May 7, 2025, 13:30-15:00
Location: Old observatory, Uppsala University
Registration: a link will be posted here two weeks before the seminar
Speaker: Adel Daoud, Linköping University
Title: The power of the hybrid-statistical-modeling culture: exemplified by combining earth-observation satellites and deep learning to analyze health and living conditions in Africa
Abstract: A fundamental distinction in the sciences, particularly the social sciences, lies between predictive and causal research goals. Yet, the introduction of Machine Learning (ML), while initially lauded for its predictive ability, has blurred this line as researchers explore its use for causal inference. My article on the Three Statistical Cultures addresses this evolving landscape, identifying a Hybrid Modeling Culture (HMC). Within HMC, predictive and causal inference form an intricate synergy, suggesting that, at its limit, the distinction itself can dissolve. This talk will delve into a compelling manifestation of this hybrid culture: Planetary Causal Inference. We explore how combining Earth Observation (EO) data – granular geographical and temporal information from satellites – with causally-oriented ML overcomes the limitations of traditional survey or census data. This allows us to analyze critical social dynamics like urbanization, conflict, climate, and crucially, poverty, at fine spatial and temporal resolutions across the globe. As a central example, I will present our work using satellite imagery within this Planetary Causal Inference framework to measure and understand poverty dynamics in Africa, illustrating the potential for scalable, high-resolution insights into pressing global challenges.
Bio: Adel Daoud is a Senior Associate Professor at the Institute for Analytical Sociology, Linköping University, and an Affiliated Associate Professor in Data Science and Artificial Intelligence for the Social Sciences, Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden. Previously he held positions at Harvard University, Stanford University, the University of Cambridge, the Max Planck Institute for the Studies of Societies, and the Alan Turing Institute. His research has both a social scientific and methodological orientation. For the social sciences, he researches global development, focusing on global poverty and health. Daoud implements novel methodologies in machine learning and causal inference. He has published in journals such as PNAS, Science Advances, World Development, International J of Epidemiology, and Ecological Economics, and machine-learning conferences such as the Association for the Advancement of Artificial Intelligence (AAAI) and the North American Chapter of the Association for Computational Linguistics (NAACL). (More information is provided at www.adeldaoud.com)
Daoud leads The AI and Global Development Lab (more information at https://aidevlab.org/). The vision of the Lab is to “combine AI, earth observation, and socio-economic theories to analyze sustainable and human development globally.” The Lab’s activities are a collaborative effort at Harvard, Texas, Chalmers, and Linköping University. The Lab is mainly funded by the Swedish Research Council.
Daoud is also the creator of a new podcast called the Journeys of Scholars, a podcast dedicated to understanding how leading academics achieve success. Through in-depth interviews, it explores the practical strategies, daily habits, and guiding principles that shape top academic performers. Rather than relying solely on books or lectures, each episode highlights personal journeys and reflections, offering listeners a nuanced view of academic excellence. These conversations address topics often overlooked in public academic discussions, revealing insights on career trajectories, strategic thinking, and habits that can guide others in their own pursuits. By sharing the firsthand experiences of accomplished scholars, Journeys of Scholars aims to provide advice, assistance, and inspiration for those striving toward academic mastery. You can find all the recent interviews on Spotify, and on the Youtube playlist.