Cong Shi, also known as Alex Shi, is a Professor of Management at the Miami Herbert Business School, University of Miami, since 2025. Previously, he served as Associate Professor at the University of Michigan (2019-2023) and Assistant Professor there (2012-2019). His academic journey began with a B.Sc. in Mathematics (First Class Honors) from the National University of Singapore (2007) and a Ph.D. in Operations Research from MIT (2012) under Professor Retsef Levi. Education : MIT (Ph.D.), NUS (B.Sc.) Current Role : Professor, Management, Miami Herbert Business School Prior Roles : Associate Professor (Tenured), University of Michigan; Assistant Professor, University of Michigan His research spans Revenue Management, Supply Chain Management, Healthcare Operations, Human-Robot Interaction, and Data-Driven Optimization. Recent publications focus on fairness-constrained inventory, sequential pricing, and trust-aware robotics. He has received prestigious awards including the Senior Research Award (2025) and Amazon Research Award (2021), alongside multiple INFORMS recognitions. The 15 most recent articles highlight advancements in inventory control with fairness constraints, sequential pricing algorithms, and trust propagation models in robotics. His work bridges theoretical rigor with practical applications in supply chains and human-robot collaboration. Scientific Awards : Senior Research Award, Miami Herbert Business School, 2025 Amazon Research Award, 2021 INFORMS Meritorious Service Awards (2018, 2019, 2021, 2023) IOE Graduate Course Professor of the Year, University of Michigan, 2019 He has advised 10 PhD students, many now in academia (e.g., UC Berkeley, Penn State) or tech roles (Meta, Amazon). Grants include NSF funding as PI and Co-PI.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱-۱۵ از ۵۸ استاد راهنما
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Gustavo Vulcanoمشاهده پروفایل
استاد مدعو
Gustavo Vulcano is an Adjunct Professor in the Department of Information, Operations and Management Sciences at the Leonard N. Stern School of Business, New York University, where he has been affiliated since 2002. He served as Assistant Professor (2002–2010), Associate Professor (2010–2017, tenured in 2012), and has held an adjunct role since 2017. His academic work bridges theoretical and applied operations management with strong industry engagement. Education: Ph.D. in Operations Management, Columbia University, 2003 M.Phil. in Operations Management, Columbia University, 2000 M.S. in Computer Science, University of Buenos Aires, 1997 B.S. in Computer Science, University of Buenos Aires, 1994 His research focuses on revenue and pricing analytics , retail operations , and supply chain management , particularly emphasizing customer choice modeling , data-driven optimization , and computational methods in network revenue management . He integrates stochastic modeling and behavioral insights to develop practical pricing and operational strategies. His work is deeply rooted in real-world applications across airlines, retail, and financial services. The analysis of his publications reveals a consistent trend in leveraging data-driven decision-making under uncertainty, with a focus on dynamic pricing, demand learning, and robust optimization. His articles span premier journals such as Operations Research and Management Science , reflecting a strong theoretical foundation combined with empirical and computational rigor. Key thematic areas include customer behavior modeling, network revenue management, and stochastic optimization for service industries. Scientific Awards and Leadership: Chair, INFORMS Revenue Management and Pricing Section (2016–2017) Associate Editor, Operations Research and Management Science Prof. Vulcano has advised numerous PhD and master’s students and has secured research grants through industry collaborations. His consulting projects with Delta Airlines, Sabre Holdings, Aerolíneas Argentinas, and ICBC demonstrate a strong commitment to translating academic research into practical solutions. He has taught core courses such as Operations Management , Pricing and Revenue Management , and Dynamic Programming across undergraduate, MBA, PhD, and MSBA programs, shaping future leaders in data-driven decision-making. He is actively involved in research labs and teams focused on operations analytics and pricing strategy , often collaborating with interdisciplinary groups at NYU Stern and industry partners. His ongoing editorial roles and consultancy reflect sustained engagement in advancing the field of revenue management and operations science.
