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Collin A. P. Joseph, M.Eng.

cjoseph30@myseneca.ca | collinapjoseph.github.io | linkedin/collinjoseph0258 | github/collinapjoseph

Summary

An Artificial Intelligence and Machine Learning Engineer with a diverse skill pool and continuous growth mindset.
Currently completing a Graduate Certificate in Artificial Intelligence at Seneca Polytechnic.

Experience

Lead Software Developer

Jun 2023 - Mar 2025
Yulio Technologies Inc. Toronto, Canada
  • Delivered new features for multiplatform (.NET Core & .NET Framework) C# application.
  • Led multi-national development team while continuing hands-on development (C# & C++).
  • Managed development of 3 key software products using Agile Project Management.
  • Liaised with client support team to organize and triage client requests for 3 products.
  • Released multiple features and updates for each product per year.

Software Developer

Dec 2020 - Jun 2023
Yulio Technologies Inc. Toronto, Canada
  • Published and maintained multiplatform (.NET Core & .NET Framework) C# application.
  • Implemented module to export 3D models from Autodesk Revit to glTF.
  • Built C# REST API client to upload models to cloud rendering platform.
  • Deployed C++ tool to generate and manipulate HDR image-based lighting environment maps.
  • Enabled native & managed runtime interoperability between modules using C++/CLI.
  • Parsed extensive variety of physically-based rendering material properties to glTF format.
  • Maintained and updated legacy SketchUp Extension (HTML/CSS & Ruby).

Software Developer

Nov 2019 - Apr 2020
wrnch AI Montreal, Canada
  • Delivered new features for Computer Vision inference server using C++.
  • Prototyped new CNN models and updated existing ones using Tensorflow.
  • Automated data pre-processing pipeline and model benchmarking using Python.
  • Deployed watchdog client using Python for server monitoring and control.
  • Shipped new features and updates to clients using Docker.
  • Collaborated with team using version control and an Agile development workflow.

Graduate Student Researcher

Sep 2017 - Oct 2019
McGill University Montreal, Canada
  • Developed ensemble classifier for medical microwave radar scans using Python.
  • Performed extensive statistical analysis on radar scans using MATLAB and R.
  • Optimized ensemble training using advanced adaptive algorithms.
  • Improved predictive performance by proposing new time-frequency decomposition features.
  • Streamlined data pre-processing by developing tools in Python.

Signal Processing Algorithm Developer (co-op)

Sep 2016 - Dec 2016
ON Semiconductor Waterloo, Canada
  • Prototyped an environment classification algorithm for low-resource digital hearing-aids (MATLAB & Assembly).
  • Optimized acoustic noise reduction algorithm in Assembly, decreasing power consumption by 20%.
  • Leveraged fixed point arithmetic operations to maximize algorithm efficiency on embedded hardware.
  • Executed rigorous regression testing on algorithm to ensure performance equaled or exceeded previous iteration.

Signal Processing Algorithm Developer (co-op)

Jan 2016 - Apr 2016
ON Semiconductor Waterloo, Canada
  • Prototyped a digital equalizer firmware module in Assembly Language.
  • Simulated and performed experimental analysis on digital equalizer using MATLAB.
  • Executed and documented extensive test procedures for acoustic feedback cancellation algorithm.
  • Documented and presented analysis and test results to firmware and software development team.

Signal Processing Algorithm Developer (co-op)

May 2015 - Aug 2015
ON Semiconductor Waterloo, Canada
  • Evaluated performance of an acoustic noise reduction algorithms using MATLAB.
  • Developed functional simulations to evaluate performance of various digital signal processing algorithm configurations.
  • Performed experimental analysis on multiple noise estimation methods for enhancement of noise reduction algorithm.
  • Developed and executed automated acoustic tests for directional noise reduction algorithm using MATLAB & C.

Teaching Assistant

Sep 2014 - Dec 2014
Faculty of Engineering, University of Waterloo Waterloo, Canada
  • Tutored engineering students in C# programming fundamentals.
  • Presented course content to students on an individual basis and in classes of up to 100.
  • Consistently completed administrative and pedagogical tasks ahead of deadlines.
  • Cooperated effectively with teaching team of 18 members to ensure smooth running of the course.

Research Assistant

Jan 2014 - Aug 2014
Center for Intelligent Antenna and Radio Systems, University of Waterloo Waterloo, Canada
  • Developed and evaluated a ray tracing simulation tool for radio wave propagation using C++ and MATLAB.
  • Improved runtime by over 60% using CUDA parallel computing platform on Nvidia GPU hardware.
  • Built GUI using MATLAB to visualize simulation results.

