About Me
Welcome To My Portfolio Webiste
A brief summary of my projects, experiences and education.
I am a full-time student studying Computer Science at the University of Warwick. I am in my fourth and final year, passionate about how the tech world is evolving and the life-changing impacts passed onto the rest of society. I also have a strong interest in the financial world, particularly in how technology affects finance personally and worldwide.
During my studies at university, I have undertaken various projects, work experiences and internships. These include Full-Stack development, machine learning, and database design. The languages and frameworks used include Python, Flask, Java, Vaadin, C, C++, SQL Server and React.
Operating within the ESB team, addressing Enterprise Application Integration problems.
Creating a new generation dashboard for the in-house Enterprise Integration Platform.
Presenting an ESG project on how blockchain can be utilised in the Voluntary Carbon Markets.
The skills used and developed here include Java, Vaadin, CSS, HTML, Financial Markets, REST-APIs, github, Jira, Confluence, Communication, Presentation and Agile Development.
My third year project and dissertation. Receiving a mark of 80%.
GPS art is the creation of visual compositions by mapping paths using a GPS tracking device. GPS artwork has gained popularity recently as a unique form of artistic expression that combines technology, physical activity, and creative design. However, plotting and designing these routes is an arduous process due to the restrictions imposed by street networks and urban landscapes. With no software or approaches currently providing a solution to this issue, this paper explores how an algorithmic approach can automatically generate GPS drawings, making the procedure more accessible and encouraging exercise.
A brief summary of my additional educational projects.
A second year group project developing an example mentor-mentee application for DB.
ViewExploring the application of clustering algorithms to the HetRec LastFM dataset to identify and analyze similarities among musical artists.
ViewUsing various machine learning techniques to separate different accent samples containing numerical data.
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