Yejin Kim,PhD is an Assistant Professor at McWilliams School of Biomedical Informatics at UTHealth Houston. She received her Ph.D. in Computer Science from POSTECH, South Korea, where she focused on machine learning for healthcare. Her current research interests include counterfactual machine learning and human-centered machine learning for healthcare. She has also been recognized for her outstanding contributions to research and received several awards from NIH R01, Robert Woods Johnson Foundation (HD4A award) and being selected as the top 10% most cited PLoS One paper. Her work has been covered in public media outlets such as CNN, NPR, and ScienceDaily. She has served on various grant review panels and committees, including the National Institute of Health, UK Research and Innovation, Luxembourg National Science Foundation.
- Tell us about your research center and/or what research/work you are currently working on?
My current research topic is building machine learning models for healthcare, with specific application on Alzheimer's disease. I'm focusing on counterfactual machine learning, graph representation learning, and large language models.
- What type of student or Postdoctoral Fellow are you looking for to work in your center?
I'm looking for Ph.D students and postdoc with strong background in computational field to work on applied machine learning.
- What does the future of your research look like?
Future of my research will be more human-centric so that machine learning can be seamless integrated into real-world challenges.
- What does the future of informatics look like?
So far developing novel methodology was the mainstream, but in the future asking right question and targeting right problem would be the key to success
- What courses do you teach?
BMI 5007 Methods in Health Data Science: Introduce health data science, briefly touch whole pipeline of data science (from data acquisition, wrangling, analysis, to visualization)
- What major UTHealth Houston departments/institutes do you collaborate with?