Projects

Personalized Medication Assistant Ongoing

Smart assistant that uses Retrieval Augemented Generation to provide information about user medication regimens.
Everyday users can use the intelligent assistant to quickly obtain relevant infomation about medications stored in their profile.
Repo: github/personalized-medication-assistant
Stack: Python, Langchain, ChromaDB, HuggingFace

Capstone: Text Extraction from Images of Handwritten Prescriptions Ongoing

Containerized REST API that extracts medication information from handwritten prescriptions.
Demo: gcp/capstone
Repo: github/capstone
Stack: Python, FastAPI, Docker, GCP, PyTorch, Hugging Face

Cloud Deployable Computer Vision API Jun 2026

Containerized REST API that accepts handwritten digits and retuns classifications using a CNN model.
Demo: gcp/handwritten-digit-api
Repo: github/handwritten-digit-api
Stack: Python, FastAPI, PyTorch, Docker, GCP

Computer Vision: Object Detection Using YOLO26n Apr 2026

Python program which uses YOLO26 to perform object detection on City of Toronto street camera images.
Notebook: github/traffic-camera-object-detection
Stack: Python, PyTorch, Gradio

Classification of Diabetes Diagnosis via Health/Lifstyle Indiciators

Apr 2026

A Python notebook modelling diabetes diagnosis using Random Forests.
Notebook: collinapjoseph/ml-notebook-diabetes-health-lifestyle-indicators
Skills & Stack: Machine Learning, Python, Scikit-Learn

Regression of Athlete Performance

Apr 2026

A Python notebook modelling powerlifting athlete performance using Linear Regression and Decistion Tree.
Notebook: collinapjoseph/ml-notebook-openpowerlifting-regression
Skills & Stack: Machine Learning, Python, Scikit-Learn

Blog Website

Oct 2025

A blog website that allows visitors to: view, create, edit and delete blog entries.
Demo: collinapjoseph/web-blog
Stack: HTML, CSS, EJS, Bootstrap, JavaScript, jQuery, Node.js, Express.js

Tabletop RPG Dice Roller

Oct 2025

Make Tabletop RPG dice roles via text input.
Demo: collinapjoseph.github.io/ttrpg-dice-roller
Stack: HTML, CSS, JavaScript, jQuery

"Simon" Memory Game

Sep 2025

Browser-based implementation of the "Simon" sequential memory game.
Demo: collinapjoseph.github.io/simon-game
Stack: HTML, CSS, JavaScript, jQuery

Drum Kit

Sep 2025

Browser-based app where user can play drums using keystrokes or mouse.
Demo: collinapjoseph.github.io/drum-kit
Stack: HTML, CSS, JavaScript

Education

Graduate Certificate, Artificial Intelligence

2026-present
Seneca Polytechnic Toronto, Canada

Current GPA: 4.0
Coursework: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics.

Google Prompt Essentials

Aug 2025
Google Career Certificates Online

Advanced frameworks and techniques for Prompting Generative AI tools.
Methods for using Generative AI to streamline data analysis.
Strategies for using Generative AI as AI Agents to enhance productivity.

Deep Learning Specialization

Sep 2019
Coursera, DeepLearning.AI Online

Five-course specialization developed by Stanford University's Andrew Ng.
Detailed explanation of essential Deep Learning architectures, including: Deep Neural Networks, CNNs, RNNs LSTMs.
Frameworks for structuring Machine Learning projects and Python-based assignments using Tensorflow and Keras.

Master's of Engineering, Electrical Engineering

2019
McGill University Montreal, Canada

Research Topics: Machine Learning, Signal Processing, Statistical Analysis.
Master's Thesis: mcgill.ca/theses/q237hx09z.
Coursework: Machine Learning, Linear Models, Optimization.

Bachelor's of Applied Science, Electrical Engineering

2017
University of Waterloo Waterloo, Canada

Co-op program (24 months of industry internships in total).
Coursework: Algorithm Design & Analysis, Adaptive Algorithms, Digital Signal Processing.

Skills

Programming Languages:
Python, C#/.NET, C++, HTML, CSS, JavaScript, SQL, MATLAB, Assembly Language
Libraries & Tools:
Git, GitHub, JIRA, FastAPI, PyTorch, TensorFlow, Scikit-Learn, Pandas, Numpy, Bootstrap, jQuery, Espress.js, Node.js, AWS (SageMaker, DataWrangler), GCP (VertexAI, Google Cloud Run, AutoML)
Technical Skills & Knowledge:
Artificial Intelligence, Machine Learning, Deep Learning, NLP, Computer Vision, Object Oriented Programming, Algorithms & Data Structures, Digital Signal Processing, Prompt Engineering
Soft Skills:
Leadership, Research, Agile Project Management, Technical Communication & Documentation
Languages:
English (Native), French (Basic), Spanish (Basic)