Principal Investigator
AI/Hub, Durham College
2019 - Present
AI Hub is an applied research centre within Durham College that helps public and private organizations solve real problems with data, machine learning, and automation. Projects pair industry partners with faculty and student researchers to design prototypes, validate approaches, and transfer solutions into production settings.
Responsibilities
- Scoped projects, wrote grant proposals, and managed over $350 000 in research funding.
- Presented findings to executives with an emphasis on practical impact.
- Built data pipelines with and trained ML models.
- Facilitated design-thinking sessions and converted business challenges into user stories.
- Mentored student researchers while maintaining code-review and Git-flow standards.
Key Projects
AI-Driven Email Automation System
2025
Designed and implemented an AI-powered outreach workflow for a craft brewery to automate retailer targeting and personalized email drafting within Ontario’s distribution rules.
Built an n8n-based pipeline integrating QuickBooks, Google Sheets, and Gmail to score and select stores, generate AI-assisted drafts with human review, and track campaigns. Standardized store records with geocoding and added tracking fields, delivered a phased implementation roadmap with safeguards (structured prompts, low-temperature settings, privacy), and validated a low-cost path to scale.
Home-Care Voice Assistant
2020
Prototyped an interactive voice bot that helps nurses complete routine patient check-ins more efficiently.
Home-care nurses were spending significant time on routine calls, so in collaboration with clinical stakeholders we designed a conversational assistant that captures key health indicators and escalates when required. A pilot showed a 22 percent reduction in call duration while maintaining positive patient feedback, and nurses appreciated reclaiming time for direct care.
Smarter Car-Buyer Targeting
2019 - 2020
Delivered a machine-learning model that identifies online shoppers most likely to purchase a vehicle in the near term.
Sales teams were investing valuable time in leads that rarely converted, so by analyzing historic CRM and web-analytics data we produced a propensity model that highlights genuine purchase intent. Qualified lead volume rose 22 percent and average deal closure occurred five days sooner, with sales managers providing feedback that informed ongoing tuning.