I am a research fellow with the Department of Radiation Oncology at Mayo Clinic, Rochester, Minnesota. My current work focuses on improving motion management in our proton therapy practice with real-time fluoroscopic imaging. To this end, I develop in-house clinical software, and conduct research on reliable tumor-tracking with computer vision / deep learning methods.
Previously, I studied nanoconfined polymer electrolytes for safer rechargeable lithium-ion batteries at Brookhaven National Laboratory, via synchrotron X-ray scattering experiments carried out at the Advanced Photon Source and the National Synchrotron Light Source II.
I enjoy solving scientific/quantitative problems with 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.
CAMPEP-accredited Certificate Program in Medical Physics, 2018–Present
Ph.D. in Mechanical Engineering, 2015
University of Colorado Boulder
B.E. in Materials Science and Engineering, 2010
To augment our proton facility vendor’s hardware with the capability of fluoroscopy-based motion verification and monitoring, I …
Accurate delivery of radiotherapy dose is predicated upon careful motion management. This is particularly true for spot-scanned proton …