C. Chira, E. Mathioudis, C. Michailidou, P. Agathangelou, G. Christodoulou, I. Katakis, E. Kontopoulos, and K. Avgerinakis, “An Affective Multi-Modal Conversational Agent for Non-Intrusive Data Collection from Patients with Brain Diseases”, in proceedings of CONVERSATIONS Conference, Springer, Amsterdam, 2022

C. Maga-Nteve, E. Kontopoulos, N. Tsolakis, P. Mitzias, I. Katakis, E. Mathioudis, K. Avgerinakis, G. Meditskos, A. Karakostas, S. Vrochidis and I. Kompatsiaris, “A Semantic Technologies Toolkit for Bridging Early Diagnosis and Treatment in Brain Diseases – Report from the Ongoing EU-funded Research Project ALAMEDA“, in proceedings of Metadata and Semantics Research Conference, Springer, Madrid, 2021

P. Agathangelou, I. Katakis, Balancing between holistic and cumulative sentiment classification, Online Social Networks and Media 29 (2022)100199.doi:https://doi.org/10.1016/j.osnem.2022.100199.835

Karl Aber,  Ioannis Katakis, Quoc Viet Hung Nguyen, Hongzhi Yin, “”Preface – Special Issue on Misinformation on the Web“”, Information Systems, Elsevier, Volume 103, 2022, 101867, ISSN 0306-4379.”

P. Agathangelou, I. Katakis, “A Hybrid Deep Learning Network for Modelling Opinionated Content”, the 34th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2018), Technical Track: Knowledge and Language Processing, Limassol, Cyprus, April 8-12, 2019.

P. Agathangelou, I. Katakis, “A Hybrid Deep Learning Network for Modelling Opinionated Content”, the 34th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2018), Technical Track: Knowledge and Language Processing, Limassol, Cyprus, April 8-12, 2019.

A. Kounoudes, G. Kapitsaki, I. Katakis, “Enhancing user awareness on inferences obtained from fitness trackers data”, User Modeling and User-Adapted Interaction, Springer, 2023.

Alexia Dini Kounoudes, Gerogia Kapitsaki, Ioannis Katakis, Marios Milis, “”User-centred privacy inference detection for smart home devices“”, at the proceedings of the 2021 IEEE Smart World Congress (SmartWorld 2021). ”

A. Gal, D. Gunopulos, V. Kalogeraki, I. Katakis, N. Panagiotou, N. Rivetti and A. Senderovich, “REMI, Reusable Elements for Multi-Level Information Availability“, in the proceedings of the 11th ACM International Conference on Distributed and Event-Based Systems, June 19-23, 2017, Barcelona, Spain (DEBS 2017)

Nikolaos Panagiotou, Nikolas Zygouras, Ioannis Katakis, Dimitrios Gunopulos, Nikos Zacheilas, Ioannis Boutsis, Vana Kalogeraki, Stephen Lynch, Brendan O’Brien: Intelligent Urban Data Monitoring for Smart Cities. ECML/PKDD (3) 2016: 177-192

A. Saravanou, I. Katakis, G. Valkanas, V. Kalogeraki, D. Gunopulos, “Detection and Delineation of Events and Sub-Events in Social Networks”, 34th International Conference on Data Engineering, Paris France, April 16th-19th, 2018 (ICDE 2018).

A. Saravanou, I. Katakis, G. Valkanas, V. Kalogeraki, D. Gunopulos, Revealing the Hidden Links in Content Networks: An Application to Event Discovery, International Conference on Information and Knowledge Management, 6-10 Nov 2017, Singapore, CIKM 2017.

I. Litou, V. Kalogeraki, I. Katakis, D. Gunopulos,“Efficient and Timely Misinformation Blocking under varying Cost Constraints“, Online Social Networks and Media, Elsevier, 2017.

Alexandros Theodotou, Athena Stassopoulou: A System for Automatic Classification of Twitter Messages into Categories. CONTEXT 2015: 532-537

P. Agathangelou, I. Katakis, L. Rori, D. Gunopulos and B. Richards, “Understanding Online Political Networks: The case of the far-right and far-left in Greece‘‘, in the proceedings of the 9th International Conference on Social Informatics, Oxford, UK, 13-15 September 2017. SocInfo 2017

Nikolaidis F., Symeonides M. and Trihinas D., 2023. Towards Efficient Resource Allocation for Federated Learning in Virtualized Managed Environments. Future Internet, 15(8), p.261. https://www.mdpi.com/1999-5903/15/8/261

Demetris Trihinas, Michalis Agathocleous, Karlen Avogian and Ioannis Katakis. “FlockAI: A Testing Suite for ML-Driven Drone Applications”, Future Internet 2021, 13, 317. https://doi.org/10.3390/fi13120317

Demetris Trihinas, Michalis Agathocleous, Karlen Avogian. “Composable Energy Modeling for ML-Driven Drone Applications”, TDIS at 9th IEEE International Conference on Cloud Engineering (IC2E 2021), Oct, 2021

Hanna Sababa and Athena Stassopoulou, “A Classifier to Distinguish Between Cypriot Greek and Standard Modern Greek“, Proceedings of the Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS) 2018, Valencia, pp. 251-255.