Robert Rooderkerk is Associate Professor of Operations Management at the Rotterdam School of Management, Erasmus University Rotterdam, where he is affiliated with the Department of Technology and Operations Management. His research sits at the intersection of marketing and operations, focusing on omnichannel retail, assortment optimization, and fulfillment strategies. He teaches courses on retail operations, empirical research methods, and consumer decision making across undergraduate, MBA, and PhD programs. Research Interests: His research combines empirical and conceptual approaches to understand how data analytics, consumer behavior, and new technologies are transforming retail. He investigates topics such as product line design, dynamic assortment personalization, and the impact of fulfillment failures on customer loyalty. His work integrates methods from econometrics, operations research, and psychology. Publication Trends: His recent publications span journals in marketing, operations, and management, reflecting the interdisciplinary nature of his work. Key themes include the adoption of retail analytics, omnichannel integration, and behavioral aspects of retail operations. There is a strong emphasis on practical relevance and industry applicability. Dutch Marketing Science Award Paul Green Award Finalist, Journal of Marketing Research Advising and Grants: While no direct list of students is provided, he supervises bachelor theses and contributes to PhD training through the ERIM Master of Philosophy program. He has served as coordinator of the Research Training and Bachelor Thesis course. His research has been supported through academic collaborations and has had significant media coverage, indicating public and industry impact. Labs and Teams: He is actively involved in the Marketing-Operations Interface research group at RSM and collaborates with scholars globally. His work contributes to the UN Sustainable Development Goals, particularly through innovations in sustainable retail practices and responsible consumption.
Fariba Karimi is a Professor of Social Data Science at Graz University of Technology and leads the Algorithmic Fairness research group at the Complexity Science Hub (CSH) in Vienna. Her work sits at the intersection of computational social science, network science, and AI ethics, with a strong focus on fairness, inequality, and bias in algorithmic systems. She holds a PhD in Physics and Computational Science from Umeå University, Sweden (2015), and was a Postdoctoral Researcher at GESIS – Leibniz Institute for Social Sciences, Germany. Her research combines large-scale data analysis, agent-based modeling, and network science to study how social structures and algorithms interact to shape disparities, particularly for underrepresented groups. Computational Social Science Algorithmic Fairness and Bias Network Science and Homophily Digital Humanism Urban Inequality and Implicit Bias Gender and Age Equity in Academia Her recent publications reveal a consistent focus on understanding and mitigating algorithmic and structural inequities. Themes include the visibility of minorities in networks, the impact of segregation on health and cognition, gender citation gaps in physics, and the development of fair ranking and recommendation systems. She employs interdisciplinary methods to analyze both digital and real-world social systems. Fariba Karimi has received several prestigious recognitions, including: Young Scientist Award from the German Physical Society (2023) ERC Starting Grant (2024) Nomination for the Hedy Lamarr Award (2021) She leads the 'Humanized Algorithms' project at CSH, funded by the ERC, and co-leads an EU Horizon project (MAMMOth) on multi-criteria fairness in AI. She advises PhD researchers such as Lisette Espín-Noboa and collaborates with institutions like the University of Mannheim and the Centre for Social Sciences. Her work contributes to both academic knowledge and practical solutions for fairer AI systems and more equitable societies.
Dr. Mehmet Gumus is a Professor of Operations Management and Academic Director of the Master of Management in Analytics (MMA) at the Desautels Faculty of Management, McGill University. He holds the Desautels Chair in Supply Chain Management and Business Analytics (2024–2029). His research focuses on supply chain dynamics, consumer behavior, and risk management, with publications in top journals like Management Science and Operations Research . Education : PhD (2007), Industrial Engineering and Operations Research, University of California, Berkeley MA (2007), Economics, UC Berkeley MS (2002), Industrial Engineering and Operations Research, UC Berkeley BSc (1997), Control Systems Engineering and Naval Science, Turkish Naval Academy Research Interests : Supply chain risk management, consumer behavior models, dynamic pricing, supply chain contracting, and mechanism design. His work integrates game theory, dynamic programming, and data analytics to address real-world operational challenges. Recent Article Trends : Recent work explores payment method impacts on urban mobility, channel profit optimization, and personalized delivery systems. Themes include sustainability, digital transformation, and ethical consumerism in retail and logistics. Awards : Bensadoun Faculty Scholar Award (multiple terms) M&SOM iFORM Best Paper Award (2015) MDIIM Faculty Fellow (2015–2017) Grants & Leadership : Principal Investigator on NSERC grants totaling CAD 400K+ for supply chain and pricing research Co-investigator in SSHRC grants for supply chain risk management and sustainable agriculture Academic Contributions : Leads the MMA program, teaches courses in operations analytics and statistics, and collaborates on initiatives like the Marcel Desautels Institute for Integrated Management.
