van der Schaar Lab

IEEE Data Science and Learning Workshop 2021 keynote


Mihaela van der Schaar will deliver a keynote talk at the 2021 IEEE Data Science and Learning Workshop (DSLW), an event to be co-located with ICASSP 2021, hosted by by the IEEE Signal Processing Society (supported by the SPS Data Science Initiative).


Why medicine is creating exciting new frontiers for machine learning


Medicine stands apart from other areas where machine learning can be applied. While we have seen advances in other fields with lots of data, it is not the volume of data that makes medicine so hard, it is the challenges arising from extracting actionable information from the complexity of the data. It is these challenges that make medicine the most exciting area for anyone who is really interested in the frontiers of machine learning – giving us real-world problems where the solutions are ones that are societally important and which potentially impact on us all. Think Covid 19!

In this talk I will show how machine learning is transforming medicine and how medicine is driving new advances in machine learning, including new methodologies in automated machine learning, interpretable and explainable machine learning, dynamic forecasting, and causal inference.

Location and local date/time

This event will take place online on June 6 at 14:40 EDT (19:40 BST).

About the event

DSLW aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science and learning theory and applications. The workshop provides a venue for innovative data science & learning studies in various academic disciplines, including signal processing, statistics, machine learning, data mining and computer vision. Both studies on theoretical and methodological foundations and application studies in different domains (e.g., health care, earth and environmental science, applied physics, finance and economics, intelligent manufacturing) are welcome.

The event is finished.


Jun 06 2021


Note: time is shown in BST
19:40 - 20:30