+
+
+ A driven and highly motivated full-stack developer, I am always ready
+ to improve and learn. With a vast knowledge of multiple programming
+ languages, paradigms and related technicologies, I have successfully
+ implemented many applications that have been used and loved by
+ clients.
+
+
+ Career
+
+ PowerHealth Solutions
+ 2019 - Current
+
+ Key Responsibilities
-
- Research distributed systems and middleware for use in tactical
- situations.
+ Redesign and maintain the PowerHealth Solutions costing product
+ (PPM).
- - Develop a project to show this research.
-
- Write about new technologies, their benefits to defence, and how
- they can be used.
+ Create and maintain various front- and back-end components to
+ support consistent theming, quality, and developer experience
+ across PPM and now the billing product.
- - Held a Negative Vetting 1 (NV1) Security Clearance.
+ -
+ Respond to internal and client feedback to improve the costing
+ product.
+
+ - Develop automated tests to improve code quality.
- Key Achievements
+ Key Achievements
- - Implementation of Raft algorithm for the camera network.
-
- Implementation of Hand Detection using CNN, and finger recognition
- with alternative algorithm.
+ Significant contributions to the redesigned costing product, that
+ is now in production use and enjoyed by clients.
+
+ -
+ Create and setup front-end and associated web server back-end
+ components on the costing and billing products, as well as
+ internal products.
-
-
- Kilburn Software
+
+ DST Group
+
+ Cadet at DST Group
+ 2018 - 2019
+
+ Key Responsibilities
+
+ -
+ Research distributed systems and middleware for use in tactical
+ situations.
+
+ - Develop a project to show this research.
+ -
+ Write about new technologies, their benefits to defence, and how
+ they can be used.
+
+ - Held a Negative Vetting 1 (NV1) Security Clearance.
+
+ Key Achievements
+
+ - Implementation of Raft algorithm for the camera network.
+ -
+ Implementation of Hand Detection using CNN, and finger
+ recognition with alternative algorithm.
+
+
+
+
+ Kilburn Software
+
+ Software Developer at Kilburn Software
+ 2016 - 2018
+
+ Key Responsibilities
+
+ - Develop Mac and iOS applications using Xamarin and C#.
+ -
+ Network and MS-SQL Server Troubleshooting and Implementation.
+
+ -
+ Adhere to quality standards regarding privacy of information for
+ schools.
+
+ -
+ Liaise with stakeholders of the application being developed.
+
+
+ Key Achievements
+
+ - Rollout of macOS and iOS applications to several schools.
+ -
+ Set up a testing station in the office to simulate a Catholic
+ Primary School.
+
+
+
+
+
+ Education
- Software Developer at Kilburn Software
- 2016 - 2018
+ Bachelor of Information Technology
+ 2016 - 2018
- Key Responsibilities
+ University of South Australia
+ GPA: 6.89
+ Awards
- - Develop Mac and iOS applications using Xamarin and C#.
-
- Network and MS-SQL Server Troubleshooting and Implementation.
-
- -
- Adhere to quality standards regarding privacy of information for
- schools.
-
- -
- Liaise with stakeholders of the application being developed.
+ University of South Australia 25th Anniversary Excellence
+ Scholarship
+ - 2nd year Scholarship in Information Technology
+ - 3rd year Scholarship in Information Technology
+ - Chancellors Letters of Commendation
- Key Achievements
+
+
+ Skills
+ Technical
- - Rollout of macOS and iOS applications to several schools.
+ - Java - Gradle, JUnit, Jooq, Swing
-
- Set up a testing station in the office to simulate a Catholic
- Primary School.
+ Angular and Web - including Typescript/Javascript, CSS, HTML
+ - SQL - primarily MSSQL/T-SQL
+ - Rust
+ - Flutter/Dart
+ - Xamarin + C#/.Net
+ -
+ Python - Tensorflow and pandas for machine learning and data
+ analysis
+
+ - Containerization - Docker and Podman/Buildah
+ - Development Tools - Git, Jira, shell
+ - Modern Operating Systems - Debian Linux, Windows, macOS
-
-
-
- Education
-
- Bachelor of Information Technology
- 2016 - 2018
-
- University of South Australia
- GPA: 6.89
- Awards
-
- -
- University of South Australia 25th Anniversary Excellence
- Scholarship
-
- - 2nd year Scholarship in Information Technology
- - 3rd year Scholarship in Information Technology
- - Chancellors Letters of Commendation
-
-
-
- Skills
- Technical
-
- - Java - Gradle, JUnit, Jooq, Swing
- - Angular and Web - including Typescript/Javascript, CSS, HTML
- - SQL - primarily MSSQL/T-SQL
- - Rust
- - Flutter/Dart
- - Xamarin + C#/.Net
- -
- Python - Tensorflow and pandas for machine learning and data
- analysis
-
- - Containerization - Docker and Podman/Buildah
- - Development Tools - Git, Jira, shell
- - Modern Operating Systems - Debian Linux, Windows, macOS
-
- Other
-
- - UI/UX - responsive, easy to use, and acessible design
- -
- Excellent written and verbal communication - handle client and
- internal feedback, new features and problems
-
- - Testing - automated unit and integration tests
-
-
-
- Hobby Projects
-
- Over the years I've hacked away at various personal projects. My
- preference is always to build, run and host applications locally,
- which includes this page!
