Matthew Strasiotto
Software Engineer at Logilica
Greater Sydney Area Australia
Summary
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Top SchoolMatthew Strasiotto is a software engineer based in the Greater Sydney Area with eight years of experience building quality software at the intersection of hardware and data-driven systems. Trained in Electrical Engineering with a major in Internet of Things, he blends embedded-systems thinking with full-stack development to deliver practical, reliable solutions. At Logilica and through academic research roles, he has applied rigorous data analysis and engineering practices to real-world problems, including medical record data liberation and lab-style research projects. An active open-source contributor, he has improved user interaction and visualization features in projects like the widely used R pipeline toolkit drake and enhanced UI/graphing tooling for a kernel-mode input project. He brings a user-centered approach to tooling—adding interactive node selection, streaming modes, and polished chart styling—showing attention to both developer ergonomics and end-user experience. Curious and hands-on, he thrives where software and hardware meet to create tangible, high-quality results.
7 years of coding experience
3 years of employment as a software developer
The University of Sydney
Github Skills (15)
data-visualizations10
net10
asp-net10
dotnet10
data-visualisation10
user-interface10
data-visualization10
csharp10
ui-design10
drake10
dotnet-core10
r10
charts10
javascript8
testing8
Programming languages (26)
Github contributions (5)
RawAccelOfficial/rawaccel
Apr 2021 - May 2021
kernel mode mouse accel
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:19 commits, 1 PR, 4 comments in 5 days
Contributions summary:Matthew primarily focused on enhancing the user interface and functionality of the grapher tool. They implemented features like docking legends and adding chart background color properties. Further work involved refactoring chart styling, including setting transparencies for chart elements and adjusting legend positioning. They also added a streaming mode feature, encompassing menu integration and color scheme updates.
kernelaccellinuxmousemouse-accel
ropensci/drake
Aug 2019 - Oct 2019
An R-focused pipeline toolkit for reproducibility and high-performance computing
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:50 commits, 1 PR, 32 comments in 2 months
Contributions summary:Matthew primarily contributed to the `vis_drake_graph` function within the `drake` package, adding and refining features related to node selection and user interaction. They integrated an `on_select` event handler to allow users to click nodes and trigger actions, initially using alert messages. The user then updated the default behavior to open the link specified in the `on_select_col` property. They also wrote tests for these behaviors.
pipelinehigh-performance-computingscientific-computingfocusedperformance
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