-     Researched and developed AI algorithms, using large datasets, to enhance the autonomy capabilities of military technology.

-     Improved success rate by 58% by applying predictive modelling and machine learning techniques to optimise performance in chaotic conditions.

-     Adapted algorithms to evolving data inputs, ensuring robust performance in high pressure, dynamic environments.

Video on the left shows implementation of a machine learning algorithm controlling the movements of a drone, while an AI detects targets in a simulated environment. Large datasets were used to refine movements and reliably detect targets, which led to a significant improvement from previous iterations of the system. This was programmed in C++ and the data and training was done in python.

-     Researched and co-authored a novice guide on electrical engineering, demonstrating analytical and communication skills.

-     Collaborated with technology and business departments to identify inefficiencies, conduct interviews, and present strategic improvement recommendations, of which 80% were implemented.

-     Assisted in developing software for managing a new fighter jet program.

-     Collaborated with a large team to design, manage and automate an engine test rig.

(No photos from Internship due to data protection policies)

-     Conducted statistical analysis on large datasets, identifying key trends, patterns and features using Python

-     Created predictive models to forecast future outcomes based on historical data.

-     Back tested models to quantify their effectiveness and uncertainties and ensure robust performance.

-     Improved accuracy by 40% by applying linear regression, time series forecasting techniques, and machine learning algorithms.