Peter Szabó
Associate Professor
Košice, Region of Košice, Slovakia
Summary
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RockstarPeter Szabó is an Associate Professor based in Košice, Slovakia, with 11 years of software engineering experience bridging academia and practical full‑stack development. He contributes to notable open-source projects such as H2O Wave, adding UI features, authentication integrations, and reliability fixes that improve realtime web apps and dashboards for Python and R users. His work demonstrates a pragmatic blend of research-level rigor and hands-on engineering—tackling both UX details like color domains and tabs and backend concerns like token forwarding and blocking UI during server calls. As an academic who ships production-quality code, he brings thoughtful, reproducible solutions to complex web and data visualization problems.
11 years of coding experience
Github Skills (23)
dashboard10
python10
oid10
typescript10
ui-design10
uid10
front-end-development10
android-app10
webapp10
typescript-types10
iphone-app10
typescripts10
react10
application10
visualization9
Programming languages (4)
Github contributions (5)
h2oai/wave
Jul 2020 - Aug 2021
Realtime Web Apps and Dashboards for Python and R
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:44 reviews, 55 commits, 20 PRs in 1 year 1 month
Contributions summary:Peter contributed to the development of the H2O Wave web application framework. Their work included implementing features such as custom color support in plots using `color_domain`, specifying selected tabs in `tab_card`, and blocking the UI while waiting for server responses. They also focused on fixing bugs, including auto-hiding of axis labels and adding data-test attributes to various UI components and form elements. Furthermore, they integrated OIDC authentication and enhanced the platform by forwarding access and refresh tokens to the Python client.
realtimepythondashboardsweb-appsr-and-python
h2oai/wave-ml
Jan 2021 - Aug 2021
Automatic Machine Learning (AutoML) for Wave Apps
Contributions:5 releases, 16 reviews, 170 commits in 7 months
deep-learningmachinelearningmachine-learningwavepredictions
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