Sheet 00 · Cover
I am a computer science student at Colorado School of Mines, with a minor in Quantum Engineering. I work on computational protein design and on how AI agents behave when they work together. I graduate in May 2027 and plan to start a PhD in computational and systems biology that fall.
Sheet 01 · Blueprints
Growing up in Kalama, a small town in southwest Washington, I spent most of my free time helping with my family's construction business. I worked through every step of homes being built from the ground up and watched architects' blueprints turn into real structures. That is where I picked up an obsession with understanding complex systems, and it carried over into chemistry sets, electronics kits, and eventually code.
A protein, it turns out, is also a structure built from a plan. It is just .
Sheet 02 · Mines
I came to Mines to study computer science because I wanted to connect the digital world to the physical one. I added a minor in Quantum Engineering, and by my second year I was taking graduate courses in quantum information alongside my undergraduate classes.
I am finishing my degree in three years and have kept a 4.0 along the way.
When I am not at a keyboard, I am usually on the track: I pole vault for the Mines track and field team. It is a good reminder that plans only matter if you commit to the jump. I also lead the Society of Quantum Engineers as president, serve on the Student-Athlete Advisory Committee, and help run a campus wellness club as treasurer.
Sheet 03 · The pivot
My first research was in the Honors VIPER quantum materials course, searching computationally for new quantum materials. I enjoyed it, but I decided materials weren't the application I wanted to pursue. I wanted to write algorithms that produce something that could physically heal people. So I joined the Bioinformatics Club and started teaching myself structural biology.
The fastest way to learn was to enter the 2026 Mines Protein Engineering Competition, which ran for four months. The goal I chose was a protein that binds nitrogenase without shutting it down, as a first step toward cheaper nitrogen fixation.
Afterward, I generalized those pipelines into a beginner-friendly protein engineering pipeline and published it as open source, so other computer scientists can get into protein design with less setup than I had. It is always a work in progress.
Sheet 04 · Summer 2026
One summer, two communities: a lab at the University of Oregon, and the Rosetta Commons network of protein design labs that ran the program.
University of Oregon · Eugene
I spent the summer as a Rosetta Commons NSF REU researcher in Dr. Parisa Hosseinzadeh's lab, computationally designing cyclic peptides. I read through the literature, built design pipelines from scratch in Python, Bash, and RosettaScripts on the lab's computing cluster, and had candidates ready for wet-lab testing within five weeks.
My first designs had trouble reaching the binding pocket. Working around that problem ended up shaping the whole project, which is a pattern I keep running into.
The first designs are now being tested in the wet lab with collaborators, and I am still working with the lab remotely.
Rosetta Commons · RosettaCon 2026
At the end of the summer I gave a lightning talk and presented a poster at RosettaCon 2026.
Lightning talk + posterComputational design of FPR2-specific cyclic peptides for resolution of chronic inflammation
Earlier that year, at an APS conference, I felt like an outsider looking in. At RosettaCon, after months in the literature, I had long conversations at posters and over meals, and I finally felt like an equal in the scientific community.
Sheet 05 · Agents
Back at Mines, I reached out to Dr. Lincoln Carr and joined his group, where I study how communities of AI agents interact and what behaviors emerge when they do.
Protein design taught me what one model can do. This work is about what happens when many of them are connected, and it is a big part of why I am interested in AI safety and biosecurity research. The same tools that design proteins and coordinate agents deserve careful study.
Build log
The same story as a construction schedule. Dashed entries are planned, not finished.
Took dual-enrollment classes at three Washington colleges while finishing high school in Kalama.
Computer science, a Quantum Engineering minor, and the track and field team.
Joined the Honors VIPER quantum materials course and the AMBER air-quality group, and started taking graduate-level courses in quantum information.
Won the Mines Protein Engineering Competition and joined Dr. Lincoln Carr's group to study multi-agent AI.
Rosetta Commons NSF REU in the Hosseinzadeh Lab, then a lightning talk and poster at RosettaCon 2026.
Field session with Kirin Autonomy, still working with the Hosseinzadeh Lab, and getting ready to mentor first-generation students back home.
Three years after starting.
Computational and systems biology.
Parts list
A few things I have built, what problem each one was for, and what came out of it.
Getting started with protein design tools takes a lot of setup, especially coming from computer science.
Generalized my competition and research pipelines into an open-source starting point for newcomers.
View on GitHub →Targets over 2,000 residues did not fit in a home PC's GPU memory.
Cropped distant chains and capped the cut face with serine, bringing targets to about 600 residues.
Read the story →Designing cyclic peptides that act on one receptor and not its close relative.
Candidates in wet-lab testing; presented at RosettaCon 2026.
Read the story →A chess neural network that estimates a player's skill from their decisions.
Adjusts the AI's difficulty in real time; built during my senior field session.
Participants in an air-quality study across Colorado needed secure access to their own data.
Built user-facing Kotlin and Python applications for the Mechanical Engineering AMBER group.
My first research project: computational discovery of new quantum materials.
Where I learned research, and where I learned I wanted to work on biology.
This parts list gets longer every semester.
Sheet 06 · Giving back
I only found my way into research because people answered my emails. I try to return the favor.
Starting soon
Rural first-gen mentoring. I am working with my old high school's college counselor to mentor first-generation students interested in STEM or athletics, and I hope to bring in other Mines students to reach more rural schools.
Student Advisory Board for Quantum Programs
As an invited member of this multi-university board, I analyzed departmental data on undergraduates in graduate courses. Part of my experience was presented in the program evaluators' talk at the NSF NRT conference, and the board's mentorship proposals are now before faculty.
Planned, not done yet
A Rural Bio-Initiative for Kalama: science seminars and shared Colab notebooks on how medicines are designed and tested, so people at home can look at the data themselves.
Sheet 07 · What comes next
I graduate from Mines in May 2027 and plan to start a PhD in computational and systems biology in Fall 2027.
The question I want to work on: structure prediction can now tell us where a molecule binds a receptor, but not which signal that receptor sends afterward. I want to build models that connect binding to signaling for G protein-coupled receptors (GPCRs), so designers can select for the response they want rather than binding strength alone.
Coming from computer science, I also know what I cannot teach myself on a PC: designing wet-lab validation, formal structural biophysics, and the statistics to know when a prediction is real. That is what graduate school is for.
Long term, I want to be a professor who does research, mentors first-generation students, and makes science easier to access.
Sheet 08 · Contact
I am especially interested in cyclic peptide design and neurological pharmaceuticals, and in the long run I want to help build treatments for mental health diseases. If you work on any of that, or on protein design, multi-agent AI, AI safety, or biosecurity, I would be glad to hear from you. The same goes for first-generation students figuring out research.