Information Technology, MIT Research Interests: Professor Smith investigates the economics of digital information markets, consumer behavior in online platforms, and policy implications of technological disruption. His work spans copyright enforcement, digital advertising, and the impact of piracy on legal media consumption. Publications: His recent studies examine AI’s role in copyright policy, effectiveness of anti-piracy measures, and market dynamics in digital streaming. Articles often bridge economics, computer science, and public policy. Awards: National Science Foundation CAREER Award Multiple Best Teacher Awards at CMU Recognized as a Top 100 Emerging Engineering Leader (NAE, 2020) Best Paper Runner-Up (Information Systems Research, 2006) Editorial and Industry Roles: Served as Senior Editor at Information Systems Research and Associate Editor at Management Science . Prior to academia, he worked in telecommunications at GTE and Booz Allen Hamilton, earning a patent for AI applications in network design. Contact: mds@cmu.edu | Office: 4800 Forbes Avenue, Hamburg Hall 2204, Pittsburgh PA 15213

Michel ClementView profile

Professor

• Marketing & Media Management
• Digital Technologies in Media
• Customer/Donor Behavior Analysis
• +5 more

Prof. Michel Clement is a Professor of Marketing & Media at the University of Hamburg Business School, holding the Chair for Marketing & Media since 2006. He previously held academic positions at the University of Passau (2005/2006) and Christian-Albrechts-University Kiel (2002–2005). His research focuses on entertainment media product management, new technologies, and donor/customer management. He has held significant administrative roles including Academic Senate Member (2013–present), Faculty Council Member (2014–present), and Director of the Research Center Media and Communication (2008–present). Education: PhD in Marketing from Christian-Albrechts-University Kiel (mentor: Prof. Sönke Albers), with a Master's in Business Administration focusing on Marketing, Innovation Management, and Psychology. Pre-academic career included management roles at Bertelsmann mediaSystems and Bertelsmann eCommerce Group, where he founded Snoopstar.com GmbH as Vice President. Research interests span digital media economics, prosocial behavior in healthcare donations, platform business models, and consumer decision-making in entertainment industries. He has contributed to understanding blood/plasma donation retention strategies, smart speaker impacts on media consumption, and pandemic-related behavioral changes. Leadership roles include supervisory board memberships at MADSACK Mediengruppe (2018–present), Studierendenwerk Hamburg (2017–present), and Universität Hamburg Marketing GmbH (2015–present). He has directed major initiatives like the Hamburg Graduate School for Media and Communication (2009–2016) and co-developed international MBA programs with Fudan University (2006–2008). Grants and collaborations include state-funded excellence initiatives and industry partnerships. His work integrates academic research with practical applications in media technology scouting, venture consulting, and digital platform governance.

Philipp AfecheView profile

Professor

• Operations Management
• Revenue Management
• Supply Chain Management
• +5 more

Philipp Afeche is a Professor of Operations Management and Statistics at the Rotman School of Management, University of Toronto. His research bridges operations and marketing/economics, focusing on revenue management, pricing strategies, and service design in congestion-prone systems like healthcare and transportation. He holds a BA from the University of St. Gallen and MS/PhD degrees from Stanford University. Afeche has been recognized with the 2014 Best Paper Award (MSOM) and the 2018 Roger Martin Teaching Award. Education: BA, University of St. Gallen, Switzerland MS, Stanford University, USA PhD, Stanford University, USA Research Interests: Afeche explores optimization challenges in dynamic service systems, including pricing under uncertainty, strategic customer behavior in queues, and platform design for shared mobility systems. His work integrates queueing theory, game theory, and empirical analysis to address real-world operational inefficiencies in healthcare delivery and transportation networks. Recent studies focus on ride-hailing market mechanisms and bipartite matching systems. Awards: 2014 Best Paper Award, Manufacturing & Service Operations Management 2018 Roger Martin Award for Excellence in Teaching Grants & Editorial Roles: Editor for Management Science and Operations Research, with funding reviews for agencies in Canada, Hong Kong, Israel, and the US. Past chair of the Service Management SIG for MSOM Society. Labs/Teams: Active in Rotman's Operations Management group and collaborates with industry partners on supply chain optimization and revenue management projects.

Hasan DavulcuView profile

Professor

• Sociocultural Modeling
• Artificial Intelligence
• Machine Learning
• +5 more

Hasan Davulcu is a Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He holds a B.S. in Mathematics from Middle East Technical University (Turkey) and M.S./Ph.D. in Computer Science from Stony Brook University (NY). His research focuses on sociocultural modeling, AI, machine learning, and behavioral analytics for fraud detection. He leads the CIPS-AI Lab, developing data mining tools for semantic information extraction from social media and web data. Affiliations: Senior Global Futures Scientist (Global Futures Scientists and Scholars Program), Co-founder & CIO of ARTIS MAGI (AI-driven behavioral analysis startup). Education: Ph.D. Computer Science (Stony Brook, 2002), M.S. Computer Science (Stony Brook, 1995), B.S. Mathematics (METU, 1993). Research interests include: Sociocultural modeling and persuasive AI. Web/social media mining, information extraction, and database systems. Behavioral analytics for fraud detection and countering extremist influence. Key achievements: 2011 HSCB Focus Exceptional Scientific Achievement Award for work on sociocultural modeling in the DOD Minerva project. Principal Investigator on NSF and DoD grants, including behavioral analytics for financial fraud and social influence analysis of extremist groups. Grants & Projects: NSF PFI:BIC Grant (2014-2019): Behavioral analytics for fraud detection via visual analytics infrastructure. DoD Minerva (2015-2019): Measuring social influence of extremist groups. ONR Projects (2018-2021): Modeling polarization, adversarial framing, and disinformation tracking. Labs/Teams: Cognitive Information Processing Systems (CIPS-AI) Lab, which pioneers data mining techniques for unstructured social media data and semantic representation systems.

