• 👋 Hi, I’m @LetMeBeJim
• 🌱 Currently working on my own website

Toronto, Ontario linkedin.com/in/bojingyao/

Machine Learning Engineer Transport Canada, 2023

• Collaborated with a team using Azure DevOps and Kanban to implement a machine learning framework, improving the efficiency of updates for the Government of Canada's regulatory catalog.
• Achieved 95% accuracy in classifying over 200,000 regulatory data points using a fine-tuned BERT model, enhancing quick access to regulation types for regulators.
• Developed a LangChain and LLM-based tool for quantifying administrative burdens, significantly reducing manual review time by automating burden calculations across departments.
• Managed Databricks pipelines for data transformation and integration of multilingual regulatory data, ensuring robust data processing workflows.
• Conducted regular knowledge-sharing sessions on machine learning and prompt-engineering techniques.
• Achieved 95% accuracy in classifying over 200,000 regulatory data points using a fine-tuned BERT model, enhancing quick access to regulation types for regulators. Additionally, performed experiment logging and model tracking through MLFlow to ensure traceability and reproducibility of results.
• Utilized Large Language Models to perform Entity Extraction from regulatory documents, leveraging Retrieval-Augmented Generation technique and Few-Shot prompting to automate the identification of industry activities from regulatory texts. Also performed some condensation of these entities through clustering, reducing required number of prompts by 75%.
• Interpret requirements and ensure the solution aligns with operational goals. Participates in stakeholder meetings to clarify technical specifications, defining KPI and success metrics.

Web Designer Unit Operations Laboratory, University of Toronto, 2019

• Developed a comprehensive multi-page WordPress website, incorporating interactive 360-degree videos to facilitate access to Standard Operating Procedures for approximately

Question Answering Machine, 2024

• Finetuned a Transformers model for Q&A purposes based on the COVID-19 research dataset
• Generated Question-Answer pairs using a BART model and finetuned a distilbert model for extractive Question�Answering.

Convolutional Neural Networks, 2023

• Produced a Convolutional Neural Networks model using VGG16 to correctly identify front view of faces with an 80% accuracy, using a small data-set of handpicked images
• Modified a pre-trained CNN model's architecture by applying Deep Learning and Transfer Learning through adding Dense layers and evaluating the model through DropOut layers for Multi-class classification tasks
• Incorporated the model in a real-time video to experiment with the applicability of using the model through a camera

Master of Science, Computer Science Toronto Metropolitan University 2024 | Toronto •With a focus on Neural Network models and Machine Learning algorithms

Honours Bachelor of Science, Computer Science Toronto Metropolitan University 2023 | Toronto

Languages Java, Javascript, PHP, Python, HTML, CSS, SQL, Bash

Software Tools & Operating Systems Databricks, Git, GitHub, Google Cloud, Windows, Linux

Frameworks Tensorflow, Keras, PyTorch, LangChain, Transformers

Interests Sketching, Puns, Warhammer 40K