Monday, March 14, 2022 7:30 am - 9:00 am

Baker Ballroom

Professional Development - Mentor/Mentee Collaborations

Presenter:   Matthew Lee Smith, PhD, MPH, CHES, FGSA, FAAHB

Texas A&M University

Title:  Keys to Quality Mentorship and Productive Collaborations: Lessons Learned from AAHB Scholars

This interactive session will provide attendees with tips and strategies essential to form strong and productive mentor/mentee relationships and collaborations.  

The session will begin with brief presentations from the AAHB Research Scholars Mentorship Program (RSMP) cohorts to highlight their efforts over the past year. Then, a panel discussion will be facilitated to enable mentor/mentee pairs to share lessons learned and address questions from the audience. Past RSMP cohorts and those interested in being part of the 2022 RSMP are encouraged to attend. 

Objectives:

• Attendees will increase their familiarity with the scope and potential benefits of participation in the AAHB Research Scholars Mentoring Program.
• Attendees will be able to describe several specific ways in which mentoring can promote the development and scholarship of early career professionals.
• Attendees will be able to identify at least three strategies for making the most out of a mentoring relationship.

Tuesday, March 15, 2022 7:30 am - 9:00 am 

Baker Ballroom 

Professional Development - Meta-Analysis with STATA

Moderator:  Matthew E. Rossheim, PhD, MPH, CPH

University of Texas Health Science Center at Fort Worth

Department of Health Behavior and Health Systems

School of Public Health

Presenter:  STATA Representative

This professional development session is designed for graduate students and researchers.

Tuesday's PDMC Sponsor:  Stata Inc.

Tuesday, March 15, 2022 1:00 pm - 2:30 pm 

Baker Ballroom 

Presenter:  Ruopeng An, PhD

Brown School, Washington University in St. Louis

Title: Incorporating Artificial Intelligence in Public Health Teaching and Research

A Brief Summary:  Artificial intelligence (AI), characterized by machine learning (ML), has been increasingly recognized as an indispensable tool in health sciences, with relevant applications expanding from disease outbreak prediction to medical imaging and from patient communication to behavioral modification. However, gaps in adopting and utilizing those modern data analytic techniques prevail in public health. This workshop aims to provide an overview of the basic concepts and applications of AI and ML in the fields of public health, medicine, and beyond. After attending the workshop, participants will be able to (1) understand the ML programming paradigm, (2) learn various contemporary applications of ML, (3) differentiate various types of ML systems, (4) explain the main challenges of ML and potential remedies, and (5) familiarize with a rich set of resources (e.g., textbooks, online courses, computational platforms, software packages, datasets) that can facilitate learning AI and ML.