I'm Vasilis, a Software Engineer that likes to do both front and back-end development. My current aim is to focus more on front-end development using the Vue.js framework.
May 2019 - Present
Currently working as a front-end developer using Vue.js.
Aristotle University of Thessaloniki
January 2018 - May 2019
Worked as a Software Developer and Academic Researcher in an EU-funded Horizon project. As part of my duties, I made use of several social media APIs to collect data, analyze it using python, develop an API that exposes the analyzed data and develop a SPA that consumes those data and displays it in a web application.
July 2018 - January 2019
Developed an SPA using Vue.js and the Vuetify component library. The app involved authentication using JWT tokens, and was communicating with a backend API to fetch sensor data for specific time periods and visualize them as well as offer some administrative functionalities.
May 2013 - Present
Developed and currently developing various web and android applications using both backend and frontend technologies for various clients remotely.
Global-Energy Solutions Ltd
December 2014 - June 2015
Intern as a web developer in charge of enhancing the company’s web page and e-shop, while also managing the company’s social media. Performed IT duties on the side and developed some websites from scratch for a company’s associate.
Aristotle University of Thessaloniki, Greece
2016 - 2018
MSc., Computer Science (Internet & Worldwide Web)
Technological Institute of Central Macedonia
2009 - 2015
BEng., Informatics Engineering (Software Engineering)
A social media crowdsourcing platform that is developed as part of the PlasticTwist project in order to visualize online data regarding plastic pollution and other aspects of reusability. Several social media and online sources APIs are used to collect and analyze data, which are later visualized by an interactive web application.
An online monitoring and analytics platform for industrial data. The platform aims to help small factories keep track of their machinery data and predict possible failures. The data are collected via sensors, transmitted to a web server for analysis and consumed from an SPA made in Vue.js.