Research
My current interests are image processing, deep learning, statistical shape modeling, mathematical optimization, medical image analysis, and machine learning theory.
- Statistical shape modeling: particle-based and RBF-based representations for anatomical shape analysis, including methods that work from images and support arbitrary regions of interest.
- Medical image analysis: deep learning for quality assessment and automated screening in cryo-EM and related imaging pipelines.
- Image processing & deep learning: algorithms and models for imaging problems, including settings with limited data or labels.
- Mathematical optimization: optimization-driven approaches to shape modeling and related learning problems.
- Machine learning theory: theoretical foundations of learning algorithms and models.
A full list of papers is on the publications page. Google Scholar is the most up-to-date source. Software and other efforts appear under projects.