Training Graph Neural networks is an expensive operation which requires increasingly more compute and memory as the input graph size increases. This project focuses on the quantized training of GNNs to tackle this problem.

Unfortunately, the blind are at a disadvantage when it comes to academic attainment simply since the necessary tools needed are not widely available. The focus of this project was to provide an Imaginative, innovative and cost-effective system to combat this.

During a Christmas charity fundraising run with Greenford Rotary Club, I noticed that an excessive amount of time was taken up to count coin donations. Therefore, to allow fundraisers to spend more time fundraising rather than counting coins I built from scratch a protoype Charity box to reduce time taken to count coin donations

Developed an alarm designed for domestic use to alert users when a certain area has been tresspased

I made a robotic arm feed me

An embedded IoT device to help reduce drink spiking

Made the viral 2048 game using C++

Wrote an algorithm to solve any mastermind code with as many symbols or digits.

Designed an operational amplifier using LT072 and MC33078 Chips to meet rigorous criteria

Designed a wirelessly controlled rover with the ability to sense, store and decode data for Acoustic, Infrared and Radio signals carrying UART data. As the project manager, I also distributed tasks amongst the team, set deadlines, maintained documentation and edited the technical report

More Coming Soon....