-
-
- Recently my interesets have shifted slightly to large machine learning
- models, and have messed around with Stable Diffusion (mainly with
- Invoke AI) and Llama
- language models in
- rustformers. The
- latter has been a bit dissappointing (at least for its programming
- ability), and I think my job will stick around a while longer!
-
-
- Finally I've thoroughly enjoyed writing in Rust, mainly the
- efficiency, ease of use and correctness that come from using this
- programming language. One example was in the
- FastCoster
- project, where I reduced the time taken for processing some demo data
- on the costing product from ~1.5 hours to ~7 seconds on a
- laptop/desktop, or ~36 seconds on a smartphone. This was mainly due to
- not using SQL Server, and using a custom algorithm in overhead
- allocation that significantly reduced memory consumption and the
- number of required calculations.
-
-
- PiCar
- Source
-
-
- This project originally involved communication between a Raspberry Pi
- and a Traxxas Slash using the Pi's GPIO to control the steering and
- throttle of the RC Car. This was mounted on some 3D printed
- brackets.The steering and throttle are set using an iPhone/Android
- application connected over WiFi.
-
- Over time this worked as a base to explore other ideas, namely:
-
- -
- SLAM: Using BreezySLAM and a 2D RP Lidar A1, the Pi can map out an
- area and send this information to the controlling phone.
-
- -
- Depth Prediction: Using the Pi's camera and an Intel Neural Compute
- Stick (NCS), the Pi could process camera data and use a custom
- implementation of the
- FastDepthOther
+
+ - UI/UX - responsive, easy to use, and acessible design
+ -
+ Excellent written and verbal communication - handle client and
+ internal feedback, new features and problems
+
+ - Testing - automated unit and integration tests
+
+
+
+ Hobby Projects
+
+ Over the years I've hacked away at various personal projects. My
+ preference is always to build, run and host applications locally,
+ which includes this page!
+
+
+ Recently my interesets have shifted slightly to large machine
+ learning models, and have messed around with Stable Diffusion
+ (mainly with
+ Invoke AI) and Llama
+ language models in
+ rustformers. The
+ latter has been a bit dissappointing (at least for its programming
+ ability), and I think my job will stick around a while longer!
+
+
+ Finally I've thoroughly enjoyed writing in Rust, mainly the
+ efficiency, ease of use and correctness that come from using this
+ programming language. One example was in the
+ FastCoster
- Neural Network to add 3D sensing capabilities.
-
-
-
- Recently there have been efforts to port the backend to Rust, with the
- 2D Lidar sensing and control completed. The Python BreezySLAM
- implementation is currently unfinished, mainly due to distractions
- from other projects
-
-
- Depth Prediction
- Source
-
-
- From the PiCar project, I explored many different implementations of
- monocular depth Prediction and 3D SLAM solutions, including
- implementing my own algorithms and trainers for depth prediction that
- perform well on constrained devices.
-
-
- This gave me a solid foundation on Tensorflow/Keras and computer
- vision. It also helped expand my knowledge on machine learning from
- university/online study, as I previously had not explored models this
- large, or specifically computer vision related models.
-
-
-
-
+ This project originally involved communication between a Raspberry
+ Pi and a Traxxas Slash using the Pi's GPIO to control the steering
+ and throttle of the RC Car. This was mounted on some 3D printed
+ brackets.The steering and throttle are set using an iPhone/Android
+ application connected over WiFi.
+
+
+ Recently there have been efforts to port the backend to Rust, with
+ the 2D Lidar sensing and control completed. The Python BreezySLAM
+ implementation is currently unfinished, mainly due to distractions
+ from other projects
+
+
+ From the PiCar project, I explored many different implementations of
+ monocular depth Prediction and 3D SLAM solutions, including
+ implementing my own algorithms and trainers for depth prediction
+ that perform well on constrained devices.
+
+
+ This gave me a solid foundation on Tensorflow/Keras and computer
+ vision. It also helped expand my knowledge on machine learning from
+ university/online study, as I previously had not explored models
+ this large, or specifically computer vision related models.
+
+