Currently working at AUSCERT as a Cyber Security Analyst.

• Developed the firmware for the control system of a unmanned ground vehicle with C/C++ utilising the PX4 framework.
• Ported and enhanced simulation of track-based vehicles from Python to C/C++

Tutor for the project-based first year engineering course ENGG1100: Professional Engineering. My responsibilities included:

• Supporting students to develop a concept report for a subsystem to their teams solution to the given problem.
• Assisting in the development and testing of their prototype.
• Providing feedback and grading reports and presentations.
• Offering additional support for all students in this course at the Engineering First Year Learning Centre.

Ran a student Facebook group alongside on-campus workshops to promote and teach MATLAB and Simulink concepts and tools. Workshops include:

• MATLAB Onramp
• Simulink Onramp
• Drone Simulation Modelling with MATLAB, Simulink, and Stateflow
• Control System Design with Simulink
• Signal Processing with MATLAB
• Data Processing and Visualisation in MATLAB

Organised and ran workshops on public speaking, negotiation, and teamwork. Provided students with mentorship on leadership and teamwork issues within their studies and careers.

Volunteered as a Coordinator and Challenge Developer for the 2022 International Cyber Security Challenge: Oceania Qualifiers.

• Developed three cyber security challenges which tested the participant’s ability to critically analyse and solve complex problems using existing and self-developed scripting tools and techniques.
• Connected with the leadership teams of cyber security oriented university clubs within Australia to organise the promotion of and participation in the qualifiers.

Investigated the trade-off between shallow and deep learning techniques in preventing cyber-attacks on critical infrastructure by comparing the accuracy, precision, recall, and F1 scores of various machine learning models and the time taken to process network traffic. During this process I was under the supervision of Dr Abigail Koay.

• Developed a internet traffic pre-processor in Python to turn raw packets in a readable format for SciKitLearn’s machine learning models.
• Invesitagated the abilities of KNN, k-Means, Random Forest, and SVM algorithms and deduce their viability in network intrusion detection. Each were trained and tested with variations of Shannon Entropy pre-processing on the given attack dataset.