CV

Personal Details

Name: John Chang Su
Email: JohnChangSu@gmail.com
LinkedIn: https://www.linkedin.com/in/john-su
GitHub: https://github.com/Johnnny-suu

Work Experience

2020 – Present Application Engineer at Simuserv LTD

• Performing finite element analysis consultancy, training, and technical assistance with Abaqus and Simulia related products across Australia and New Zealand

• Taught Abaqus and FEA design to professional engineers.

• Project lead on simulating the thermal stress response from welding using Abaqus FEA. The results were compared with real-life measurements and our simulations results were able to show that the measurements were not correctly performed.

• Modelling a carbon-fibre composite tyre for the automobile industry

2022-2023 Research assistant for University of Sydney

• Investigating the use of Physics Informed Neural Networks (PINNs) to solve forward and inverse differential equations. The focus examined recover fluid velocity with limited temperature or concentration data.

• Created a python framework for post-processing LS-Dyna simulations allowing researchers to view simulation results in near real time and generate results without needing to transfer simulation data.

2022 – 2023 Avionics Engineer for University of Sydney Rocketry Team

• Design of avionics bay and camera bay using SolidWorks

2018 - 2019 Research assistant at the University of Auckland

• Chemical analysis of electrospray ionization via theta capillaries
• Bond graphs – Graphical representation of metaphysical systems

Education

2022 – 2023 Master of Engineering – Intelligent Information

University of Sydney

• Electrical Engineering with a focus on machine learning, fibre optics and sensor design
• Engineering Postgraduate Merit in Electrical and Information Engineering Scholarship Recipient
• Grade: High Distinction

Projects

• Thesis: Adapter Layers for low precision Neural networks. The project investigates the possibility of using adapter layers to improve the accuracy and finetuning methods for binary quantised neural networks.
• Leader of a team of 35+ master students to 1^st place in designing a sustainable city

2016-2019 Bachelor of Engineering (Honours) – Engineering Science

University of Auckland

• Computational modelling from physics/biological modelling to optimisation of logistics and operations
• GPA: 7.9/9.0 (First Class Honours)

Personal Projects

• Led a team to design a self-driving electric RC using camera vision. Led the development of the computer vision algorithm and electronics of the RC car

• Participant in AWS Deepracer 2022 Sydney League to design reward functions for reinforcement learning based control algorithms

Skills

Python

• Pytorch, Scipy, NumPy and Pandas for numerical modelling and machine learning
• Computer Vision techniques such as canny edge detection, HOG transform using OpenCV
• Interfacing with commercial software APIs such as Abaqus and Ansys to help researchers and professional engineers to post process results

Simulation Skills

• Certified Simulia Technical Support (incl. Abaqus)
• Abaqus for linear and highly non-linear structural simulation
• Isight for optimisation, design of experiments and six sigma analyses for engineering design
• Tosca for topological optimisation of models
• Fe Safe for fatigue analysis of structures
• Ansys Fluent and X-flow for CFD modelling

Miscellaneous

• Languages spoken: English (Fluent), Mandarin Chinese
• Sports: Kendo, long distance running, football