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Assembly Series

A tradition of convening thought leaders since 1953

McKelvey School of Engineering

Brown School

Machine Learning: An Overview of Fundamentals and Applications

Thursday, April 22, 2021 | 3:00 PM - 4:00 PM

Virtual Event

Join the Secondary Data in Aging Interest Group for this talk presented by Ruopeng An.

Born in the 1950s, artificial intelligence (AI) symbolizes the effort to automate intellectual tasks usually performed by humans. Machine Learning is an AI application that provides computer systems the ability to learn and improve from experience without being explicitly programmed automatically. In the recent decade, machine Learning models have been increasingly recognized as an indispensable tool in the field of health sciences, and their applications are rapidly expanding from outbreak prediction to medical imaging and from patient communication to behavioral modification.

This talk provides an high-level overview of the fundamental concepts and applications of machine learning in health sciences and beyond.

The Secondary Data in Aging Interest Group is an interdisciplinary learning collaborative. Focusing on research using secondary data, this group discusses theoretical and methodological issues and research of policy and programs relevant for a person’s life course and aging.

All experience levels, department and university/organization affiliations are invited.

This event will take place via Zoom. Add this event to your calendar to access the Zoom meeting link.

Event Type

Meetings & Conferences


Science & Technology, Medicine & Health



Institute for Public Health
Event Contact

Emily Hickner | ehickner@wustl.edu

Speaker Information

Ruopeng An
Associate Professor, Brown School

Ruopeng An conducts research to assess environmental influences and population-level interventions on weight-related behaviors and outcomes throughout the life course. In particular, his work assesses socioeconomic determinants and policies that impact individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people living with a disability.

The goal of his research has been to develop a well-rounded knowledge base and policy recommendations that can inform decision making and the allocation of resources to combat obesity.

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