Georgios Matzarapis

Diploma Thesis: A hybridization of Mobile Crowdsensing, Twitter Analytics, and Sensor Data for the holistic approach of pollen onsets detection, using Flask microframework

During the last years of my studies I worked at the Internet of Things (IoT) laboratory, directed by Professor Sotiris Nikoletseas. I implemented tasks related to big data processing - efficient ways to read/write from/to NoSQL databases - and also developed my thesis. Furthermore, I participated as auxiliary staff in the laboratory of the course ”Topics in Computer Architecture” where used the assembly programming language.

• Developed key features for robots' telemetry system, including local data storage, internal streaming using the ZMQ protocol, and live-streaming via web-sockets to Foxglove Studio
• Designed and implemented a cloud-hosted logging management infrastructure with Grafana Loki
• Migrated robots' body control API to Behavior Trees, enhancing modularity and scalability

• Developed a middleware library responsible for the communication between backends
• Developed proxy services to forward HTTP requests to HTTPS based backend
• Developed rest APIs
• Developed automation tools for monitoring purposes of credit cards
• Participated in the PCI-DSS v4 audit

• Worked on the development of a Windows end user service, responsible for coordinating the communication between applications and the cloud
• Developed unit and integration tests, as well as a mock HTTPS server to remove external dependencies

• Developed end-to-end features on a document management web system
• Created helper tool that improved the live monitoring of servers' status
• Provided 1st level technical support to the customers

• Developed the UI automation infrastructure of the Greek department, to test features of the Windows Remote Desktop application
• Created test plans, test cases and evaluated them for the inclusion in regression test suites
• Manually testing on Android, iOS, Windows, Mac, Linux

Worked on a personal allergy tracking application:

• Developed tools for the quality evaluation, metrics extraction and process of data to evaluate the movements made by a human with those calculated by a machine learning process
• Implemented rest API accessible and documented by swagger