Trustworthy and Distributed Automated Reasoning

Mihaela van der Schaar (University of Cambridge)

8 February 2024, 10:00-11:30 | Commissiekamer 3, Aula | No live-stream


Abstrat

In this keynote, I describe new breakthroughs on ML interpretability. This will include 1) powerful ways to interpret ML methods for time-series forecasting, clustering (phenotyping), and heterogeneous treatment effect estimation, 2) provide personalized explanations of ML methods which refer to the unique experience of the user of the ML method, and 3) autonomously discover scientific concepts using concept activation regions, which are generalizations of concept-based explanations. To learn more about our work in this area - see our website dedicated to this topic - https://www.vanderschaar-lab.com/interpretable-machine-learning/ and our github - https://github.com/vanderschaarlab/Interpretability

 

 

 

 

Mihaela van der Schaar

Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is founder and director of the Cambridge Centre for AI in Medicine (CCAIM).

Mihaela was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), a National Science Foundation CAREER Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award.

Mihaela is personally credited as inventor on 35 USA patents (the majority of which are listed here), many of which are still frequently cited and adopted in standards. She has made over 45 contributions to international standards for which she received 3 ISO Awards. In 2019, a Nesta report determined that Mihaela was the most-cited female AI researcher in the U.K.