02About
About
I build secure backend software and applied ML systems for operational and financial workflows.
Python is where most of my work happens: applied machine learning, quantitative research, and the backend systems that make both usable. I am an Engineering Science student at the University of Toronto, specializing in Machine Intelligence and Mathematics, a Schulich Leader Scholar, and a Software Engineering Intern at Northstar Downhole Specialists.
At Northstar I work in Python across the lifecycle of OdooRedo — application development on Django and PostgreSQL, Documents and IPR workflows, role-based access control and audit trails, rollback-safe data migration, automated verification, CI, and AWS infrastructure provisioned with Terraform.
My applied ML work spans PyTorch CNNs for RF-signal classification at the Royal Military College of Canada and synthetic-data, clustering, and autoencoder prototypes with UTMIST and Flybits. My quantitative work covers portfolio-risk modeling, regime detection, stress testing, and an event-driven Rust trading engine.
Publicly, that comes out as an LLM evaluation platform, a live incident-triage demo, a leakage-aware market-regime and portfolio-risk platform in Python, a deterministic Rust matching engine, and the released FormatClip Chrome extension.
- Software Engineering
- Machine Learning
- Quantitative Research
- Reliable AI
- Systems Programming
- 7Project and research records
- 10Work experiences
- 3Public demos and releases
- 150KLargest research dataset, in samples
Education
Bachelor of Applied Science (BASc), Engineering Science
University of Toronto · Toronto, Ontario
Sep 2025 – Expected May 2029
Pursuing a BASc in Engineering Science with concentrations in Machine Intelligence and Mathematics, alongside project work in reliable AI, quantitative risk, and systems software.
- Concentrations
- Machine Intelligence, Mathematics
- Distinction
- Schulich Leader Scholar
- GPA
- 3.56 / 4.00Current GPA as of the August 2026 source set
- Selected coursework
- Data Structures & Algorithms, Probability & Statistics, Linear Algebra, Calculus, Python/C computing, MATLAB
Leahurst College
Ontario Secondary School Diploma · 2022 – 2025
- Maxima Cum Laude
- 95%+ academic average
- Six-time school champion in University of Waterloo competitions
- Governor General's Academic Medal
Recognition
Jul 2025
Schulich Leader Scholarship$120,000
Awarded a $120,000 Schulich Leader Scholarship in support of undergraduate STEM study.
Jun 2025
Governor General's Academic Medal
Received the Governor General's Academic Medal upon completing secondary school.
Jan 2023
Perfect Score — Beaver Computing Challenge
University of Waterloo
Earned a perfect score in the Beaver Computing Challenge.
Certification
Economic Fundamentals for Leadership
Fraser Institute · May 2026
Completed the Economic Fundamentals for Leadership certificate course issued by the Fraser Institute.
Technical Focus
- Python for applied ML
- Python, PyTorch, scikit-learn, XGBoost, NumPy, Pandas, Model evaluation, Time-series validation
- Backend and cloud platforms
- Python, FastAPI, PostgreSQL, REST APIs, AWS, Terraform, Docker, Django
- Quantitative research and risk
- VaR, Stress testing, Efficient-frontier optimization, Market regimes, Transaction costs, Portfolio P&L
- Systems programming
- Rust, Event-driven design, Deterministic replay, Property tests, Golden tests, Reproducible benchmarks
Skills
- Languages
- Python, Rust, C, C++, SQL, TypeScript, JavaScript, Java, MATLAB
- ML & Data
- PyTorch, scikit-learn, XGBoost, NumPy, Pandas, CNNs, Clustering, Autoencoders, GMM, HMM, KMeans, Model evaluation, Synthetic-data pipelines, Time-series modeling, Time-series validation, Leakage-aware validation
- Backend & Web
- FastAPI, Django, PostgreSQL, REST APIs, Pydantic, Alembic, Next.js, React, Streamlit
- Cloud & Delivery
- AWS, ECS, RDS, S3, SES, ALB, WAF, Terraform, Docker, GitHub Actions, CI/CD, Vercel, Google Cloud Run
- Testing & Quality
- pytest, Playwright, Ruff, CodeQL, Criterion, Property-based testing, Integration testing, End-to-end testing, Synthetic load testing, Benchmarking, Git, GitHub
- Quantitative
- Probability and statistics, Value at Risk, Stress testing, Efficient-frontier optimization, Portfolio optimization, Portfolio P&L, CAPM, Yield curves, Bond-pricing fundamentals, Options-pricing fundamentals, Transaction costs, Market-regime modeling
- Signals & Embedded
- RTL-SDR, RF spectrograms, Signal classification, Embedded ML inference
How I Work
Typed contracts over loose model output.
Incident Triage validates structured responses across Next.js and FastAPI before rendering. Incident Triage Copilot
Evaluation gates before model changes ship.
EvalOps checks pass rate, score, estimated cost, and p95 latency across versioned evaluation runs. LLM EvalOps
Temporal safeguards in quantitative research.
Market Risk uses chronological splits, train-only scaling, shifted signals, and future-mutation tests. Market Regime & Risk
Determinism before optimization.
The Rust engine uses deterministic JSONL replay, golden scenarios, and property tests before comparing benchmarks. Event-Driven Trading Engine
Explicit privacy and failure boundaries.
FormatClip stores snippets locally and sends selected text only after an explicit Format action. FormatClip
Metrics keep their methodology.
RF results retain their unseen-signal and approximation qualifiers, and Northstar latency stays scoped to a synthetic workload. RF Signal Classification
Selected Journey
Jun 2026 – Present
NorthstarSoftware Engineering Intern
Feb 2026 – Present
UTEFAPortfolio Manager
Sep 2025 – Aug 2026
UTMIST / FlybitsMachine Learning Engineer
May 2025 – Sep 2025
Royal Military CollegeMachine Learning Researcher
Sep 2025 – Apr 2026
UTEFASales & Trading Analyst
Volunteering
Sep 2022 – Jun 2025
Leahurst College
Math Tutor
Provided mathematics tutoring and adapted explanations and practice to individual student needs.
May 2023 – Jul 2023
Kingston Yacht Club
Sailing Instructor · Kingston, Ontario, Canada
Helped teach sailing skills and safe on-water practices to approximately 10–20 sailors.
Interested in reliable software, applied ML, or quantitative systems?
I am open to internship, research, and collaborative opportunities where careful engineering and measurable evidence matter. Open to software engineering, machine learning engineering, quantitative development and research, and research-engineering opportunities.