Dennis Eschمشاهده پروفایل
استادیار
Dennis Esch serves as Lecturer (Assistant Professor) in Marketing and Behavioural Science at Cranfield School of Management, Cranfield University, where he acts as the Strategic Marketing and Sales Group's liaison for research matters. Previously, he directed the Cranfield Customer Management Forum, one of the School's premier research practice clubs. Dr. Esch holds award-winning academic qualifications in marketing, psychology and behavioural science from Lancaster University Management School and Cranfield School of Management, establishing a strong interdisciplinary foundation for his research. His research program centers on three interconnected domains: the psychological mechanisms of brand influence in consumer decision-making, the transformative impact of emerging technologies on consumer perceptions and preferences, and the complex relationship between social consumption experiences and human happiness. Methodologically, he integrates behavioral science principles with marketing theory through quantitative approaches including experiments, field studies, and big data analysis to address questions with both theoretical significance and practical managerial relevance. Dr. Esch's publication record reveals an evolving research trajectory from foundational consumer behavior studies (2016-2019) examining product assortment effects, sports consumption impacts, and social identity dynamics, toward contemporary methodological innovations in mobile research platforms (2022-2025). His recent work demonstrates particular expertise in evaluating mobile-first platforms for crowdsourcing behavioral, advertising, and personality research, addressing critical questions about digital research validity and ecological relevance. While specific major scientific awards beyond his noted 'award-winning degrees' aren't detailed in available information, his research has been published in reputable outlets including Behavior Research Methods and Academy of Marketing Science proceedings, indicating scholarly recognition. Dr. Esch brings extensive international teaching experience across multiple contexts, having instructed postgraduate students and executives in brand management, marketing strategy, consumer behavior, and research methods in the UK, Germany, and Switzerland. His pre-academic industry background includes significant roles at Audi, Henkel, Vaillant Group, and Swiss Post, providing practical grounding for his academic work and enhancing the real-world applicability of his research findings. His research methodology reflects a commitment to bridging the gap between laboratory rigor and field relevance, particularly through his investigations of mobile research platforms that can capture authentic consumer experiences while maintaining scientific validity. This approach addresses contemporary challenges in behavioral research methodology while generating actionable insights for marketing practitioners.
Sajad Modaresiمشاهده پروفایل
استادیار
Sajad Modaresi is an Assistant Professor of Operations at the Kenan-Flagler Business School, University of North Carolina at Chapel Hill. His research integrates analytical modeling, statistical methods, and machine learning to address operational decision problems and design practical solutions. He specializes in data analytics for retail operations, online personalization, and dynamic decision-making under uncertainty. PhD in Operations Management, Fuqua School of Business, Duke University MS in Industrial Engineering, University of Pittsburgh BS in Industrial Engineering, Sharif University of Technology Modaresi’s work focuses on developing machine learning algorithms for dynamic operational decisions, such as optimizing personalized assortment and pricing strategies. He also investigates consumer choice models in retail environments. His research bridges estimation and optimization to create adaptive systems for uncertain settings. His publications include studies on data-driven assortment personalization, combinatorial optimization, and consumer perception of brands. These works have been recognized with awards from prestigious competitions like the MSOM Student Paper Competition and INFORMS JFIG Paper Competition. First Prize, 2018 MSOM Student Paper Competition Second Prize, 2013 INFORMS JFIG Paper Competition Finalist, 2021 MSOM Data-Driven Challenge Modaresi teaches courses in business analytics, retail operations, data-driven decision-making, and operations management, emphasizing practical applications of analytics in real-world scenarios.
- Wealth Inequality
- Family Formation
- Homeownership
- +۴ مورد دیگر
Philipp Lersch is a Professor at the Humboldt University , affiliated with the Institute of Social Sciences under the Faculty of Humanities, Social Sciences and Education. He also serves as the Women's* Representative. His research focuses on wealth inequality, family dynamics, homeownership, and social mobility. Visiting Address: Universitätsstraße 3b, Room 112 Mailing Address: Unter den Linden 6, 10099 Berlin Email: p.m.lersch@hu-berlin.de , pmlersch@hu-berlin.de Research Interests include: Wealth inequality in family contexts Homeownership mobility across Europe Gender roles in financial decision-making Intergenerational wealth transmission Life course sociology Recent Trends in his work emphasize computational reproducibility, cross-national comparisons of housing wealth, and the intersection of demographic shifts with economic disparities. His publications span topics like cohabitation wealth premiums, marital dissolution impacts, and policy-driven financial behaviors.
