Curriculum Vitae

Honours Bachelor of Science (H.BSc) in Computer Science and Statistics

Awards: University of Toronto Scholarship (2020-21 Fall/Winter Session)

IBM Canada WatsonX Bob Core

• Built full-stack dashboards with React, TypeScript, and Node.js, improving AI model evaluation efficiency by 40%.
• Fine-tuned and evaluated 100+ large language models (LLMs) across multiple enterprise domains.
• Designed interactive UIs to visualize 50K+ model metrics, enabling faster and more accurate performance comparisons.
• Developed secure, scalable backend services following IBM's Carbon Design System and internal compliance standards.
• Utilized LLM-assisted tools to accelerate development cycles by 25% and enhance testing coverage.
• Coordinated product strategy and feature roadmap for AI model evaluation platforms, aligning technical goals with user needs.

IBM Canada WatsonX Code Assistant

• Defined product vision and roadmap for internal AI model evaluation and fine-tuning platforms.
• Facilitated sprint planning and cross-functional communication, improving delivery speed by 20%.
• Collaborated with AI researchers, engineers, and design teams to align development priorities with user needs.
• Collected and analyzed feedback from 50+ enterprise users to guide feature design and usability improvements.

University of Toronto - CSC309 Programming on Web, CSCC01 Software Engineering

• Conducted tutorials and supported students in understanding course material.
• Collaborated with colleagues to ensure alignment with course objectives.
• Facilitated student engagement through interactive communication platforms.
• Evaluated student work and contributed to fair assessment practices.

MintC. Proverbs Auction

• Built responsive front-end components with React and JavaScript.
• Developed back-end APIs using Django and integrated PostgreSQL/MySQL databases.
• Streamlined data queries with GraphQL and secured data with RSA and AES encryption.
• Conducted automated QA testing, reducing downtime by 30%.

• Trained CNN models (VGG19, ResNet) for phytolith image classification in archaeological research.
• Developed reproducible computer vision pipelines using Python and PyTorch on GPU servers.
• Applied visualization and error analysis techniques (e.g., Grad-CAM) to interpret model behavior.

• Led the creation and refinement of machine learning algorithms for advanced predictive modeling.
• Directed a team to integrate AI techniques, achieving practical and impactful results.
• Ensured accuracy and reliability of models through comprehensive validation processes.