Find Academic Supervisors

• E-Commerce
• Service Science
• Econometric Analysis
• +4 more

Dr. Yen-Chun Chou is a Full-time Professor at the Department of Management Information Systems, National Chengchi University (NCCU), where he has held the position since February 2024. Previously, he served as Associate Professor (2018-2024) and Assistant Professor (2013-2018). His career spans over a decade at NCCU, focusing on E-Commerce, Service Science, and Econometric Analysis. Ph.D. in Information Systems from Arizona State University's W. P. Carey School of Business (2008-2013) Master of Science in Information Management from Carnegie Mellon University (2006-2007) Bachelor of Science in Information Management from National Chengchi University (2000-2004) Dr. Chou's research bridges E-Commerce with predictive analytics, machine learning, and operations management. His work explores emotional arousal in online reviews, sparse modeling for R&D efficiency, and interdisciplinary integration of buy-till-you-die modeling with machine learning. Recent projects include demand forecasting optimization and semiconductor product design analytics. His publications demonstrate expertise in supervised machine learning , technology adoption frameworks , and customer behavior modeling . Key topics include cross-item learning , meta-analysis of IT organizational adoption , and multi-theoretical productivity growth in IT services. Recipient of U-Micro Best Paper Award (Honorable Mention) and Ministry of Education's Special Outstanding Talent Grant Multiple awards from the National Science Council (now NSTC) and political university's Academic Research Excellence Awards Recognized as Distinguished Professor and Senior Excellent Teacher (10-year award) at NCCU Dr. Chou has served as Principal Investigator on over 12 MOST/NSTC projects since 2012, with current research focused on personalized marketing optimization (2025-2029) and semiconductor design analytics (2023-2025). His teaching fields include E-Commerce, Service Science, and Empirical Analysis.

Chen GuoqingView profile

Professor

• Business Intelligence
• Big Data Analysis
• E-commerce
• +4 more

Chen Guoqing is a Professor and Senior Professor of Humanities at Tsinghua University's School of Economics and Management, where he serves as Deputy Director of the Academic Committee. He chairs the National Natural Science Foundation of China's Big Data Major Research Program Guidance Expert Group and directs the Ministry of Education's Higher Education Management Science and Engineering Professional Teaching Guidance Committee, with additional roles on national informatization and New Liberal Arts committees. Education: Bachelor's Degree, Renmin University of China (1982) Master's Degree, University of Leuven, Belgium (1988) Doctorate, University of Leuven, Belgium (1992) Research Focus: Professor Chen pioneers research in Business Intelligence and Big Data Analysis, developing frameworks like PAGE for data-driven decision-making. His work spans E-commerce, IT Strategy, and Fuzzy Logic, with recent emphasis on personalized recommendation systems, online consumer behavior, and AI-human collaboration in business contexts. His publications reveal a trajectory from foundational fuzzy logic research to cutting-edge big data applications, consistently bridging technical innovation with managerial relevance. Awards: AIS Fellow (first from mainland China) IFSA Fellow Fudan Management Outstanding Contribution Award Changjiang Scholar Distinguished Professor National Science Fund for Distinguished Young Scholars National Outstanding Doctoral Dissertation Advisor Leadership: As former Executive Vice Dean of Tsinghua SEM and Vice President of IFSA, he has shaped academic policy globally. He leads major NSFC projects and international collaborations while advising government bodies on informatization strategy. His teaching includes national-level courses like "Management Information Systems" and "Management in the Big Data Era."

Liu ChunView profile

Associate Professor

• Capital Markets
• Financial Measurement
• Risk Management

Liu Chun is an Associate Professor in the Department of Finance at Tsinghua University's School of Economics and Management. He holds a PhD from the University of Toronto (2002-2007), a Master's (1999-2001) and Bachelor's (1995-1999) in Economics and Management from Tsinghua University. His research focuses on capital markets, financial measurement, and risk management. Professor Liu teaches courses including Intermediate Financial Theory, Financial Data Analysis, and Financial Practice Classes. His research explores diverse aspects of China's financial system including local government financing, SME credit access, investor behavior, and market microstructure. Recent work analyzes policy impacts using advanced econometric methods like Bayesian latent variable models and survival analysis. His publications predominantly appear in finance and economics journals, with thematic concentrations in: Chinese financial market dynamics Behavioral finance and investor decision-making Policy evaluation and regional development Financial econometrics and statistical modeling Market microstructure and volatility analysis Fintech innovations and digital finance Professor Liu maintains research collaborations across departments and supervises projects on financial infrastructure development. His office is located in Room B310 of Tsinghua University's Lihua Building in Beijing.

