ML and Cybersecurity Research Hub
ML-enabled applications and cybersecurity research delivered across multiple client engagements.
Impact
Improved engagement by 50% across deployed apps
Boosted model accuracy by 35% for analytics workflows
Delivered 10+ client projects on time
Established ML evaluation baselines for future releases
Improved security posture by 15% across assessed systems
Improved collaboration efficiency by 20% across client teams
Metrics
What we built
A portfolio of ML and security solutions built for clients in healthcare, sports, and media, blending research with production delivery. Each engagement shipped modular ML services, production-ready APIs, and UX improvements with clear success metrics.
Challenge
Clients required ML-driven features, robust security, and measurable engagement improvements across varied products and timelines. Data quality and model performance needed to be balanced with delivery deadlines.
Solution
Delivered modular ML services, responsive front ends, and security tooling using IoT devices and tuned ML pipelines. Established evaluation workflows to track accuracy, latency, and engagement impact.
Responsibilities
- Architected ML-enabled web and mobile experiences end to end
- Trained, evaluated, and optimized ML models for client data
- Built security tooling and evaluation pipelines
- Owned delivery across multiple client engagements and timelines
- Collaborated with stakeholders to define measurable KPIs
- Built IoT security prototypes using Raspberry Pi and WiFi Pineapple
- Assembled digital forensics tooling with Dickey
Technology stack
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