We are pleased to invite you this Friday to a talk by Professor Frank van der Wouden, PhD, titled Predicting Creative Production Using a Geographical and Causal ML Framework.
🗓️ Date: Friday, May 1, 2026
🕛 Time: 2:30 – 3:15 PM
📍 Location: 37 Hillhouse Ave, Room 102
Title: Predicting creative production using a geographical and causal ML framework
Abstract: Creativity is geographically concentrated and strikingly persistent. Only a small number of cities produce a disproportionate share of patents, scientific papers, cultural works, software, art and new firms. Yet we still lack a rigorous way to predict where creative production emerges, explain why it persists and identify what might be changed through policy. This project develops a geographical and causal machine-learning framework to address that gap. Rather than measuring creativity as an abstract trait, we analyze geo-coded proxies of creative output across innovation, scholarship, culture, software, art, firms and events. We integrate three traditions (human geography, physical geography and remote sensing/GIS) by linking creative outcomes to harmonized measures of population, built environment, climate, land cover and the HKU GLASS land-surface satellite suite. Using an open Python pipeline and causal-ML methods, we estimate which features matter most, how their importance changes over time and how relationships differ across regions, producing both academic insight and policy-relevant evidence.
Speaker: Frank van der Wouden, PhD
Bio: Professor van der Wouden received his PhD from the University of California, Los Angeles in 2018 and a Research Master’s degree (2012) and Bachelor’s degree (2010) from Utrecht University in the Netherlands. Before joining the faculty of Hong Kong University, he was a post-doctoral scholar at the department of Management and Organizations at the Kellogg School of Management of Northwestern University and affiliated with the Northwestern Institute on Complex Systems. Professor van der Wouden is an innovation scholar, focusing on the strategic dimensions of managing technological change and innovation, knowledge creation and (regional) economic development. He is interested in the production of new technology and the uneven spatial distribution of economic and innovative activities, often through the lens of collaboration. His research informs corporate strategic decision-making, entrepreneurship and public policy. His work is distinctly interdisciplinary, using theories and methods from strategy, management, innovation studies, economics, sociology, network science and geography. Most of this research is quantitative and computationally intensive, using econometrics, network analysis, data mining, and machine learning tools to answer research questions.
