Lecture Series on Causal Inference methods for real-world data

The ACADI team from Luxembourg Institute of Health (LIH), in collaboration with the Luxembourg Institute of Socio-Economic Research (LISER) and the University of Luxembourg, hosts a Lecture Series on "Causal Inference Methods for Real-World Data." This initiative addresses the growing importance of real-world data (RWD) analysis in fields like healthcare, economics, and environmental studies, where understanding causal relationships is essential for effective decision-making. The Series provides researchers, policymakers, and analysts with advanced tools to mitigate biases, define estimands, and employ cutting-edge artificial intelligence (AI) techniques to derive robust causal insights. Through a multidisciplinary approach, the program aligns with global priorities such as precision health and data-driven decision-making, fostering innovation and impactful collaborations. Featuring internationally renowned speakers such as Prof Miguel Hernán from Harvard and Dr Peter Tennant from the University of Leeds, and equitable representation across genders and career stages, the program highlights foundational theories, advanced methodologies, and practical applications. Recorded webinars are available at https://www.lih.lu/fr/event/lecture-series-causal-inference-methods-for-real-world-data-2025-2026/