I'm a PhD student studying under Dr. Ross Beveridge.
My work focuses on understanding convolutional neural network (CNN) feature spaces. Most recently, we have learned that face recognition models converge to the same outputs after rotation, even when those models don't share training data or CNN architecture. This research has been applied in the DARPA Active Interpretation of Disparate Alternatives (AIDA) program.
Previously, I contributed to the DARPA Communicating with Computers (CwC) program, which focused on DIANA, an intelligent avatar described here.
I also help with Kat McNeely-White's research in various ways, most recently building a tool for running MINERVA2 memory simulations.
I apply computer vision techniques to improve the experience of Amazon customers in collaboration with a cross-disciplinary team of scientists and engineers. Most recently, this involves exploring the use of self-supervision and vision transformers on a massive dataset of images in a unique domain.
I co-developed, maintained, presented, and published a multi-modal virtual assistant named Diana. I focused on gesture recognition, user perception, and performance optimization (C#, Python 3, Unity engine, TensorFlow, MS Kinect, funded by DARPA CwC).
I collaborated with CU-Boulder and Brandeis Univ. on the creation of a multi-model embedding-based knowledge base for participation in the DARPA AIDA program. My chief contribution was the extension of my MS thesis work to facilitate cross-CNN face identification and correlation (Python 3, TensorFlow, Java).
Beyond grading, proctoring, and occasional lecturing, I taught small workshop-style labs and provided regular one-on-one instruction. The classes I assisted were intermediate C++ programming and advanced DBMS. At the end of the first class, one particular student told me they “couldn’t have done it without me.”
I defined, designed, developed and maintained a web app for managing child participants and associated parents for the purpose of conducting childhood development research (C#, SQL, .NET/MVC, HTML/CSS/JS).
Working on a small, cross-functional, partially remote team, I co-developed adaptive web-based surveys for the purpose of improving patients’ medical outcomes (e.g. pain management, mobility). I was known as a powerhouse and always pushed for using modern design and development tools. While we all wore many hats, I particularly loved back-end optimization and refactoring (C#, SQL, .NET/MVC, HTML/CSS/JS).
I worked on multiple small teams developing console and web applications using .NET/MVC.
I maintained and expanded computational frameworks in support of computational physics research.
In the Material Science and Technology Department, I assisted with the development of scientific instruments, the processing and analysis of experimental materials, and the proposal and presentation of research (Article).
Coursework includes computer vision, machine learning, AI, and distributed systems.
Including most of a Chemical Physics degree.
My near-term goal is to work in industry solving problems using cutting-edge research and tools. I'm most interested in machine learning and computer vision, but I'm also excited by problems relating to high-performance, distributed systems.
When the weather is good, I enjoy camping and cycling here in Colorado, and restoring old motorcycles. Otherwise, you can find me tending to my many houseplants or gaming with my wife.