Python
genus: languages
collected: 2022
status: thriving
The observer
I'm a computer science graduate (Brock, Honours '26) who never learned to stay in one lane. In four years I've trained computer-vision models on 43,088 hand-annotated objects, compressed one until it ran in 1.5 milliseconds on edge hardware, parallelized convolutions across threads and machines, shipped an iOS app on a serverless backend, and taught AI to do a mortgage brokerage's paperwork — 230 hours of it a year.
The method never changes: find a field I haven't touched, read everything, build something real, measure it honestly. My degree gave me the fundamentals; the rest — CUDA and TensorRT, Cloudflare Workers, SwiftUI, agentic AI workflows — I taught myself because a project demanded it.
And the entrepreneurial part isn't a side note: I co-founded RentSwipe and run its engineering, because finding the problem and shipping the fix is the whole point. (Before all of this I supervised lifeguards. I stay calm when production goes down.)
Specimen collection
skills, collected in the field — each one picked up because a project demanded it
PyTorch & OpenCV
genus: machine learning
collected: 2024
status: flowering
TensorRT · ONNX · CUDA
genus: edge inference
collected: 2024
status: blazing
TypeScript & Workers
genus: serverless
collected: 2025
status: shipping
Swift & SwiftUI
genus: mobile
collected: 2025
status: established
C & C++
genus: systems
collected: 2022
status: hardy
OpenMP & MPI
genus: parallel computing
collected: 2025
status: multiplying
SQL · D1 · Postgres
genus: data
collected: 2023
status: well-indexed
NB: collection grows
every season
Notable experiments
IN
PRODUCTION
PRODUCTION
Four AI pipelines for a mortgage brokerage
My current role: I designed, built, and now operate four production pipelines — document intake, email drafting, commitment monitoring, and anniversary reporting. They read real client paperwork, validate it against schemas, cross-check the CRM, and draft outputs a human approves. Together they save the brokerage 230+ hours a year. Debugging OAuth, parsing, and duplicate-run failures in production taught me more than any course.
MATERIALS: TypeScript · Cloudflare Workers · Microsoft Graph · SharePoint · Zoho · Finmo · Claude
saves 4.5 hrs of
paperwork a week
85×
FASTER
FASTER
Computer vision at 1.5 milliseconds
An end-to-end small-object detection workflow I owned from data preparation to deployment: 25 classes, 43,088 annotations, and 30+ training iterations per model of ablation-style tuning. Then the fun part — exporting to ONNX and building a TensorRT FP16 engine that cut inference from 127.8 ms to 1.5 ms while holding accuracy, after proving INT8's accuracy drop wasn't worth the trade.
MATERIALS: Python · PyTorch · OpenCV · ONNX · TensorRT · CUDA
127.8 → 1.5 ms.
still love saying it
CO-
FOUNDED
FOUNDED
RentSwipe
The venture: apartment hunting, but swipeable. I built the whole stack — a SwiftUI iOS app on a Cloudflare Workers backend, JWT sessions with role-based access control, and an indexed D1 (SQLite) persistence layer for users, listings, applications, and messages. Plus a trust-and-safety messaging system — block/report workflows, content enforcement, rate limiting — designed for App Store compliance from day one.
MATERIALS: Swift · SwiftUI · Cloudflare Workers · D1 (SQLite) · JWT / RBAC
finding the problem
is half the job
3RD
OF 40
OF 40
Code similarity detection platform
A plagiarism-detection engine for programming courses. I built the C/C++ similarity core — tokenization, normalization, template subtraction, fingerprinting, and Greedy String Tiling — to catch structurally similar submissions, then wrapped it in asynchronous analysis with anonymized, side-by-side reporting. Placed 3rd of 40 teams in the course's competitive evaluation.
MATERIALS: C · C++ · Greedy String Tiling · async pipelines
template subtraction
was the trick
INDEX OF FURTHER EXPERIMENTS
- Fast 2D convolution via FFT OpenMP ~2.38× speedup · MPI halo exchanges · parallel computing 2025
- Customer churn classifier interpretable end-to-end decision-tree pipeline · neural networks 2024
- Supervising instructor guard three summers keeping humans alive · Norfolk County pools 2022–25
Write to the field
Hiring? Building something interesting? Want to trade notes on ML, serverless, or shipping things that work?
— write to me. I read everything.
Ty