About Me

I am a self-directed engineer actively building within signal processing, VLSI & ASIC design, and field-based device physics in the context of semiconductors, robotics and autonomous systems, and machine learning.

My approach to engineering is fundamentally first-principled and implementation-level, focused on building performant, scalable, and valuable proprietary systems.

Technical Skills

Languages: C, C++, Python, MATLAB, Verilog, SystemVerilog …
Simulation & Analysis: Matlab (Signal Processing, Control System, System ID …), Simulink, SPICE …
RTL Silicon Engineering: SystemVerilog RTL, Quartus Prime, formal verification …
Electromechanical Integration: Parametric CAD (Solidworks, Onshape), Embedded Control …

Education

  • Bachelor of Science — The University of Melbourne
    2023–2026 · Completed Both Majors:  { Electrical Engineering Systems Mechanical Engineering Systems
    Supplementing majors with advanced Software Engineering and Physics classes.
  • Master of Electrical Engineering — Machine Learning & Autonomous Systems — The University of Melbourne
    Expected 2027

Leadership & Extracurricular Experience

Professional Experience

Engineering Portfolio

Featured
By Category
01

Computational Electromagnetics & Field-Based Device Modelling

Developed first-principles electromagnetic and device-level models using Maxwell's equations, vector calculus, and nonlinear semiconductor theory.

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02

Multiphysics Simulation & Numerical Methods

Numerical implementation of structural mechanics and dynamic system solvers, integrating finite element modelling with nonlinear and differential equation methods.

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03

System Architecture, Drivetrain Design & Embedded Integration

End-to-end mechatronic system development spanning drivetrain optimisation, robust control systems, and subsystem packaging across autonomous rover and electromechanical prototype platforms.

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04

Signal Processing & Machine Learning

Active filter synthesis, frequency-domain characterisation, and hardware-validated digital signal processing — extended into machine learning and data-driven methods.

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05

Embedded Systems, Control & Autonomous Dynamics

Development of distributed embedded systems and performance-oriented C++ architectures — integrating hardware control, real-time communication pipelines, and structured software design from firmware through to GUI — alongside designed-and-tuned feedback control for dynamic platforms, combining practical PID implementation with classical, stability-focused control analysis.

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07

Miscellaneous

Thermal and fluid science work spanning experimental pipe flow characterisation and thermodynamic cycle analysis — cross-validated results with theoretical models and assessed performance against idealised benchmarks.

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