van der Schaar Lab

AIDA AI Excellence Lecture

Presentation

Mihaela van der Schaar will deliver a presentation as part of the AI Excellence Lecture Series hosted by the International AI Doctoral Academy (AIDA).

Title

Machine learning for medicine and healthcare

Abstract

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 time-series, causal inference, interpretable and explainable machine learning, as well as the development of new machine learning areas – quantitative epistemology.

Location and local date/time

This event will take place online on September 21 at 17:00 CEST (16:00 BST).

About the event

AIDA is very pleased to offer you high-quality scientific lectures on several current hot AI topics.

Lectures are offered alternatingly by:
– Top highly-cited senior AI scientists internationally or
– Junior AI scientists with the promise of excellence (AI sprint lectures)

Lectures are typically held once per week, Tuesdays 17:00-18:00 CET (8:00-9:00 am PST), (10:00 am-11:00am CST).

Attendance is free.

The lecture will last 60 minutes (45 minutes plus questions). Questions should be oral at the end of the talk by using the ‘Raise hand’ button.

Presentation

Mihaela van der Schaar will deliver the 4th annual Kalman Lecture at the University of Potsdam.

Title

Quantitative epistemology: conceiving a new human-machine partnership

Abstract

Quantitative epistemology is a new and transformational area of research pioneered by our lab as a strand of machine learning aimed at understanding, supporting, and improving human decision-making. We are developing machine learning models that  capture how humans acquire new information, how they pay attention to such information, how their beliefs may be represented, how their  internal models may be structured, how these different levels of knowledge are leveraged in the form of actions, and how such  knowledge is learned and updated over time. Because our approach is driven by observational data in studying knowledge as well as using machine learning methods for supporting and improving knowledge acquisition and its impact on decision-making, we call this “quantitative epistemology.

Our methods are aimed at studying human decision-making, identifying potential suboptimalities in beliefs and decision processes (such as cognitive biases, selective attention, imperfect retention of past experience, etc.), and understanding risk attitudes and their implications for learning and decision-making. This would allow us to construct decision support systems that provide humans with information pertinent to their intended actions, their possible alternatives and counterfactual outcomes, as well as other evidence to empower better decision-making.

Location and local date/time

This event will take place online on October 4 at 10:15 CEST (09:15 BST).

About the event

The Kalman Lecture is an annual public lecture and is named after Rudolf Emil Kálmán, the co-invented and developed of the Kalman Filter. The new annual lecture series will give insights into current scientific topics at the interface of machine learning, statistics and applied mathematics.

The event is finished.

Date

Sep 21 2021
Expired!

Time

Note: time is shown in BST
16:00 - 17:00
Category