Projects · Products · Analytics Solutions Center

Things I build, and ship.

An iPhone app, a company, a research ledger, tools for students, and the industry projects I mentor. Open any plate for the story and the screenshots.

§ 01 — Products & tools

01 · iPhone app · App Store 2026 Eisenhour Eisenhower matrix, by the hour. A local-first daily planner that turns decisions into scheduled hours. No account, no subscription, no tracking. Open →
PAD Renovations PAD Renovations
02 · Company · Utah, 2026 PAD Renovations One call, one price, one guarantee. An AI operating layer for residential contracting, and my own company. Open →
03 · Research tool · paper trading Hunt Ledger A paper-trading book for a monthly research hunt, rebalanced from a CSV and marked against SPY. Not investment advice. Open →
04 · For students · web app DAIS Resume Studio AI-assisted resume coaching for Huntsman DAIS students: review, queue course projects, rebuild in the department template, with the instructor in the loop and nothing stored. Open →
05 · Teaching · 16 tools Interactive teaching tools Random walks, stationarity, SARIMA, bias and variance, gradient descent, a neural network that trains live in the browser. No install, no account. Explore →
06 · Open source · GitHub Course materials Notebooks, code and exercises for Machine Learning in Economics and Finance, Deep Learning, Deep Forecasting and Python for Data Science. github.com/PJalgotrader ↗

§ 02 — Analytics Solutions Center

Project mentor · ongoing · huntsman.usu.edu/asc

Industry projects, student teams

Mentoring student teams on industry-sponsored analytics projects through USU’s Analytics Solutions Center, spanning finance, healthcare, retail, and government — hands-on experience solving real business problems with machine learning.

Project areas

  • Predictive modeling and analytics
  • Data visualization and dashboard solutions
  • Machine learning and deep learning applications
  • Forecasting tools and automation
  • AI solutions and intelligent systems

Focus areas

Where the work sits

Machine learning and deep learning, applied across financial markets, algorithmic trading strategies and economic analysis, grounded in industry experience from BlackRock.

Time series forecasting, from ARIMA and exponential smoothing through LSTMs, RNNs and transformers, applied to market prediction, economic forecasting and risk.

Building software with AI in the loop: the products above share a stack (Expo, Next.js, Supabase, Vercel, Cloudflare, Claude Code) and a rule: keep the user’s data on the user’s device where possible, and ship.

§ 03 — Publications

Scholarship of practice

Applied over archival

As a Professor of Practice, my focus is applied teaching and industry collaboration rather than traditional academic research. My scholarly work emphasizes practical applications of machine learning in finance and the development of open educational resources.

Google Scholar profile ↗