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Session Description

Free ticketed event
The Healthcare Data Science for Engineering Education Workshop aims to provide engineering educators with the necessary knowledge and skills to use healthcare data science to improve their teaching and research. The present session will start with the basics of healthcare data science, including, but not limited to, different types of healthcare data and various challenges of working with healthcare data. The workshop will also include a hands-on demo of the All of Us Research Workbench, a data science platform for healthcare analytics and research. Participants will learn how to use the workbench to access, pre-process, and analyze healthcare data, develop predictive models, and visualize the results. We also present a case study utilizing medical imaging for ground truth annotation and clinical diagnostics. The workshop will discuss how healthcare data science can be leveraged to develop new courses, improve existing courses, and conduct research in industrial and systems engineering, data science, and other fields. Participants will be encouraged to share their ideas and experiences and learn how to apply healthcare data science in their work from other engineering educators. The workshop targets engineering educators at all experience levels, from those new to healthcare data science to those successfully using it in their teaching and research.

Speakers

1. Sreenath Chalil Madathil

   State University of New York at Binghamton

   Assistant Professor
   Systems Science and Industrial Engineering

   An industrial engineering researcher focused on solving healthcare, energy, and manufacturing domain problems using operations research, simulation, and data analytics. I am interested in applied research problems.

2. Dr. Md Fashiar Rahman

   University of Texas at El Paso

   Dr. Md Fashiar Rahman currently serves as an Assistant Professor within the Department of Industrial, Manufacturing, and Systems Engineering (IMSE) at The University of Texas at El Paso. He obtained his Ph.D. and M.S. degrees in Computational Science in 2021 and 2018, respectively. Dr. Rahman's professional journey has been marked by substantial contributions to image data mining, machine learning, and deep learning within the realms of industrial and healthcare applications. His research expertise encompasses data analytics, computer modeling and simulations, artificial intelligence in healthcare, smart manufacturing, computational intelligence, and advanced quality technology.

3. Michael Pokojovy

   Old Dominion University

   Old Dominion University