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Fink692/README.md

Charles Backman

I build apps, AI tools, and research software. My work spans native mobile development, local AI, browser-agent tooling, and reproducible machine-learning experiments.

Based in Winnipeg, Canada. I also lead an AI club at St. John's-Ravenscourt, teaching students and teachers to turn ideas into working software.

R茅sum茅 路 Project catalog 路 Writing 路 Email

Selected work

Project What I built Explore
Evidence Board A research workspace with source-linked claims, ten browser-agent tools, reviewable proposals, and undo. The public sample uses illustrative data. Code 路 Demo 路 Tool contracts
Context An offline relationship-memory app with reviewed imports, optional on-device AI, and native iOS bridges. Code 路 Screenshots 路 Privacy
BlockScore Founder and product lead of a five-person team building a SwiftUI app for Canadian address research. Reports show sources and coverage; the app is in development and source is private. Public data companion
Project Hope A charity operations platform with a desktop sample, contact migration, organization permissions, and local AI assistance. Real team use requires a hosted workspace. Code 路 Website and downloads
WildGap A biodiversity survey tool using H3, GBIF, and weather data to identify observation gaps and plan field missions. Code 路 Demo
Clearcoat Quote Studio A vehicle-photo quoting MVP with browser quality checks, deterministic pricing, and human-review routing. Code and screenshots

Research

  • AgriStress: co-founder and lead developer of a multispectral stress-mapping research platform. Working with University of Manitoba Plant Sciences researchers to incorporate longitudinal wheat and canola drone imagery. Research prototype; code is private.
  • Quant Systems Lab: chronological order-book replay and independently checked accounting. The published study processes 301,587 messages; all five policies lose money on the sample. Study.
  • UFC Predictor: pre-fight features and probability evaluation. The recorded chronological benchmark reports 63.55% accuracy on 1,709 held-out fights. This is a historical result, not live betting performance. Results.

More work includes municipal-data tools, accessibility testing, adaptive-model research, engineering simulation, and business software. See the full catalog for status and evidence.

How I work

I use AI coding tools throughout development. I set the product direction, review changes, and test the result. I care about source provenance, useful interfaces, and making failure cases visible.

Languages: Python, TypeScript, Swift, Java
Tools: React, React Native, Next.js, Django, FastAPI, NumPy, scikit-learn, PyTorch, Playwright, GitHub Actions

Background

Honours student at St. John's-Ravenscourt, graduating in June 2027. My experience includes product strategy, research, teaching, and running a commission-based resale business.

IBM SkillsBuild Artificial Intelligence Fundamentals certification. Second place in an RRC Polytech business competition.

Last reviewed: 12 October 2026. Project links distinguish working samples, research, and unfinished releases.

Popular repositories Loading

  1. Quant-Research-Lab Quant-Research-Lab Public

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  2. ufc-predictor ufc-predictor Public

    Leakage-safe UFC winner prediction pipeline with stamina-aware rolling features

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  3. context-memory-aid context-memory-aid Public

    Private, offline-first relationship memory for iOS, Android, web, and macOS with optional on-device AI.

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  4. quant-systems-lab quant-systems-lab Public

    Auditable Python quant-research platform centered on real-data queue-aware market making, chronological evaluation, reproducible reports, and 195 tests.

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  5. Fink692 Fink692 Public

    GitHub profile README showcasing quantitative finance projects

  6. public-procurement-transparency-engine public-procurement-transparency-engine Public

    Python