Xiaoyan DengView profile

Associate Professor

• Visual Marketing
• Consumer Behavior
• Marketing Research
• +4 more

Dr. Xiaoyan Deng is an Associate Professor in the Marketing & Logistics department at the Max M. Fisher College of Business, The Ohio State University. She holds a PhD in Marketing from the Wharton School, University of Pennsylvania (2009), and teaches in Fisher’s Undergraduate, MBA, and PhD programs. Education: PhD in Marketing, Wharton School, University of Pennsylvania (2009) Her research focuses on visual marketing , examining how marketplace design elements—including advertising, product and packaging design, and retail displays—influence consumer decision-making . She also investigates marketplace social inference and behavioral nudges . Her work has been published in top journals like Journal of Consumer Research , Journal of Marketing , and Journal of Consumer Psychology , with over 3,800 Google Scholar citations. Recent publications span topics such as fast fashion consumption , color psychology , and retail packaging effects on flavor perception. Her research often integrates consumer neuroscience and multisensory marketing frameworks. Scientific Awards: Marketing Science Institute (MSI) Young Scholar (2017) Finalist for 2021 AMA/MSI/H. Paul Root Award Outstanding Reviewer for Journal of Consumer Research (2017) Dr. Deng serves on editorial review boards for JCR , JM , and JMR , and co-edited a 2023 special issue of the Journal of the Association for Consumer Research . She supervises PhD student research and contributes to academic discourse through conference editorial roles.

Fiona BurligView profile

Assistant Professor

• Energy Economics
• Environmental Economics
• Resource Economics
• +4 more

Fiona Burlig is an Assistant Professor at the Harris School of Public Policy at the University of Chicago, a Faculty Research Fellow at the National Bureau of Economic Research (NBER), Deputy Faculty Director of EPIC-India, and technical advisor to the Odisha Data, Policy, and Innovation Centre (DPIC). She is also an affiliate of J-PAL, BREAD, and the International Growth Centre (IGC). Dr. Burlig's educational background includes: PhD in agricultural and resource economics from the University of California, Berkeley BA in economics, political science, and German from Williams College As an applied microeconomist, Dr. Burlig's research spans the intersection of energy, environmental, and resource economics with development economics. Her work focuses on critical issues in developing countries, particularly India, examining how access to resources like electricity and clean water impacts economic development and human welfare. She employs rigorous experimental and quasi-experimental methods to evaluate the causal effects of policy interventions, with notable studies on rural electrification, groundwater management, and climate adaptation strategies. Dr. Burlig's recent publications reveal a consistent focus on resource management in developing contexts, with particular attention to energy access, water resources, and climate adaptation. Her work often combines field experiments with large-scale data analysis to provide policy-relevant insights. The geographic focus is primarily India, with several studies examining rural development challenges in that context. Methodologically, she is known for innovative experimental designs that address complex policy questions in resource-constrained settings. Dr. Burlig actively collaborates with researchers across disciplines and has secured funding for multiple research projects examining energy access, water management, and climate adaptation strategies in developing countries. Her work with private companies like Spring Health demonstrates her commitment to translating research into practical solutions for clean water access. Dr. Burlig is deeply involved with several research initiatives: EPIC-India, where she serves as Deputy Faculty Director Odisha Data, Policy, and Innovation Centre (DPIC), where she serves as technical advisor National Bureau of Economic Research (NBER), as a Faculty Research Fellow Joint Center for Energy Heritage, where she collaborates on energy policy research

