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I-X Seminar: Pushing the boundaries of what is possible with ML: The Reality-Centric AI Agenda with Professor Mihaela van der Schaar

Key Details:

Time: 13.00 – 14.00
Date: Tuesday 5 November
Location: Hybrid Event | I-X Conference Room | Level 5 |  Translation and Innovation Hub (I-HUB)
Imperial White City Campus
84 Wood Lane
W12 0BZ

13:00 - 14:00
05/11/2024
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Speaker

Professor Mihaela van der Schaar

Professor Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge. 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 and Fellow of the Royal Society in 2024. She has received numerous awards, including the Johann Anton Merck Award (2024), 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. She was a Turing Fellow at The Alan Turing Institute in London between 2016 and 2024.

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.

Talk Title

Pushing the boundaries of what is possible with ML: The Reality-Centric AI Agenda

Talk Summary

This talk introduces the Reality-Centric AI agenda, an approach that tackles the complexity and challenges of the real world through machine learning (ML). I will explore how we are expanding the boundaries of ML to advance this vision—ranging from using AI to drive scientific discovery, to pioneering new directions in causal inference over time, to making AI effective with real-world data, and to empowering individuals with AI. Join me to dive into this emerging research agenda and explore how we can join forces to shape the future.  

 

A networking lunch will be provided at the end of the seminar. 

Register

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