|6. Juni 2023
|The Lecture has to be cancelled on short notice. We hope to be able to welcome Prof. Hansen in Stuttgart at a later point in time.
|Download als iCal:
The Stuttgart ELLIS Unit is pleased to announce the upcoming ELLIS Distinguished Lecture Series talk by Lars Kai Hansen (Technical University of Denmark).
To let the data speak machine learning is often based on weak inductive biases, hence the general notion of a black box approach. However, in many domains - including bio-medicine - explainable AI is key to successful application and we need to open the black box and study what has been learned. I will present recent contributions to our understanding of learned representations illustrated by applications in bio-medicine, computer vision, and natural language processing.
Professor Hansen will also be available for individual meetings on June 6. If you are interested in scheduling a meeting, please email email@example.com.
Lars Kai Hansen has a PhD in physics from University of Copenhagen. Since 1990 he has been with the Technical University of Denmark, where he heads the Section for Cognitive Systems. He has published more than 350 contributions on machine learning, signal processing, and applications in AI and cognitive systems. His research is generously funded by Danish Private Foundations and Research Councils, by the European Union, and the US National Institutes of Health. He has made seminal contributions to machine learning including the introduction of ensemble methods. His work in functional neuroimaging includes the first brain state decoding work based on PET (1994) and on fMRI (1997). He was elected Catedra de Excelencia at UC3M Madrid (2011), ELLIS Society Fellow (2020), and received the Novo Nordisk Foundation’s Distinguished Data Scientist Award (2022).