Development of custom device drivers for the interface of PC - UAV (Unmanned Aerial Vehicle), to manage and configure the UAV from a PC, using USB input to Virtual COM port.
Developed device drivers for the interface of PC – Drone to overcome connectivity and configuration issues. Device drivers provide access to the hardware features and are vitally important to the performance, reliability and flexibility of the system. As device drivers are the link between the application software and hardware components, an in-depth knowledge of both is necessary to ensure the driver is reliable, efficient and well structured.
Date: January 2014
Client: GeoAnalysis S.A.
Category: Software Engineering
Website development and administration - Energyfirst
Website for an Engineering Company 2014 - 2017
A website for an Engineering Company (2014 - 2017), promoting renewable energy applications and efficiency of indoor environments (Houses, Offices, Storage Units etc.).
Date: February 2014
Client: Energyfirst
Category: Software Engineering
Web application for a human resources liaison office
A Human Resources Liaison Office component for Joomla CMS.
A Human Resources Liaison Office component for Joomla CMS, part of my Bachelor of Engineering thesis. Fully managed on the admin panel. Offers many functionalities, including but not limited to, creating profiles e.g. employee-employer, job publications, applying for roles, and more.
Date: December 2014
Client: Bachelor thesis
Teammate: Margarita Kontofaka
Category: Software Engineering
Analysis of Real-World Innovation Networks with data Mining & Machine Learning
Study of real-world data related to innovation such as research partnerships and large corporate data, which were preprocessed, cleansed and used to build networks. The existing relationships between these networks at different levels (geographic, corporate, etc.) are constructed and their properties examined. Network data are being studied using data mining and machine learning models for existing patterns to better understand the dynamics of the past and predict the network’s evolution for future decision making.
