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CTO @OpenAdaptAI | Principal AI Engineer @ziggiz | ML Consultant | AI systems for automation, security, and unstructured data | MASc UofT · Mila admit (deferred)
I identify and solve valuable problems by building industry-leading software, products, and teams, including: - An agentic web app for a global software giant that detects documentation errors with superhuman speed and accuracy - A neurological disorder diagnostic aid for a global top hospital (acquired) - A human-in-the-loop roof damage estimation system for a top-10 US insurance carrier ($20M in yearly savings) - A content recommendation system for a Silicon Valley mobile app unicorn - The medical device industry's first 3D liver section image segmentation system My job is to: 1. Identify customer & stakeholder pain points via customer discovery 2. Design and carry out experiments to validate commercial and technical hypotheses 3. Define requirements and budgets for Minimum Viable Products 4. Build and lead teams and products that leverage state-of-the-art technologies at scale
Université de Montréal
Doctor of Philosophy - PhD (deferred), Computer Science
September 1, 2013 – September 1, 2013
University of Toronto
M.A.Sc., Computer Engineering
January 1, 2011 – January 1, 2013
University of Toronto
B.A.Sc., Computer Engineering
January 1, 2006 – January 1, 2011
ziggiz
Principal AI Engineer
November 1, 2024 – Present
OpenAdapt.AI
Founder & CTO
May 1, 2023 – Present
Tribe AI
Machine Learning Consultant
March 1, 2022 – Present
A.Team
Machine Learning Consultant
November 1, 2021 – Present
Remote
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Kindred.ai
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RBC Capital Markets
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July 1, 2013 – January 1, 2015
Toronto, Ontario
University Health Network
Software Developer
May 1, 2009 – December 1, 2014
Toronto, Ontario
ES Computer Training & Technologies
Software Developer
May 1, 2007 – September 1, 2011
Newmarket, Ontario
Boosting with Perceptrons and Decision Stumps
September 1, 2011 – December 1, 2011
Empirical study of four different boosting algorithms and two families of weak classifiers on three datasets. Using this data, we try to evaluate the parameters for the weak classifiers, as well as the advantages of the different types of boosting algorithms.
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background working across startups, large corporations, and consulting firms, indicating adaptability to various organizational cultures. Their experience in leading teams and working on open-source projects (OpenAdapt.AI) suggests a collaborative and innovative mindset. However, the target role is 'Data Analyst', while the candidate's experience is heavily skewed towards 'AI Engineer' and 'Machine Learning Consultant'. This might indicate a potential mismatch in the depth of hands-on data analysis (e.g., statistical modeling, business intelligence tools) versus AI/ML model development and deployment. While they have strong data pipeline experience, the core focus of a Data Analyst role might require a different emphasis.
Soft Skills & Operational Fit
The candidate's experience as a Founder & CTO, Principal AI Engineer, and various consultant roles indicates strong leadership, problem-solving, and client-facing communication skills. Their involvement in guild leadership and sales discovery calls further supports their operational fit for collaborative and strategic roles. The descriptions suggest a proactive and results-oriented individual.