João Niza BragaView profile

Adjunct Assistant Professor

• Consumer Behavior
• Marketing
• Intuition in Decision Making
• +3 more

João Niza Braga serves as an Adjunct Assistant Professor and Post-doctoral Research Fellow at the Catholic University of Portugal, primarily affiliated with the Católica Lisbon School of Business and Economics while also teaching in the Faculty of Human Sciences. His academic roles encompass graduate instruction and research leadership at CUBE (Católica Lisbon Research Unit in Business and Economics). Braga holds advanced degrees in Psychology from the University of Lisbon, including both Master's and Ph.D. qualifications. His international research experience includes visiting positions at Indiana University and New York University. Ph.D. in Psychology, University of Lisbon Master's in Psychology, University of Lisbon His research program investigates intuitive cognitive processes in consumer behavior, economic decisions, and social interactions, with particular emphasis on heuristic processing in online contexts and hedonic experiences. Key contributions examine how representativeness and availability heuristics operate in consumer decision-making, sports prediction, and conspiracy thinking, bridging experimental psychology with real-world business applications. Current work explores digital environment effects on health-related choices and mindfulness interventions. Analysis of his 15 most recent publications (2015-2024) reveals a methodological focus on disentangling cognitive mechanisms through controlled experiments, with recurring themes in hot-hand fallacies, online shopping behavior, and causal perception errors. His work consistently applies psychological theory to business contexts, particularly in marketing and managerial decision-making. Scientific recognition includes: FCT Postdoctoral Research Grant (2017) As a Post-doctoral Research Fellow at CUBE, Braga directs funded research projects examining heuristic processing in digital environments while mentoring graduate students in consumer behavior methodology. His academic service includes developing curriculum for Master's programs across business and human sciences disciplines. He maintains active research collaboration through CUBE, a multidisciplinary hub fostering innovation in business and economics scholarship at Catholic University of Portugal, where his work integrates psychological science with practical business insights.

Hari SundaramView profile

Professor

• Applied Machine Learning
• Network Science
• Human Computer Interaction
• +3 more

Hari Sundaram is a Professor in the Computer Science Department at the University of Illinois at Urbana-Champaign with affiliate appointments in the Charles H. Sandage Department of Advertising, the Institute for Communication Research, and the Center for Social & Behavioral Science. His academic journey includes positions as Associate Professor at the University of Illinois (2014-2021) and Arizona State University (2002-2014), where he also served as Associate Director of the Arts, Media and Engineering program (2012-2009). Dr. Sundaram's educational background includes a Ph.D. in Electrical Engineering from Columbia University (2002), an M.S. in Electrical Engineering from Stony Brook University (1995), and a B.Tech in Electrical Engineering from the Indian Institute of Technology, Delhi (1993). His research, conducted through the Crowd Dynamics Lab, focuses on designing computational systems that empower individuals to make better decisions. His work spans Applied Machine Learning (particularly recommender systems), Network Science (studying how platform rules induce strategic behavior), Human-Computer Interaction (developing systems to elicit truthful preferences), and Mechanism Design (creating rules to incentivize pro-social behavior). His research has significant implications for understanding fairness and discrimination in online markets. Dr. Sundaram's work has been recognized with numerous awards including multiple Best Paper Awards from ACM CSCW (2023), Best Article Award from the Journal of Interactive Advertising (2020), ACM Distinguished Member (2019), IEEE Senior Member (2019), and several IBM Faculty Awards. He has also been consistently recognized for teaching excellence, receiving the "Teacher Ranked as Excellent" award multiple times. As leader of the Crowd Dynamics Lab, Dr. Sundaram oversees research that bridges computer science with social sciences, focusing on how computational systems can enhance human decision-making while addressing fairness concerns. His work has practical applications in online marketplaces, social media platforms, and educational technologies.

