Research Fellow in Open data Engineering
Konstantinos is currently working as Research Fellow in Open Data engineering in the School of Computing and Digital Technology. He has a Bachelor’s degree in “Computer Science and Telecommunications Engineering” from the Higher Technological Educational Institute of Thessaly in Greece and a Master’s in “Advanced Computer Science” from Birmingham City University. He has 12 years of working experience in the IT industry (2005-2017) where he was implementing complex IT solutions including networking, IP PBX (VoIP) and satellite internet (VSAT and one-way).
During his employment with BCU, he has worked as Research Associate for the “Big Data Corridor” - a European Regional Development Fund (ERDF) project in collaboration with Birmingham City Council, Aston University, EnableID, Innovation Birmingham, and West Midlands Combined Authority (WMCA), aiming to provide data-related support and solutions for SMEs of the Greater Birmingham and Solihull Local Enterprise Partnership (GBSLEP) area. Following the completion of the “Big Data Corridor” project in 2019, he has been working as Data Scientist in the Data Science Collaboration (DSC) project - a consultancy project between Birmingham City Council and BCU, aiming to investigate new ways of handling and analyzing data to extract Insight and allow data-driven decision making for the provisioning of council’s services to Birmingham citizens.
His research interests include Data Science (Data integration, analysis and visualization, Machine Learning) and Data Modelling for different types of database systems such as relational (MySQL, Oracle, PostgreSQL), NoSQL (Cassandra DB, HBase, MongoDB), and graph (Neo4j) databases. He is also interested in Smart Cities and more specifically in vehicle traffic and air-quality data, and is currently working on a project that investigates the impact of the Clean Air Zone (CAZ) enforcement in Birmingham. Finally, he has some research experience in working with IoT data collection and integration and with using Big Data technologies such as Hadoop, HBase and Hive.