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Welcome! I’m Morgan White 👋
I’m a Computer Science Honours Graduate (CGPA: 10.92/12) from Carleton University, specializing in Artificial Intelligence and Machine Learning. I bridge the gap between cutting-edge research and practical industry applications, from multi-agent reinforcement learning to production-ready automation tools.
What I Do
I build intelligent systems that solve real-world problems. My work spans:
Professional AI Development:
- Developed an AI classification tool at the Canadian Food Inspection Agency that reduced manual data entry from 80% to 20% of analyst time—automating classification of 90,000+ food product rows with over 80% precision
Research Contributions:
- Conducted Honours research on cooperative agent behaviors using Unity ML-Agents, investigating how elimination mechanisms affect multi-agent cooperation in Sequential Social Dilemmas
- Published research on MARL robustness for agent blindness in VMAS, achieving 86% performance improvement through systematic hyperparameter optimization
Full-Stack AI Projects:
- Built autonomous robotics systems with computer vision and sensor fusion (100% success rate)
- Developed deep learning models for financial prediction and content analytics
- Created native iOS applications with custom UI components and secure authentication
I combine strong theoretical foundations in algorithms, machine learning, and mathematics with the ability to deliver production-ready code.
Technical Skills
Languages: Python, Java, C++, C#, Swift, Prolog, SQL
AI & Machine Learning:
- Deep Learning: TensorFlow/Keras, PyTorch, Neural Networks (RNN/LSTM/Transformer), TorchRL
- Reinforcement Learning: Unity ML-Agents, PPO, SAC, POCA, MAPPO, Multi-Agent Systems
- NLP: VADER Sentiment Analysis, TF-IDF Vectorization, NLTK, Lemmatization, Text Classification
- Libraries: Scikit-learn, Pandas, NumPy, VMAS (Vectorized Multi-Agent Simulator)
Robotics & Computer Vision:
- Webots Simulator, Sensor Fusion, Path Planning, Object Detection, Color-based Vision Systems
Development Tools & Practices:
- Git & GitHub, Agile Development, API Integration (YouTube, Reddit, Yahoo Finance), iOS Development (UIKit)
Specialized Knowledge:
- Multi-Agent Reinforcement Learning, Game Theory, Functional Programming, Sequential Social Dilemmas, Cooperative AI
Professional Experience
Canadian Food Inspection Agency — AI Developer (May 2024 - April 2025)
- Automated classification of 90,000+ food product rows using machine learning
- Reduced analyst data entry time by 75%, freeing capacity for high-value analysis
- Achieved 80%+ precision, recall, and F1-scores through TF-IDF vectorization and lemmatization
- Delivered presentations and training to ensure successful adoption across teams
- Offered contract extensions twice based on performance and impact
Carleton University — Teaching Assistant (Winter 2023, Fall 2024)
- Facilitated learning in Programming Paradigms and Introduction to AI courses
- Held weekly office hours supporting students with complex theoretical concepts
- Graded assignments and provided constructive feedback to enhance understanding
Elections Canada — Programmer Analyst (June 2022 - December 2022)
- Refactored hard-coded settings into dynamic database configurations
- Improved system maintainability and adaptability for the EREG application
- Collaborated with database developers and QA teams on feature integration
Featured Projects
🤖 Autonomous Robot Jar Collection System
Tech: Webots, Java, Computer Vision, Robotics
Built a fully autonomous mobile robot that navigates a 20×20m warehouse, detects honey jars using multi-sensor fusion (camera, compass, distance sensors), and completes manipulation tasks with 100% success rate and ±3° heading accuracy.
🧠 Multi-Agent RL: Agent Elimination & Cooperation
Tech: Unity ML-Agents, C#, Python, PPO, SAC, POCA
Honours research investigating whether elimination mechanisms improve cooperation in MARL environments. Built custom Unity environment with configurable elimination rules, testing 3 RL algorithms across 500K training steps.
🔍 MARL Robustness for Agent Blindness in VMAS
Tech: Python, PyTorch, TorchRL, VMAS, MAPPO
Research project studying how swarm agents handle partial observability through random “blindness” events. Created 6 custom scenarios, achieving 86% performance improvement through extensive hyperparameter tuning (50+ experiments).
🎬 YouTube Views Prediction with Transformers
Tech: Python, TensorFlow, YouTube API, NLTK, NLP
Advanced deep learning system using Transformer architecture with multi-head attention, GloVe embeddings, and feature interaction layers to predict video view counts from titles, descriptions, channel authority, and temporal patterns.
📈 Stock Price Prediction Using Reddit Sentiment
Tech: Python, TensorFlow, PRAW, yfinance, VADER
Multi-input RNN fusing real-time financial data with sentiment analysis of Reddit discussions to predict daily stock price changes, demonstrating how social media sentiment drives market movements.
Academic Achievements
Harry S. Southam Scholarship — $9,000 for Academic Achievement (2020-2023)
Dean’s Honour List — Consistent academic excellence (2020-2022)
Honours Thesis — Published research on agent elimination in cooperative MARL environments
Let’s Connect
I’m actively seeking opportunities in:
- AI/ML Engineering — Building intelligent systems that solve real problems
- Research & Development — Advancing the state of multi-agent learning and cooperative AI
- Robotics & Autonomous Systems — Developing perception and planning algorithms
Email: morgan13white@icloud.com
LinkedIn: morgan-white-95b245237
GitHub: morganwhite13
Resume: Download PDF
“The goal is not to build machines that think like humans, but to build systems that augment human capabilities and solve problems we couldn’t solve alone.”