Raghu Nandan SenguptaView profile

Professor

• Sequential Estimation
• Statistical Reliability Theory
• Risk Analysis
• +4 more

Dr. Raghu Nandan Sengupta is a Professor at the Department of Management Sciences, Indian Institute of Technology Kanpur (IITK). With a Ph.D. from IIM Calcutta and a BE in Mechanical Engineering from BIT Mesra, he has held visiting positions at institutions including Princeton University, University of Warsaw, and Technische Universität Dresden. His academic leadership includes serving as Head of Department (2017-2020) and Chairman of GATE/JAM-2025. Research Focus: Sequential Estimation, Statistical Reliability Theory, Risk Analysis, Optimization Techniques in Finance, Meta Heuristic Algorithms, and Robust Optimization His publications span topics like reliability-based portfolio optimization , multiobjective decision-making , and brand sensitivity in B2B marketing . Key awards include DAAD Research Stays, EU-NAMASTE Erasmus Mundus Fellowship, and Indo-US S&T Forum Fellowship. He has advised 16 PhD students and contributed to editorial boards of journals including Sequential Analysis and Foundations of Computing and Decision Sciences . Scientific Awards: DAAD Research Stays (2017, 2015) EU-NAMASTE Erasmus Mundus Fellowship (2015) Indo-US S&T Forum Fellowship (2008) Erasmus Mundus Europe Asia Fellowship (2011) He has taught courses such as Probability and Statistics , Quantitative Methods for Decision Making , and Security Analysis & Portfolio Management at IITK, University of Warsaw, and IGIDR Mumbai. His work bridges statistical inference , financial engineering , and operations research , emphasizing practical applications in industry and academia.

• Human Capital
• Socioeconomic Inequalities
• Educational Decision-Making
• +3 more

Pia Pinger is Professor at the Department of Economics, University of Cologne, and serves as Speaker of the excellence cluster ECONtribute - Markets & Public Policy . She holds affiliations as IZA Research Fellow and CESifo Affiliate, with research spanning human capital, socioeconomic inequalities, and behavioral economics. Her educational background includes a Ph.D. from the University of Mannheim. Pinger's work employs causal inference methods to examine how early-life conditions shape lifelong outcomes. She investigates educational decision-making through microeconometric analyses, explores socioeconomic disparities in childhood development, and integrates psychological frameworks into economic models. Her studies frequently bridge economics with demography and public health, revealing mechanisms behind intergenerational transmission of inequality. Publication trends indicate sustained focus on intergenerational health/economic effects (2016-2024), behavioral foundations of economic preferences (2017-2020), and labor market dynamics (2024). Recent work combines experimental designs with large-scale datasets to isolate causal relationships in wage negotiation and childhood development. Her scientific recognition includes: IZA Research Fellow Pinger leads project A02 within the ECONtribute cluster and mentors junior researchers through collaborative projects. Her secured funding supports investigations into human capital formation and policy interventions. Current work-in-progress examines parental investment patterns and talent attraction mechanisms. She directs research activities within the ECONtribute excellence cluster, coordinating interdisciplinary teams studying market behavior and public policy design. Her project leadership (A02) focuses on socioeconomic determinants of human capital development.

• Cognitive Psychology
• Judgment and Decision Making
• Probability Judgment
• +5 more

Peter Juslin is a Professor at Uppsala University, affiliated with the Department of Psychology and the Division of Perception and Cognitive Psychology. His research focuses on cognitive psychology, judgment, and decision-making, particularly on phenomena like overconfidence, the naivety of intuitive statistics, and additive probability integration. He collaborates with interdisciplinary teams across psychology, law, and energy systems. PhD in Psychology (1993), Uppsala University Bachelor of Arts (1989) in Psychology and Philosophy, Uppsala University His research explores how humans make probability judgments, the role of similarity-based processes, and applications to real-world domains like legal decision-making and energy consumption. He critiques traditional heuristics-and-biases approaches, proposing instead that naive sampling models explain judgment errors more effectively. Recent work examines cognitive processes in demand response, environmental psychology, and associative models in probability estimation. Key themes include cognitive constraints, sequential decision-making, and the interplay between intuitive and analytic reasoning. Scientific awards include the Torgny Segerstedt Medal (2008), Oscar Award (1998), and New Scientist Award (1994). He was elected to the Royal Swedish Academy of Sciences in 2013. He teaches advanced courses in cognitive psychology, supervises students at all levels, and engages in public science through articles and lectures to governmental agencies.

