- Conducted stability analysis and wrote GHS code scripts to assess the impact of damage and intact scenarios on vessel stability and safety.
- Developed and managed Excel-based analytical tools for continuous stability analysis and weight reporting, optimizing data-driven decision-making throughout the vessel design process.
- Prepared comprehensive reports, presented findings, and made recommendations based on data analysis and naval architecture expertise.
- Crafted ship standards and technical manuals complying with safe practices, classification society rules and operational standards.
- Worked extensively with computer-aided design (CAD) software to design and model vessels, including hull forms and compartment layouts.
- Employed optimization and simulation techniques to improve vessel maneuverability.

- Wrote GHS code to evaluate vessel stability in damage and intact scenarios, ensuring compliance with safety regulations.
- Utilized historical vessel data to adjust and refine initial weight estimates, refining and enhancing the accuracy of weight predictions throughout the vessel design process.
- Analyzed data and produced reports in Microsoft Office Suite to create precise vessel stability and weight reports for the engineering team.
- Worked closely with interdisciplinary teams as designs progressed from functional design stage to production design for Royal Canadian Navy vessel construction.
- Produced comprehensive ship standards and design reports, utilizing strong attention to detail and technical expertise to improve vessel performance and safety.
- Updated technical drawings in CAD software, adhering to vessel requirements and classification society regulations, and ensured seamless integration with other departments.

For my lighthouse labs final project I create a recommender system. I love movies and I am very interested in neural networks. This project uses a hybrid collaborative and content based filtering neural network recommender system to recommend movies to users based on the previous movies they've watched.

The project predicted flight delays using machine learning algorithms in python. It involved many steps including:
- data review and extraction using SQL
- data cleaning, preprocessing & exploratory data analysis in Python
- weather data extraction using API
- feature engineering to make the data set more robust
- created and evaluated numerous machine learning models