Mihaela van der Schaar
Time: The Next Frontier in Machine Learning
In this talk, I aim to illuminate the underemphasized yet critical dimension in machine learning: time. I contend that time harbors the potential to revolutionize machine learning methodologies, particularly within healthcare. This presentation underscores the opportunities and challenges that emerge from integrating temporal dynamics into machine learning models, enriching prediction accuracy, inference robustness, and conceptual understanding.
In this talk, I will aim to answer questions such as:
- What new challenges are we encountering as we try to uncover dynamical systems over time and can we overcome them?
- How might the increased precision and accuracy in early disease detection, afforded by integrating temporal dynamics into machine learning models, reduce healthcare costs and improve the quality of life for patients?
- How can we effectively balance the robustness of Bayesian methods with the necessary frequentist guarantees when predicting and managing uncertainties over time?
- How can learning from informative sampling over time help us counteract biases inherent in non-random data collection methods? Could this method be the key to unraveling the subtle, yet critical temporal patterns in health data?
- How might our approach to causal deep learning need to change as we incorporate temporal data?
Biography: 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.