Ronald W. NiedrichView profile

Professor

• Consumer Behavior
• Judgment and Decision Making
• Brand Choice
• +3 more

Ronald W. Niedrich serves as Professor and Robert S. Greer Chair in Marketing within the Department of Marketing at Louisiana State University's E. J. Ourso College of Business. Currently holding the position of Department Chairman, he has been a faculty member at LSU since 1999 with previous leadership roles including Director of the Professional Sales Institute (2013-2015), Marketing Department Ph.D. Advisor (2008-2012), and Behavioral Research Lab Administrator (2000-2008). His educational background features a PhD in Marketing from the University of South Carolina (1999), MBA in Business from The College of William and Mary (1987), and BS in Ceramic Engineering from Clemson University (1982). Niedrich's research examines the cognitive mechanisms underlying consumer decision processes, with particular emphasis on how individuals construct brand preferences, form price judgments, and develop brand attitudes. His work bridges psychological theory and marketing practice through rigorous experimental methodologies, frequently investigating the impact of contextual factors like priming effects, exposure sequences, and reference points on consumer responses. This research program has established him as a significant contributor to the theoretical foundations of consumer behavior. His publication record demonstrates consistent engagement with core marketing challenges, evolving from foundational work on disconfirmation paradigms and scale design to contemporary investigations of fluency heuristics and online auction dynamics. The research maintains strong connections between theoretical innovation and practical marketing applications across diverse contexts including retail, advertising, and digital commerce. Professor Niedrich's scholarly contributions have been recognized through: LSU Tiger Athletic Foundation Undergraduate Teaching Award (2007, 2013) E. J. Ourso College of Business Research Excellence Award (2011) As an educator and mentor, he teaches consumer behavior courses at undergraduate, MBA, and doctoral levels while maintaining active research supervision. His 2012 Louisiana Board of Regents grant as Co-Principal Investigator demonstrates ongoing research funding support. The Behavioral Research Lab he previously administered continues to provide critical infrastructure for experimental consumer research at LSU, facilitating sophisticated investigations into decision processes through controlled laboratory environments and advanced data collection techniques.

• Behavioral Economics
• Household Finance
• Cognitive Economics
• +4 more

Andrew Caplin is the Silver Professor of Economics at New York University, where he co-directs the Center for Experimental Social Science and leads multiple research initiatives. His primary affiliations include ongoing roles at NYU and as a Research Associate at the National Bureau of Economic Research (NBER). Professor Caplin's research spans behavioral economics, household finance, cognitive foundations of decision-making, and economic data engineering. Key themes include: Modeling of economic decision-making under cognitive constraints Labor market dynamics and retirement behavior Design and evaluation of economic policies Integration of machine learning with economic theory His recent publications (2019-2025) demonstrate a consistent focus on experimental economics and behavioral insights, with emerging emphasis on AI interactions and judicial decision-making. The work increasingly employs field experiments and large-scale surveys across international contexts. Honors include election as Fellow of the Econometric Society. He leads significant grants including the Sloan-Nomis Program and Vanguard Research Initiative, supporting investigations into cognitive-economic interfaces and retirement planning. At the Center for Experimental Social Science, Professor Caplin coordinates interdisciplinary research on human behavior using experimental methods, facilitating collaborations across economics, psychology, and data science.

