John Hoffman

profile photo of john working at his computer(s)

[email protected]

Hello!

This website is largely an effort to archive and keep a record of my work, as well as a sort of business card for my experience. Please feel free to reach out if you'd like to collaborate or hire me for consulting work.

JMH - December 28, 2023

Websites

Research Interests

I'm an imaging and computer vision scientist currently working in the UCLA Department of Radiology! Much of my work is predicated on the idea that a CT scan is more than just a single reconstruction, and that with access to the raw projection data we can learn substantially more from CT imaging than we currently do. By using first principles and physics, we can begin to understand how information, rather than just pixel values, flows through the mathematical reconstruction operation, and how that determines the inherent reliability of a scan, particularly for use in quantitative imaging. We hope that by understanding this flow of information, we can predict which imaging features will be more or less reliable for clinical diagnostic purposes. We (as many others) are also looking to understand the coming roles that AI and machine learning can and will play in the days ahead, and also how we can improve AI performance to make it more suitable for clinical usage. In particular, we have begun investigating a "recon-in-the-loop" data augmentation strategy for AI, as well as some early investigations into automated phantom analysis trained using only synthetic models of the phantom; this continues into some explorations into manufacturing our own phantoms. We continue to expand this area of our research.

Computing

I personally am deeply interested in the computational details of all of the problems I work on and encourage my students to also dive deep to better understand these details. Computation lies at the core of modern medicine in every way (PACS, image viewers, scheduling, drug delivery, security of a hospital, CT image reconstruction, CT image acquisition, etc.) and impact not only the research that we do, but the real viability of certain techniques both for research and clinic. As with all science, through a better understanding our tools we gain access to new knowledge. My work has included GPU algorithm implementation with OpenCL and CUDA, CPU architecture-specific optimization, deployment of algorithms as services (server/backend deployment), low-level network programming for distributed computing, cloud development and deployment, and many other topics. I love seeing projects move from conception to deployment and start being used by real people. The hacker mentality of "crack it open and figure out how it works" runs deep.

Academics

Job Experience

Selected Publications

Selected Abstracts