• Consumer Behavior
• Marketing Strategy
• Retail Distribution
• +4 more

Mélanie Ouvry is an Associate Professor and Dean of Faculty at MBS Education since 2017. With over 15 years of experience in higher education, she has held roles as program director for specialized master's programs, department head for marketing and interim management, and served as a communication strategy consultant at Publicis Group. Her research focuses on consumer behavior, retail dynamics, and cross-cultural marketing experiences. Her academic expertise includes strategic marketing, buyer behavior analysis, and advertising strategy. Key research themes explore multi-store shopping behaviors, consumer experience valuation, loyalty mechanisms, and the cognitive dimensions of retail environments. She has conducted extensive studies in retail distribution systems, communication strategies, and tourism-related consumer behavior in historical commercial districts like the Medina of Sousse. Her publications span topics from grocery shopping decision-making to television audience engagement, reflecting her interdisciplinary approach bridging marketing, cognitive science, and cultural studies. Teaching responsibilities include advanced marketing strategy courses and consumer behavior analysis modules.

• Plasmonics
• Photocatalysis
• Electrocatalysis
• +3 more

Professor Emiliano Cortés is a faculty member at the Ludwig Maximilian University of Munich (LMU), where he leads research in Plasmonic and Photonic Chemistry at the Nano-Institute Munich. His work bridges the fields of nanotechnology, physical chemistry, and materials science, focusing on light-matter interactions for energy conversion applications. Dr. Cortés' research focuses on plasmonics , photocatalysis , and electrocatalysis at the nanoscale. His group investigates how the dynamics of photons, plasmon-polaritons, carriers, phonons, and molecular states influence chemical reactivity. A key aspect of his work involves developing techniques to study plasmonic systems at the single particle level and designing rational synthesis approaches for plasmonic colloidal photo and electrocatalysts. His research has significant implications for sustainable energy technologies, environmental remediation, and advanced sensing applications. Analysis of Professor Cortés' recent publications reveals a strong focus on energy conversion processes, with particular emphasis on CO2 reduction, ammonia synthesis, and hydrogen production. His work integrates plasmonic effects with catalytic processes to enhance reaction efficiencies, often through innovative interface engineering and nanostructure design. The research spans fundamental studies of charge carrier dynamics to practical applications in energy storage and environmental technologies. Professor Cortés actively mentors doctoral candidates and postdoctoral researchers, currently advertising open positions for projects on Single particle photo and electrocatalysis and Synthesis of hybrid colloids . His research group, the Hybrid Plasmonics Lab (www.hybridplasmonics.org), receives funding from various sources to support their work on plasmon-mediated chemistry for sustainable applications. The Cortés research group operates within the Nano-Institute Munich, utilizing state-of-the-art facilities for nanomaterial synthesis, characterization, and testing. Their work combines experimental approaches with theoretical modeling to understand and harness light-matter interactions at the nanoscale for practical applications in energy conversion and environmental technologies.

Craig A. BondView profile

Professor

• Natural Resource Economics
• Environmental Economics
• Stochastic Dynamic Modeling
• +6 more

Craig A. Bond is a Professor at the RAND School of Public Policy, a Senior Economist at RAND Corporation, and Editor-in-Chief of the RAND Journal of Economics. His work bridges military resource allocation and environmental economics through advanced econometric modeling. Current Roles: Research QA Manager (RAND Arroyo Center), Senior Economist Methodological Expertise: Stochastic dynamic programming, discrete choice modeling, non-market valuation Key Research Themes: Military readiness, coastal resilience, green infrastructure, post-disaster recovery Research Interests: Craig Bond specializes in natural resource economics , environmental economics , and applied welfare economics , with recent work focusing on: Risk modeling for defense acquisitions and personnel strategy Resilience dividend valuation frameworks Green infrastructure cost-benefit analysis Climate adaptation in coastal communities Publication Trends: His 15 most recent works (2017-2025) show interdisciplinary focus across: Military Economics: Recruiting optimization, training requirements, economic multipliers Environmental Policy: Coastal land loss, invasive species impact, water management Resilience Modeling: Disaster recovery frameworks, adaptive systems

Patrick ScholtenView profile

Professor

• Industrial Organization
• E-commerce Economics
• Applied Game Theory
• +2 more

Dr. Patrick Scholten is Professor of Economics at Bentley University, researching industrial organization, e-commerce economics, and applied game theory. His work analyzes firm behaviors in online markets using econometric methods. Education includes: PhD in Economics, Indiana State University MS in Student Affairs and Higher Education, Indiana State University Research examines price dispersion, network effects, ID verification impacts, and corporate social responsibility expectations. Recent publications focus on geo-cultural FDI determinants and business sustainability pressures.

Onur VarolView profile

Assistant Professor

• Computational Social Science
• Network Science
• Machine Learning
• +4 more

Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.