SangHyuk Kim
Investigating Medical Imaging + Systems Programming
[google scholar] [github] [sanghyuk.kim001@umb.edu]
Hello. I am Sanghyuk Kim, a Ph.D. student in Computer Science at the University of Massachusetts Boston, working under the guidance of Prof. Daniel Haehn in the Machine Psychology Lab. My research bridges medical imaging and systems programming to drive innovative advancements in healthcare diagnostics.
Before my Ph.D., I gained over four years of professional experience in software engineering, specializing in graphics kernel development for Unix/BSD operating systems. This background now underpins my interdisciplinary focus on leveraging low-level systems software for healthcare applications, notably in melanoma detection.
My work explores the intersection of:
- Machine Learning with Uncertainty Quantification: Developing pipelines that enhance diagnostic reliability in medical imaging. Recent work on melanoma detection achieved a 40.5% reduction in misdiagnoses, presented at IEEE ISBI 2025.
- Medical Imaging and AI for Healthcare: Leveraging systems programming to improve imaging diagnostics and reduce risks associated with AI hallucinations in critical settings.
- Kernel-Level Programming: Creating robust solutions like graphics kernels to improve cross-platform operability and efficiency, now applied to cutting-edge research in healthcare.
Currently, I’m investigating new methods to combine machine learning with systems programming, aiming to enhance medical imaging reliability and expand the frontiers of healthcare technology.
I'll be attending IEEE ISBI 2025 (Houston, TX, USA). Feel free to connect!