van der Schaar Lab

Inspiration Exchange

Inspiration Exchange is a series of engagement sessions aiming to share ideas and discuss topics that will define the future of machine learning in healthcare. These events will target machine learning students, and will emphasize sharing of new ideas and development of new methods, approaches, and techniques.

As a lab, our purpose is to create new and powerful machine learning techniques and methods that can revolutionize healthcare. This doesn’t happen in a vacuum. At inception, we are inspired by ideas and discussions; in implementation, we need connections, trust, and partnership to make a real difference.

While you can learn about our work at major conferences in machine learning or in our papers, we think it’s a better idea to create a community and keep these conversations going. We’re also aware that many people—both in healthcare and machine learning—have questions about what we do, and how they can contribute.

For more information about Inspiration Exchange—and to sign up to join in—please have a look at the sections below, and keep checking for new updates.

Inspiration Exchange

Themed discussion sessions specifically for machine learning students (particularly masters, Ph.D., and post-docs).

We would like to:
– discuss machine learning models and techniques
– share ideas about how machine learning can revolutionize healthcare
– spark new projects and collaborations
– raise awareness about this unique and exciting area of machine learning.

Standard session format:
– presentations by van der Schaar Lab researchers
– Q&A
– presentations by participants

Inspiration Exchange session 1 (September 2, 2020)

Our first session was on September 2 at 16:00 BST, and ran for roughly an hour, with 11 questions asked.

Ahead of this session, Mihaela published a piece of content on machine learning and the future of healthcare, entitled AutoML: powering the new human-machine learning ecosystem.

Inspiration Exchange session 2 (October 5, 2020)

Our second session was on October 5 at 16:00 BST, and ran for roughly an hour and 10 minutes.

This session featured presentations from 4 of the van der Schaar Lab’s researchers regarding the Lab’s key AutoML projects. In addition, three session participants presented their own proposals for building on these projects by improving the AutoML methods or applying them in new contexts or applications.

Inspiration Exchange session 3 (November 9, 2020)

Our third session was on November 9 at 16:00 GMT, and ran for roughly 50 minutes.

This session featured presentations from 4 of the van der Schaar Lab’s researchers regarding the lab’s AutoML software packages (AutoPrognosis and Clairvoyance), followed by a Q&A.

Inspiration Exchange session 4 (December 3, 2020)

Our fourth session was on December 3 at 16:00 GMT, and ran for roughly an hour, with 10 questions asked.

The session covered a range of the lab’s most recent and exciting research projects in machine learning for healthcare. A total of 9 short presentations were given by the van der Schaar Lab’s researchers, followed by a Q&A session.

Fifth session in January 2021!

Our next session will be held on January 26 at 16:00 GMT, and will run for roughly 1 hour.

Our theme for the first three sessions was automated machine learning (AutoML), whereas the fourth session was devoted to introducing a range of brand-new and exciting machine learning for healthcare projects the lab has been working on. In our fifth session, we will focus on synthetic data.

If you’d like to join us for future sessions, please sign up using the form below. We’ll be in touch soon with URLs and other info.

Time zones

Cambridge, United Kingdom Tue, 26 Jan 2021 at 16:00 GMT
Paris, France Tue, 26 Jan 2021 at 17:00 CET
New York, USA Tue, 26 Jan 2021 at 11:00 EST
San Francisco, USA Tue, 26 Jan 2021 at 08:00 PST
Beijing, China Wed, 27 Jan 2021 at 00:00 CST
Shanghai, China Wed, 27 Jan 2021 at 00:00 CST

To add your city/time zone, click here.

Sign-up form

To learn more about our team of researchers, click here. You can find our publications here.