Machine Learning Experience

Tools and Libraries | TensorFlow, PyTorch, GeoPandas, Computer-Vision, Clustering, Regression

• Worked with Convolution Neural Networks to practice supervised learning and test L2 Regularization

• Constructed a project aimed to use clustering of toronto neighbourhood data to find ideal vendor locations

• Experimented with Regression and Classification techniques on specified data to optimize RMSE and MAE

• Co-Developed a machine learning model for prediction optimization @ Bell increased potential customers by 20%

• 12 Month Internship Experience with Machine Learning and Data Science @ Bell

Cloud Computing Experience

Applications Utilizeds | GCP, AWS, Kubernetes, Docker, Azure, Confluent Kafka, Apache Beam

• Studied Cloud Computing with a focus on Google Cloud Platform and Confluent Kafka @ OTU

• Within the Final Research Project Docker was utilized to containerize Autonomous Vehicle Software to transfer to a Jetson

• Developed a Project to calculate the risk associated with the ACC systems in autonomous vehicles utilized GCP, Apache Beam Spark, BigQuery, and Looker Studio

• Working on various certifications on AWS for example: Solutions Architect Associate

Software Development Experience

Applications Utilizeds | Mobile SDK, Java, C#, C++, Git, Python

• Smarts Play a mobile platform designed to cater to the needs and interests of sports enthusiasts, athletes, and fans.

• Co-developed a P2P Distributed Social Network utilzing blockchain technology to add a layer of security to social interaction

• Contributed to an Open Source Java project to clean the GUI and remove various errors via Java testing extensions

• Contributed to various web development projects with the use of HTML, CSS, SQL, React, and Javascript

Capstone Adaptive Cruise Control

Applications Utilizeds | Ros, C++, Autoware, Python, YOLO, IoT, Linux

• Led a group in the development of software that can emulate adaptive cruise control functionality

• This project looks into the ROS and Autoware frameworks to automate a specific function [Adaptive Cruise Control] in the environment

• Designed and deployed extensions to the Autoware framework to allow platooning functionality longitudinal, and lateral-longitudinal.

• Implemented a real-time perception from depth and LiDAR cameras to allow real vehicles to adaptive to intermediate vehicles

• Leveraged Git version control for effective collaboration, version management, and project tracking.

• Worked alongside the Radio Frequency, Wireless Home Internet, No Line of Sight, and Propagation Modelling

teams. To optimize overall accuracy in prediction of qualified homes

• Analysis and definition of the best propagation models for pre-qualification of Wireless Home Internet users

• Optimized machine learning model using Various Python Libraries, improving RSME by 25% points and increasing precision by 30%

• Optimized and developed universal MySQL database entries, to ensure all data shared across teams is consistent for cell tower information. reducing model error by 30%