I'm currently working as an Assistant Professor in the Computational Data Sciences Department at George Mason University Korea, where I teach several courses related to data science and conduct research on applied AI for a variety of medical and biomedical problems.
These days, I'm tinkering with automated machine learning experiments (e.g., Autoresearch) for computer vision and working on several applied AI projects in biopharmaceuticals and medical and biomedical imaging. I'm also interested in fundamental machine learning problems related to spurious correlations, robust predictions, and interpretable AI.
If you are working on related topics -- especially pharmaceutical applications (quality control, sub-visible particles, vial inspection, and similar topics) -- and are looking for someone with strong coding, visualization, and AI experience, feel free to reach out.
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spur-breast
Repository for our MICCAI 2025 paper on creating a dataset to investigate spurious correlations in breast-tumor detection. -
svp-generative-ai
Repository for our work on using generative AI for pharmaceutical quality control, focusing on sub-visible particles in flow-imaging microscopy. -
pytorch-simple-diffusion
A minimal, introductory repository demonstrating a bare-bones diffusion implementation.
Thanks for stopping by! If you are curious about something, feel free to send an email.


