Yejin Kim
Associate Professor (tenured)
Houston, Texas, United States
Summary
👤
Senior🎓
Top SchoolYejin Kim is a tenured associate professor and machine learning researcher in Houston with nine years of experience applying multimodal and temporal ML to healthcare, specializing in subject segmentation and causal inference for treatment effect analysis. She has led NIH-funded projects and interdisciplinary teams to develop tensor/matrix factorization, recurrent and graph neural network models that revealed disease subtypes and improved clinical trial targeting. Her work spans from federated and interpretable tensor methods to causal trees and Bayesian networks, with measurable translational outcomes such as identified subtypes that increased trial success prospects and a $3.9M grant. A pragmatic coder and mentor, she bridges academia and deployment using PyTorch, causalML, and clinical data pipelines, and she has a track record of organizing datathons and mentoring trainees. Notably, she has delivered recommender systems and privacy-preserving factorization techniques, demonstrating a rare blend of deep theoretical methods and real-world clinical impact.
9 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science (Machine learning), 3.89/4.3, Doctor of Philosophy - PhD, Computer Science (Machine learning), 3.89/4.3 at Pohang University of Science and Technology
English, Korean
Github Skills (4)
validation6
deep-learning4
visualizer2
medical2
Programming languages (2)
Github contributions (5)
yejinjkim/seq-div-rec
May 2019 - Feb 2020
Contributions:6 commits, 5 pushes, 1 branch in 9 months
yejinjkim/drug-repurposing-graph
Aug 2020 - Apr 2022
Code repository for "Prioritizing Repurposable Drugs for SARS-CoV-2 using Deep Learning and Population-based Validation"
Contributions:7 commits, 1 PR, 2 pushes in 1 year 8 months
drugsvalidationdeep-learningcode-repositorysars-cov-2
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