Past talk · AI/ML Seminar Series
From Models to Medicine: Theoretical Foundations and Practical Impact of Machine Learning in Healthcare
Assistant Professor, Department of Computer Science, ETH Zurich
- Date & time
- Thursday, August 7, 2025 · 1:00 PM
- Location
- Donald Bren Hall 4011
Abstract
The fusion of artificial intelligence and medicine is driving a healthcare transformation, enabling personalized treatment tailored to each patient's unique needs. By leveraging advances in machine learning, we can transform challenging and diverse patient data into actionable insights that have the potential to reshape clinical practice. In this presentation, I will cover both the theoretical foundations and practical applications of machine learning in healthcare. I will highlight innovative approaches designed to enhance diagnostics, improve patient care, and make medical decision-making more accessible and reliable. I will touch on five fundamental, interconnected areas: multimodal data integration, unsupervised structure detection, longitudinal data analysis, transparent model development, and development of decision support tools. Through real-world medical examples, I aim to illuminate the collaborative future of machine learning and healthcare.
About the speaker
Julia Vogt is an assistant professor in Computer Science at ETH Zurich, where she leads the Medical Data Science Group. The focus of her research is on linking computer science with medicine, with the ultimate aim of personalized patient treatment. She has studied mathematics both in Konstanz and in Sydney and earned her Ph.D. in computer science at the University of Basel. She was a postdoctoral research fellow at the Memorial Sloan-Kettering Cancer Center in NYC and with the Bioinformatics and Information Mining group at the University of Konstanz. In 2018, she joined the University of Basel as an assistant professor, and in May 2019 she and her lab moved to ETH Zurich.