I study the systems that matter — building at the intersection of secure software, intelligent automation, and the financial logic underneath it all.
I'm a Computer Science student with a minor in Finance, focused on where security and artificial intelligence intersect — because that's where the most interesting (and consequential) problems live.
My background in QA roles gave me something most CS students don't have: a deep instinct for how systems fail. I've spent time finding edge cases, automating test suites, and thinking adversarially about software — excellent training for both security work and building robust AI systems.
The finance minor isn't an accident. Understanding how capital flows, risk is priced, and markets behave gives technical work a layer of meaning — I'm drawn to fintech, algorithmic systems, and the infrastructure that underpins financial security.
Right now I'm learning, building, and looking for internship or co-op opportunities where I can contribute real work and keep growing fast.
Designed and maintained automated test suites covering 200+ test cases across the core API. Reduced regression cycle time by 35% by migrating manual flows to Selenium + PyTest. Documented and triaged 80+ bugs with detailed reproduction steps and severity classification.
Performed black-box and exploratory testing on a fintech web platform. Collaborated with dev team in Agile sprints, wrote test plans for new payment flows, and flagged a critical authentication bypass that was patched pre-release.
Assisted faculty research on adversarial machine learning. Implemented baseline attack models (FGSM, PGD) in PyTorch, contributed to literature review on robustness of image classifiers, and co-authored one internal technical report.
Real-time SSH intrusion detection tool that parses auth logs, detects brute-force patterns using a sliding-window algorithm, and sends alerts via Telegram bot. Built as a practical response to a CTF challenge that exposed a gap in common monitoring tooling.
Financial news sentiment classifier fine-tuned on FinBERT. Ingests RSS feeds from 12 financial sources, scores market-moving headlines in real-time, and visualises sentiment drift across sectors. Achieved 89% accuracy on held-out test set.
Lightweight end-to-end testing framework wrapping Playwright with a custom DSL for human-readable test specs. Integrates with GitHub Actions for automatic regression runs on every PR. Used internally across two academic group projects.
Command-line tool that pulls historical equity data via yFinance, computes Value-at-Risk using Monte Carlo simulation, and outputs a risk summary with Sharpe ratio, max drawdown, and correlation heatmap. Built to apply finance coursework to real data.
I'm actively looking for internship, co-op, and research opportunities in security, AI engineering, or fintech — especially roles where I can bring a QA mindset to building more robust systems.
If you're working on something interesting, have a role in mind, or just want to talk about adversarial ML or broken auth flows — my inbox is open.