معرفی
Ryan Dew is an Assistant Professor of Marketing and the Govil Family Faculty Scholar at the Wharton School of the University of Pennsylvania. He is affiliated with the Wharton AI and Analytics Initiative, Wharton Human-AI Research, and the Penn Eidos LGBTQ+ Health Initiative. His research bridges marketing, data science, and machine learning, with a focus on developing interpretable computational tools for customer analytics and design.
Research Interests: His work centers on marketing analytics, data-driven design, preference measurement, and decision support. He leverages Bayesian nonparametrics, deep generative models, and representation learning to analyze unstructured data (e.g., text, images) in marketing contexts such as branding, logo design, and influencer selection. His methodological approach emphasizes flexibility and interpretability in modeling consumer behavior.
The recent publications reflect a strong trend toward integrating AI and machine learning into core marketing problems—particularly in customer segmentation, product design, and influencer marketing. There is a clear emphasis on adaptive systems, dynamic modeling, and the use of rich data sources to enhance decision-making.
Scientific Awards:
- 2022 Frank M. Bass Award
- 2018 INFORMS SMS Doctoral Dissertation Award
- 2018 ASA Marketing Section Doctoral Research Award
- Finalist, 2019 Frank M. Bass Award
- Finalist, 2020 Paul Green Award
- Finalist, 2022 John D.C. Little Award
- 2023 MSI Young Scholar
- Wharton School's 2024-2025 Govil Family Faculty Scholar
- Wharton Teaching Excellence Award
Advising and Grants: Ryan Dew teaches PhD and MBA courses including MKTG9570 (Empirical Models in Marketing) and MKTG7120 (Data & Analysis for Marketing Decisions). He advises PhD students through dissertation supervision (MKTG9950) and independent study. He co-organizes a cross-school virtual reading group on probabilistic ML and Bayesian computation for junior faculty and PhD students, indicating active mentorship and collaboration. While specific grants are not listed, his research awards and scholar designation suggest competitive funding support.
Labs and Teams: He is actively involved in the Wharton AI and Analytics Initiative and Wharton Human-AI Research, suggesting participation in interdisciplinary research teams focused on AI applications in business. His collaborations span multiple institutions and disciplines, including psychology, computer science, and statistics.
