Clay Ndugga

Software Engineer

I'm a Mathematics & Engineering graduate from Queen's University. I enjoy using math and programming to tackle complex challenges and find innovative solutions.

resume.pdf

Clay Ndugga

Software Engineer

I'm a Mathematics & Engineering graduate from Queen's University. I enjoy using math and programming to tackle complex challenges and find innovative solutions.

resume.pdf

Experience

Software Engineer

Longview Systems   ·   8 Months 2023   ·   Calgary, AB

  • Modernized an existing codebase through refactoring, leveraging best-practice system design patterns and migrating to Azure/Databricks cloud architecture for enhanced scalability and performance.
  • Designed and implemented a robust data ingestion system using REST APIs, increasing reliability, and achieving a 70% improvement in ingestion times.
  • Engineered an end-to-end IoT solution encompassing data ingestion, storage, and real-time decision-making through ML models, enhancing operational efficiency.
  • Utilized Agile Scrum methodologies for iterative development and feature roll-out, while effectively tracking project milestones and tasks in Azure DevOps.

Machine Learning Engineer

Boardwalk Real Estate   ·   4 Months 2022   ·   Calgary, AB

  • Built an ML model using Tensorflow to predict tenant lease renewals with 85% accuracy, reducing profit loss to empty properties
  • Collected and processed over 1,000,000 data points from various sources including databases, surveys, and property management reports
  • Identified significant factors that effect the probability of a tenant renewing their lease
  • Optimized the model by hyperparameter tuning and feature engineering, increasing precision metrics by 20% compared to baseline models

Thesis

Neural Network Pointcloud Compression

    Made With:

Efficient compression is essential for the storage and transmission of data. While traditional methods like JPEG for images and MPEG for videos are effective for 2D media, they struggle with 3D data formats like point clouds. This project aims to enhance point cloud compression using a Non-Linear Transform Coder (NTC) , which can better handle the complexities of 3D data. The project focuses on designing a NTC for lossy point cloud compression. The architecture leverages neural networks to capture spatial patterns in point cloud data and eliminates redundancy, leading to efficient compression.

Projects

YTC Landing page Diagram

Youtube Comment Finder

    Made With:

I developed a serverless web application that integrates YouTube and Spotify, allowing users to search YouTube comments for song mentions. The backend leverages AWS Lambda and DynamoDB to efficiently manage job state between functions, ensuring scalability and reliability. Following serverless best practices, the architecture incorporates queues for loose coupling, idempotent function design, and caching mechanisms to enhance performance and resilience.

Serverless Architecture Diagram

LLM Research Paper Abstract Generator

    Made With:

Provided with a research paper title and a list of key findings, this project will generate an abstract for the research paper. This project demonstrates a serverless architecture for generating research paper abstracts using Large Language Models (LLMs). It employs a Retrieval-Augmented Generation (RAG) approach, integrating LLM prompt engineering with queries to a vector database for contextual relevance and accuracy. The project uses practices and tools that are crucial for modern, scalable applications.

Queen's Housing Full Stack Web Application

    Made With:

Queen's Housing is a full stack web application with a nodejs RESTful API backend, and a frontend made with tailwind css. The project gives a place for students to share and discuss their rental experiences, and is currently deployed on heroku. The project had similiar technical requirements as a social media app as I learned about: user authentication in browser sessions, designing database structure to fit certain requirments, routing, RESTful API development, and front end UI design. Note: The project is fully functional but contains mock data

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Queen's Housing Full Stack Web Application

    Made With:

How it's Made

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Challenges

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What I learned

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  • One-to-few
  • One-to-many
  • One-to-alot

PID controller tuning using the Genetic Algorithm

    Made With:

Using signal processing, control systems, and machine learning a PID controller was tuned with the Genetic Algorithm on an unkown blackbox system. The Genetic Algorithm is a global optimization technique that mimics natural selection to solve minimization problems!

React Frontend for VideoGame API

    Made With:

A React frontend for a video game API. The entire project was built using Typescript to replicate the needs of a large scale production environment. The react frontend allows users to selectively filter and search for different games, a GET request containing the relevant search parameters is then sent to the API to retrieve the appropriate games. Chakra UI was used to ensure consistent and aestically pleasing visuals.

NYC Taxi Fare Prediction

    Made With:

Analyzed NYC Taxi trip data and built multiple models to predict trip fare. Created an Ensemble model that combines the output of multiple predictive models to achieve higher prediction accuracy

Education

Applied Mathematics & Engineering

Systems and Robotics Minor   ·   2019 - 2024   ·   Kingston, ON

  • Similar to Software Engineering with a focus on advanced mathematics