Paraskevas KoukarasFaculty list

Paraskevas Koukaras

Dr. Paraskevas Koukaras is an academic scholar at the International Hellenic University (IHU) and a postdoctoral research associate at the Information Technologies Institute (ITI) of the Centre for Research and Technology - Hellas (CERTH). He has participated in H2020 and LIFE projects, engaging in demand response technologies for improved decision-making regarding energy ecosystems and prescriptive analytics for increased energy efficiency and well-being in residential buildings. His research interests focus on the domains of social media and energy, including energy load forecasting and optimization, machine learning, data analytics, information modeling, multi-layer information networks, heterogeneous information networks, graph mining and hybrid functionality algorithms.

Title:
Academic Scholar
University Degree/ Diploma:
IT Engineer, Department of Informatics, Alexander Technological Educational Institute of Thessaloniki (ATEI)
PhD Degree:
Interdisciplinary data science methods using machine learning for enhanced knowledge acquisition, School of Science and Technology, International Hellenic University (IHU)
E-mail:
p.koukaras@ihu.edu.gr
Recent publications:
Journals
  1. Koukaras, P., Tjortjis, C., & Rousidis, D. (2022). Mining association rules from COVID-19 related twitter data to discover word patterns, topics and inferences. Information Systems, 109, DOI: 10.1016/j.is.2022.102054.
  2. Koukaras, P., Nousi, C., & Tjortjis, C. (2022). Stock Market Prediction Using Microblogging Sentiment Analysis and Machine Learning. Telecom, 3(2), 358–378, DOI: 10.3390/telecom3020019.
  3. Kasseropoulos DP., Koukaras P., & Tjortjis C. Exploiting Textual Information for Fake News Detection. International Journal of Neural Systems. 2022 Dec;32(12):2250058. DOI: 10.1142/s0129065722500587. PMID: 36328968.
  4. Mystakidis, A., Ntozi, E., Afentoulis, K., Koukaras, P., Gkaidatzis, P., Ioannidis, D., Tjortjis, C. & Tzovaras, D. Energy generation forecasting: elevating performance with machine and deep learning. Computing (2023). https://doi.org/10.1007/s00607-023-01164-y
  5. Stasinos N., Kousis A., Sarlis V., Mystakidis A., Rousidis D., Koukaras P., Kotsiopoulos I. & Tjortjis C. A Tri-Model Prediction Approach for COVID-19 ICU Bed Occupancy: A Case Study. Algorithms. 2023; 16(3):140. https://doi.org/10.3390/a16030140
Conferences
  1. Kapoteli, E., Koukaras, P., & Tjortjis, C. (2022). Social Media Sentiment Analysis Related to COVID-19 Vaccines: Case Studies in English and Greek Language. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 360-372). Springer, Cham, DOI: 10.1007/978-3-031-08337-2_30.
  2. Karagkiozidou, M., Koukaras, P., Tjortjis, C. (2022). Sentiment Analysis on COVID-19 Twitter Data: A Sentiment Timeline. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 647. Springer, Cham, DOI: 10.1007/978-3-031-08337-2_29.
  3. Koukaras, P., Dimara, A., Herrera, S., Zangrando, N., Krinidis, S., Ioannidis, D., Fraternali, P., Tjortjis, C., Amagnostopoulos, C-N., & Tzovaras, D. (2022). Proactive Buildings: A Prescriptive Maintenance Approach. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham. DOI: 10.1007/978-3-031-08341-9_24.
  4. Zangrando, N., Herrera, S., Koukaras, P., Dimara, A., Fraternali, P., Krinidis, S., Ioannidis, D., Tjortjis, C., Anagnostopoulos, C-N., & Tzovaras, D. (2022). Anomaly Detection in Small-Scale Industrial and Household Appliances. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652., Springer, Cham, DOI: 10.1007/978-3-031-08341-9_19.
  5. Mystakidis, A., Ntozi, E., Afentoulis, K., Koukaras, P., Giannopoulos, G., Bezas, N., Gkaidazis, P.A., Ioannidis, D., Trjortjis, C. & Tzovaras, D. (2022, August). One Step Ahead Energy Load Forecasting: A Multi-model approach utilizing Machine and Deep Learning. In 2022 57th International Universities Power Engineering Conference (UPEC) (pp. 1-6). IEEE, DOI: 1109/UPEC55022.2022.9917790.
Book Chapters
  1. Koukaras, P., Rousidis, D., & Tjortjis, C. (2020). Forecasting and prevention mechanisms using social media in health care. In Advanced Computational Intelligence in Healthcare-7 (pp. 121-137). Springer, Berlin, Heidelberg, DOI: 10.1007/978-3-662-61114-2_8.
  2. Nousi, C., Belogianni, P., Koukaras, P., & Tjortjis, C. (2022). Mining Data to Deal with Epidemics: Case Studies to Demonstrate Real World AI Applications. In Handbook of Artificial Intelligence in Healthcare (pp. 287-312). Springer, Cham, DOI: 10.1007/978-3-030-79161-2_12.
  3. Kapoteli, E., Chouliara, V., Koukaras, P. & Tjortjis, C. (2023). Social Media Sentiment Analysis Related to COVID-19 Vaccinations. In: Lim, C.P., Vaidya, A., Chen, YW., Jain, V., Jain, L.C. (eds) Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-031-11170-9_3
  4. Michailidis, G., Vlachos-Giovanopoulos, M., Koukaras, P. & Tjortjis, C. (2023). Healthcare Support Using Data Mining: A Case Study on Stroke Prediction. In: Lim, C.P., Vaidya, A., Chen, YW., Jain, V., Jain, L.C. (eds) Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library, vol 229. Springer, Cham. https://doi.org/10.1007/978-3-031-11170-9_4
  5. Rousidis, D. & Koukaras, P. (Ιn Press, Q1 2023). From Relational to NoSQL Databases – Comparison and Popularity. Graph Databases and the Neo4j use cases in Social Media Analytics using Graph Databases (TBC), CRC Press, Taylor & Francis Group.
Research projects:
  • eDREAM “enabling new Demand Response Advanced, Market oriented and secure technologies, solution and business models”, https:/ /edream-h2020.eu/
  • DRIMPAC “Unified DR interoperability framework enabling market participation of active energy consumers”, https://www.drimpac-h2020.eu/
  • PRECEPT “A novel decentralized edge-enabled PREsCriptivE and ProacTive framework for increased energy efficiency and well-being in residential buildings”, https://www.precept-project.eu/
  • SmartWins “Boosting Research for a Smart and Carbon Neutral Built Environment with Digital Twins”, https://smartwins-project.eu/
  • easySRI “Improving and demonstrating the potential of SRI”, https://www.easysri.eu/en
  • SMACCs “ Erasmus Mundus Joint Master Degree”, https://www.smaccs.eu/
Course titles:
Additional course titles:
  • Software Development Methodologies
  • Big Data & Cloud Computing
  • Advanced Database Systems
  • ICT Essentials
  • Foundations of Computing
  • Data Science
  • Data Mining
  • Multimedia Data Analysis
Links to bibliometric databases:
https://scholar.google.com/citations?use...
https://dblp.org/pid/256/3942.html
https://www.scopus.com/authid/detail.uri...