معرفی
Filip Edström is a PhD student in Statistics at the Umeå School of Business, Economics and Statistics (USBE), Umeå University. He is affiliated with the Centre for Transdiciplinary AI. His research focuses on causal models and their applications in AI, particularly addressing fairness in machine learning and synthetic data generation.
Education: Current PhD candidate in Statistics at USBE. Previous academic background not explicitly detailed in provided texts.
Research Interests: Explores causal inference frameworks within AI systems, emphasizing ethical considerations like algorithmic fairness. Engages with synthetic data methodologies to enhance AI robustness and transparency. Collaborates on projects such as ROCC – Robots with Causal Capabilities (2023–2026), aiming to integrate causal reasoning into robotics.
Teaching: Serves as a teaching assistant for Statistik A1 and instructor for Data Analytics with R at Umeå University.
Labs/Teams: Active member of the Centre for Transdiciplinary AI, fostering interdisciplinary AI research.