Ezgi Kayaمشاهده پروفایل
مدرس ارشد
Dr Ezgi Kaya is a Senior Lecturer (Associate Professor) in Economics at Cardiff Business School, Cardiff University. She is also a fellow at the Global Labor Organization (GLO) and a member of the ESRC Peer Review College. Between 2023 and 2025, she was a Research Fellow funded by ADR UK (Administrative Data Research UK), an Economic and Social Research Council (ESRC) investment. Dr Kaya received her PhD in Economics from the IDEA Graduate Programme at Universitat Autònoma de Barcelona in 2014. Her research focuses on labour market inequalities, particularly in relation to gender and immigration. She explores the effectiveness of transparency legislation and family-friendly policies in shaping labour market outcomes, the relationship between labour market institutions and fertility, and the role of assortative mating and household interactions in shaping the labour supply behaviour of married women and men. Additionally, she has conducted significant research on peer effects in academic and economic performance, as well as the co-residence decisions of young adults with their parents. Dr Kaya's recent publications reveal a strong focus on gender pay gap analysis across multiple contexts including medicine, the public sector, and different firm sizes. Her work increasingly utilizes linked administrative data to examine immigrant labor market outcomes and the impact of family policies like shared parental leave. A notable theme across her recent work is the examination of how policy interventions, particularly transparency legislation, affect labor market inequalities. Etta Chiuri Best Paper Prize (2014) Turkish Economic Association Postgraduate Research Award (2008) Dr Kaya is actively involved in supervising PhD students, with current supervisees including Suzanna Nesom, Imran Khan, Julia Diniz, and Xinning Ma. She has previously supervised successful PhD candidates such as Aohan Gao, Jiarui Nan, John Poole, Widdi Mugijayani, and Jiayi Huang. She is also a co-investigator of the GW4 Maternity Leave Network, demonstrating her commitment to research on family-friendly policies and their labor market impacts. As a member of the ESRC Peer Review College and a Research Fellow with ADR UK, Dr Kaya is deeply embedded in the UK research infrastructure, contributing to the advancement of social science research through data linkage and innovative methodologies.
Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.
- Innovation Management
- Marketing
- Entrepreneurship
- +۷ مورد دیگر
Prof. Dr. Christian Barrot is a Professor of Marketing and Innovation at Kühne Logistics University (KLU) in Hamburg. As Dean of Programs (2016–2024), he shaped KLU's award-winning curriculum. His academic journey began at Christian-Albrechts-University of Kiel and BI Norwegian School of Management, followed by research at Penn State and Columbia Business School. He was promoted from Assistant to Professor at KLU (2011–2017) and served as Acting President (2022–2023). Diplom-Kaufmann (MSc. Business Administration), Christian-Albrechts-University of Kiel (2001) Dr. sc. pol., Christian-Albrechts-University of Kiel (2008) Dr. habil., Christian-Albrechts-University of Kiel (2014) His research focuses on innovation management, digital transformation, and customer relationship strategies , emphasizing social networks, referral programs, and quantitative analysis. Recent studies explore Needmining for customer needs extraction , D2C vs multi-brand distribution dynamics, and ethical leadership impacts on purchasing. His work bridges theoretical models (e.g., Bass diffusion extensions) with industry applications (telecom, medical devices). Prof. Barrot's accolades include the 2018 Sheth/Journal of Marketing Award (long-term contribution) and AMA-Sheth Fellowship (2005). He led the DFG-FOR 1452 research group on digital social media marketing, securing €4.0M in funding. His methodological expertise spans agent-based modeling and social network analysis, applied in viral marketing campaigns and product-sampling strategies.