Archie Singh KhumanView profile

Senior Lecturer

• Artificial Intelligence
• Computational Intelligence
• Machine Learning
• +5 more

Dr. Archie Singh Khuman serves as Associate Head of Education and Senior Lecturer at De Montfort University's School of Computer Science and Informatics. An award-winning academic and proud DMU alumnus (BSc 2009, MSc 2011, PhD 2017), he specializes in Artificial Intelligence, Computational Intelligence, and Uncertainty Modelling with extensive leadership in curriculum development and Universal Design for Learning. His educational background demonstrates deep institutional commitment: PhD in Computer Science (2017, De Montfort University) MSc in Intelligent Systems (2011, De Montfort University) BSc (Hons) in Computer Science (2009, De Montfort University) Dr. Khuman's research pioneers hybrid uncertainty frameworks, notably the R-fuzzy grey analysis framework (RfGAf), bridging Grey Theory, Fuzzy Logic, and Rough Sets. His work focuses on quantifying perception-based uncertainty for applications in healthcare diagnostics, robotic swarm intelligence, and risk assessment systems, emphasizing real-world implementation through industry partnerships. His publication trajectory reveals increasing interdisciplinary convergence, particularly in healthcare AI applications since 2021. Recent outputs integrate Grey-Fuzzy methodologies for medical diagnostics (diabetes, heart disease), sentiment analysis of pandemic communications, and adaptive systems in automotive/industrial contexts, demonstrating strong translation from theoretical foundations to societal impact. Major recognitions include: Five consecutive Students' Choice Teaching Awards (2018-2024) De Montfort Teacher Fellowship (2022) Senior Fellow of the Higher Education Academy (2022) Leverhulme Trust-funded international Grey Systems network (£124,997) Best Paper Award at Grey Systems and Uncertainty Analysis (2016) As academic lead for the Data Analytics Project, he mentored students in developing machine learning solutions that generated £2.5m savings for retail partners. His grant portfolio includes Royal Society funding for IoT-based scheduling (£12,000) and leadership of the Race Equality Network. Current initiatives focus on transnational education partnerships and SI-PASS peer learning programs. Dr. Khuman co-leads DMU's Institute of Artificial Intelligence research group and serves as School Governor for Inglehurst Junior School, maintaining active collaborations with institutions in China, Canada, Romania, and Spain through the International Network on Grey Systems.

Yang LiView profile

Associate Professor

• Statistical Machine Learning
• Bayesian Nonparametrics
• Scalable Optimization
• +5 more

Yang Li serves as Associate Professor of Marketing and Associate Dean for the MBA Program at Cheung Kong Graduate School of Business (CKGSB). Holding a PhD in Marketing from Columbia Business School alongside dual master's and bachelor's degrees from Columbia and Peking University respectively, he bridges advanced statistical methodologies with practical business applications. His research centers on statistical machine learning and Bayesian nonparametrics applied to consumer behavior analysis, with specialization in online personalization, text mining, and choice modeling. Recent work demonstrates significant focus on fragmented attention economies, ethical AI frameworks, and NFT network dynamics, reflecting contemporary digital market challenges. Management Science Marketing Science Journal of Marketing Research Journal of Consumer Research Harvard Business Review Professor Li's publications reveal evolving expertise from foundational pricing elasticity studies toward cutting-edge AI applications in consumer contexts. His work increasingly integrates generative models and graph neural networks to decode complex consumer collection behaviors and digital ecosystem dynamics. Scientific recognition includes being a Finalist for the 2021 Paul E. Green Best Paper Award. Industry impact is demonstrated through executive education programs and strategic consultancies with Tencent, Haier, and Tmall. As Associate Dean for MBA Programs, he oversees curriculum development while maintaining active corporate governance roles on boards of publicly traded companies across China and Hong Kong, directly applying his research insights to strategic decision-making in digital transformation initiatives.

• Economic Theory
• Behavioral Economics
• Industrial Organization
• +5 more

Ran Spiegler is a Professor of Economics at Tel Aviv University and University College London, specializing in economic theory with a focus on behavioral and industrial organization frameworks. His research portfolio includes: Decision making under flawed causal reasoning Narrative economics in political and economic contexts Markets with boundedly rational consumers Incentive structures in platform-algorithm interactions Recent publications reveal a cohesive trajectory in behavioral industrial organization, emphasizing how cognitive limitations affect market outcomes in digital environments. His work bridges theoretical economics with real-world applications in data markets, media ecosystems, and consumer-platform dynamics, frequently collaborating with scholars like Kfir Eliaz and Yair Antler. No scientific awards, student advisement records, or grant information appears in the provided materials.