Cybersecurity Incident Alert & Response Platform – Power Apps
Associated with Dilico Anishinabek Family Care
Oct 2025
Developed a security-focused emergency communication system used to notify staff during phishing attempts, suspicious email activity, network outages, and other incidents. Integrated with Azure AD, SharePoint, Power Automate, and Twilio to automate alerts through Call, SMS, Teams, and email.
Phishing Simulation & Training Program
Associated with Dilico Anishinabek Family Care
Sep 2025
Designed and executed a full phishing-simulation campaign to strengthen organizational security. Built a custom HTML phishing email and branded landing page, configured follow-up notifications, and used Microsoft Defender Attack Simulation to track engagement. Integrated automated training modules for users who clicked the simulated link, boosting detection and reporting rates.
Duo Security Bypass-Code Automation
Associated with Dilico Anishinabek Family Care
Aug 2025
Designed and deployed a Power Automate + Microsoft Copilot Studio workflow to automatically generate and deliver Duo Security bypass codes for internal testing and emergency access.
Integrated with Active Directory and internal approval logic to streamline temporary MFA overrides while maintaining full audit logs.
Reduced manual help-desk workload and improved response time for urgent access requests.
IT Help Desk Automation (Copilot Studio Chatbot)
Associated with Dilico Anishinabek Family Care
Jul 2025
Designed and deployed a Microsoft Copilot Studio chatbot to automate routine IT support requests (password resets, ticket creation, Duo bypass-code retrieval, and knowledge-base queries).
Integrated with Microsoft 365, Azure AD, and Service Desk for real-time ticket updates and user authentication.
Implemented Python and Power Automate scripts to extend functionality and provide dynamic responses.
Benchmarked the Copilot solution against ManageEngine Zia, improving first-response time and reducing help-desk workload by over 40%.
Intelligent Video Learning Dashboard (AWS + Flask + NLP)
Associated with Lakehead University
Feb 2025 – Mar 2025
This project is an end-to-end pipeline for building an interactive video learning dashboard powered by AWS and NLP. It allows students to explore course videos via searchable transcripts, topic modeling, and key phrase extraction, with a clean, Flask-based interface deployed on EC2 Ubuntu.
Big data analysis using Hadoop and Apache Spark
Associated with Lakehead University
Aug 2024 – Dec 2024
Processed 145,460 records from CSV files, focusing on the 5Vs (Volume, Velocity, Veracity, Validity, Visualization). Utilized Hadoop for clustering and Spark for analytics and machine learning predictions.
Machine Learning Models for Early Detection of Fetal Distress
Associated with Lakehead University
Aug 2024 – Dec 2024
Objective: Develop predictive models for the early detection of fetal distress using machine learning techniques.
Implemented Algorithms: Gradient Boost, Decision Tree, Random Forest
Programming Language: Python