Nice to meet you!

I am a medical physicist at the Department of Radiation Oncology at the University of Michigan.

My current research focuses on interpretable machine learning for modeling oncologic outcomes. I am also interested in big data infrastructure for clinical decision support and workflow automation.

Before moving to Ann Arbor, Michigan, I completed my residency training at the University of Pennsylvania, where I also served as the physics resident education officer.

My training in medical physics started at the Mayo Clinic, Rochester, Minnesota, where I completed a CAMPEP-accredited postdoctoral certificate program. While working as a research fellow there, I developed a GUI software application for real-time motion management for proton therapy. This custom tool, named Wukong, provides added assurance for internal tumor/target localization during setup and beam-on. It has been translated into clinical use as a standard operating procedure (SOP).

In my earlier basic science pursuit, I studied nanoconfined polymer electrolytes for safer rechargeable lithium-ion batteries at the Brookhaven National Laboratory, via synchrotron x-ray scattering experiments performed at the Advanced Photon Source and the National Synchrotron Light Source II.

I enjoy solving scientific/quantitative problems by programming. In particular, I am fluent in Python and familiar with its scientific eco-system (i.e. NumPy, SciPy, Matplotlib, LmFit, Mayavi, scikit-image etc.). I like readable, elegant NumPy vectorization solutions, but am also comfortable with extending Python via Numba or pybind11/C++ for numerical performance boosting. For larger coding projects, I use C#/.NET (LINQ is marvelous) and strive for robustness and maintainability through good software engineering principles.