Matthew Jensenمشاهده پروفایل
پژوهشگر ارشد
Matthew Jensen is a Research Fellow at Yale School of Medicine, Yale University. His research focuses on genetics, neuroscience, and the application of artificial intelligence in healthcare. He explores topics such as psychiatric disorders, genetic variation, single-cell genomics, and privacy-preserving genomic data analysis. His work bridges computational biology with clinical insights, particularly in understanding neurodevelopmental disorders and leveraging AI for disease characterization. Key research interests include: Genetic modifiers and their impact on disease variability Single-cell analysis of brain and other tissues Development of AI tools for digital phenotyping and polygenic risk assessment Functional genomics and regulatory element dynamics in human health Recent publications highlight innovations in: Privacy-preserving genomic analysis using homomorphic encryption Multi-cohort studies of schizophrenia transcriptomes Comprehensive mapping of brain regulatory elements No scientific awards or grants are explicitly mentioned in the provided information.
Sebastian Gabelمشاهده پروفایل
استادیار
Sebastian Gabel is an Assistant Professor at the Rotterdam School of Management, Erasmus University and a Scientific Advisor at the Schwarz Group . His research bridges quantitative marketing , machine learning , and econometrics , focusing on developing scalable methods for consumer behavior modeling in retail contexts. Teaching : Courses on AI-driven marketing strategy, big data analytics, and machine learning applications. Research Focus : Deep learning for personalization, recommender systems, pricing, and assortment optimization. His industry collaborations with leading retailers and marketing solution providers have led to revenue growth through automated personalization systems. Notable awards include the 2017 EMAC Best Paper Based on Doctoral Dissertation Award (Finalist) and the 2022 Frank M. Bass Dissertation Paper Award (Finalist) . His work leverages machine learning to transform raw retail data into actionable insights, particularly through frameworks like Product2Vec and P2V-MAP , which map market structures and optimize store layouts.
Jan Becker is a Professor of Marketing and Service Management at Kühne Logistics University (KLU) in Hamburg, Germany. He holds a Dr. habil. and Dr. sc. pol. in Marketing from Christian-Albrechts-University at Kiel. With over 15 years of industry and consulting experience in digital transformation, his work bridges academic research and practical applications in customer management. Academic Affiliation: Kühne Logistics University (2011–present) Research Focus: Customer Relationship Management, Strategic Marketing, Service Management, Electronic Commerce Teaching: Offers courses in Consumer Behavior, Marketing, Marketing Analytics, and Nonprofit Management across bachelor, master, and doctoral programs His research explores critical areas such as: Geographic proximity effects on social influence Proactive postsales service efficiency Reward-scrounging in referral programs Outcome heterogeneity in entertainment marketing CRM implementation challenges in corporate settings Network effects in peer-to-peer systems Notable scientific awards include the 2018 Sheth/Journal of Marketing Award and the 2015 IJRM Best Paper Award. He is a regular visiting scholar at UCLA’s Anderson Graduate School of Management. Jan Becker’s industry collaborations focus on advanced analytical methods for decision-making in customer management, including churn prevention, referral program optimization, and targeting strategies. His empirical studies span telecommunications, online communities, and digital media sectors, emphasizing both theoretical rigor and practical relevance.
- Alcohol Use and Abuse
- Anxiety
- Depression
- +۳ مورد دیگر
Fartein Ask Torvik is an Associate Professor II since 2016, based at an institution not explicitly named in the text. He is also a Researcher/Postdoctoral Fellow at The Norwegian Institute of Public Health since 2012, having completed his PhD there between 2009 and 2012. His academic work spans alcohol use and abuse, anxiety, depression, behavioral genetics, quantitative methods, and personality research. Education : PhD Candidate (2009–2012) at The Norwegian Institute of Public Health. Research Interests : Focuses on behavioral genetics, mental health comorbidity, educational attainment, and the societal impacts of mental disorders. His work combines quantitative methodologies with large-scale population studies, often leveraging genetic and registry data. Key themes include gene-environment interactions, assortative mating, and the interplay between mental health and academic performance. Research Trends in Articles : His recent publications emphasize genetic and environmental influences on mental health, educational disparities, and familial transmission patterns. Studies often use twin cohorts, Mendelian randomization, and national registry data to explore causal relationships in health and education. Awards : No specific scientific awards or honors are listed in the text. Advising & Grants : No formal advisees or grant details are provided. His collaborative projects include the Health, Cognition, Family, and Employment among Men (HOMME) and Learning from Mistakes: A Longitudinal Neuroimaging-Cohort-Registry Study . Labs/Teams : Engaged in interdisciplinary teams focusing on population health, psychiatric genetics, and developmental epidemiology, likely through collaborations with The Norwegian Institute of Public Health and other academic partners.