Projects & Experience

Staff Engineer-Roboticist at MindPerfect Pty Ltd, responsible for prototyping construction solutions and programming. Manufactured AR4 robot for such use. Documentation TBA

Masters of Electrical and Computer Systems Engineering. Projected to graduated end of 2026

Led the technical branch as an executive for Monash Deep Neuron. Directed and managed HPC (High-Performance Computing) projects, providing technical and administrative management to several dozen team members. Performed and spear-headed recruitment, interviews and inductions for new recruits.

Led the High Performce Computing (HPC) Monash University workshop during semester 1 2026, consisting of several weeks teaching 100+ university undergraduates. Workshop 1: Introduction to C++ programming. Head lecturer. Workshop 2: Introduction to computer architecture. Head lecturer. Workshop 3: Introduction to HPC. Head lecturer. Workshop 4: HPC with NCI. Teaching assistant & event organiser. Workshop 5: Accelerated computing with Nvidia. Teaching assistant & event organiser. Workshop 6: HPC with Pawsey. Teaching assistant & event organiser. Photos/proof coming soon after workshops are completed.

Employed under professor at faculty of Civil Engineering, co-wrote the following Monash University Research Paper (for ISARC2025). Designed and executed an experiment analysing human-robot trust and performance using an UR robot arm. Captured motion data via Xsens and Optitrack and processed metrics using Python data analysis pipelines. Find the link below; the submission paper until official acceptance to ISARC2026 is posted.

Graduated with Electrical & Computer Systems Engineering Major. Chemical Engineering; Micro-Nano Technologies Minor. Certificate link is below, but you will need to request my email for the PIN to access for security purposes.

A self-hosted, cost-free LLM infrastructure tunneling a Google Colab T4 GPU instance to a local Python client via Ngrok. Features a custom "Sovereign Client" class implementing sliding-window memory management, context compression, and dynamic persona switching for the Qwen 2.5 (14B) model. Idealised as a remote cloud node for LLM API calls in larger projects.

A real-time Brain-Computer Interface (EEG) system funded by a Motorola Solutions grant with Monash Deep Neuron. Led and engineered a pipeline streaming EEG data into valid frequency domain waves via LSL and Kafka to a custom "EEG2Arm" AI model (3D CNN + Transformer) that translates motor imagery into safety-validated commands for Universal Robotics arms. Using docker to maintain universal "plug and play" functionality among any device.

Led the Optimised Computing (HPC) Monash University workshop series during the beginning of semester 1 2025. Consisting of 3 weeks teaching a class of university undergraduates fundamentals to C, Computer architecture, Computer memory, and CMake.

Internship at Mindperfect ltd as a systems and performance engineer. Responsible for benchmarking, unit testing library synthesis and usage for proprietary AI swarm program. Gtest, abseil, google benchmark, sanitiser (GCC) and Valgrind were utilised in this vein. Additionally, worked on emerging technologies such as LLMs (Llama v3), Sqlite for AI swarm communication database, C++ eigin & threading libraries for high performance mathematics, UML statecharts for intelligent swarm logic, and QT for cross-platform GUI creation. Allowing company assets to remain compliant and defect free.

Under Monash Deep Neuron's technical branch, partook as a project manager for the High performace computing project of Astrophysical simulations. A project tasked with synthesising a Astrophysical fluid engine starting from the mathematics (Navier-Stokes differential equations) using Cpp. Further, utilised openMP and mathematical innovations to allow for high performance, real time simulations. yielding a high-accuracy, yet fast engine for visual effects. SFML was used for the GUI development.

Winner of biennial SMEE (Society of Mechanical and Electrical Engineers) and MECC (Mechanical Enginering Clayton club) hackathon at Monash University, consisting of crafting the hardware and software of an arduino-based robot to traverse a maze the fastest. Winning the prize pool of $600.