Trihinas, D., Thamsen, L., Beilharz, J., and Symeonides, M. Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. In 2022 IEEE International Conference on Cloud Engineering (IC2E), pp. 29-35. IEEE, 2022. https://lauritzthamsen.org/assets/texts/TrihinasThamsen_2023_TowardsEnergyAwareMachineLearningInGeoDistributedIoTSettings.pdf

Julie Durand, Athena Stassopoulou, Ioannis Katakis, “Adverse Drug Reaction Classification in Social Media: A Multi-label Approach”, The 22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology, October 26-29, 2023, Venice, Italy. http://ailab.unic.ac.cy/wp-content/uploads/2023/10/adverse_drug_reaction-1.pdf

Moysiadis, T., Koparanis, D., Liapis, K., Ganopoulou, M., Vrachiolias, G., Katakis, I., Moyssiadis, C., Vizirianakis, I. S., Angelis, L., Fokianos, K., & Kotsianidis, I. (2023). A personalized stepwise dynamic predictive algorithm of the time to first treatment in chronic lymphocytic leukemia. IScience, 26(9), 107591. https://doi.org/10.1016/j.isci.2023.107591

T. Moysiadis, D. Koparanis, K. Liapis, M. Ganopoulou, G. Vrachiolias, I. Katakis, C. Moyssiadis, I. Vizirianakis, L. Angelis, K. Fokianos, I. Kotsianidis, “A novel personalized stepwise dynamic predictive algorithm in Chronic Lymphocytic Leukemia”, 35th Panhellenic and 1st International Statistics Conference “Statistics in Health Sciences” (Poster Presentation), Athens, May, 25 – 28, 2023

A. Triantafyllidis, S. Segkouli, S. Zygouris, C. Michailidou, K. Avgerinakis, E. Fappa, S. Vassiliades, A. Bougea, N. Papagiannakis, I. Katakis, E. Mathioudis, A. Sorici, L. Bajenaru, V. Tageo, F. Camonita, C. Magga-Nteve, S. Vrochidis, L. Pedullà, G. Brichetto, P. Tsakanikas, K. Votis, D. Tzovaras. Mobile App Interventions for Parkinson’s Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review. Sensors 2023, 23(7): 3396, 2023.

C. Maga-Nteve, E. Kontopoulos, N. Tsolakis, P. Mitzias, I. Katakis, E. Mathioudis, K. Avgerinakis, G. Meditskos, A. Karakostas, S. Vrochidis and I. Kompatsiaris, “A Semantic Technologies Toolkit for Bridging Early Diagnosis and Treatment in Brain Diseases – Report from the Ongoing EU-funded Research Project ALAMEDA“, in proceedings of Metadata and Semantics Research Conference, Springer, Madrid, 2021

Kalia Orphanou, Athena Stassopoulou, Elpida T. Keravnou: DBN-Extended: A Dynamic Bayesian Network Model Extended With Temporal Abstractions for Coronary Heart Disease Prognosis. IEEE J. Biomedical and Health Informatics 20(3): 944-952 (2016)

Kalia Orphanou, Arianna Dagliati, Lucia Sacchi, Athena Stassopoulou, Elpida Keravnou, Riccardo Bellazzi: Combining Naive Bayes Classifiers with Temporal Association Rules for Coronary Heart Disease Diagnosis. ICHI 2016: 81-92

Kalia Orphanou, Athena Stassopoulou, Elpida Keravnou: Risk Assessment for Primary Coronary Heart Disease Event Using Dynamic Bayesian Networks. AIME 2015: 161-165

Kalia Orphanou, Athena Stassopoulou, Elpida Keravnou: Temporal abstraction and temporal Bayesian networks in clinical domains: A survey. Artificial Intelligence in Medicine 60(3): 133-149 (2014)

Kalia Orphanou, Athena Stassopoulou, Elpida Keravnou: Integration of Temporal abstraction and Dynamic Bayesian Networks for Coronary Heart Diagnosis. STAIRS 2014: 201-210

Symeonides M., Trihinas D., Pallis G. and Dikaiakos M.D., 2023, August. SparkEdgeEmu: An Emulation Framework for Edge-Enabled Apache Spark Deployments. In European Conference on Parallel Processing (pp. 154-168). Cham: Springer Nature Switzerland. http://ailab.unic.ac.cy/wp-content/uploads/2023/10/2023-EuroPar-Sparkemu.pdf

Zacharias Georgiou, Chryssis Georgiou, George Pallis, Elad Michael Schiller and Demetris Trihinas, “A Self-stabilizing Control Plane for Fog Ecosystems”, In Proceedings of the 13th IEEE/ACM International Conference on Utility and Cloud Computing (UCC2020), London, UK, Dec 2020.

Moysis Symeonides, Zacharias Georgiou, Demetris Trihinas, George Pallis, Marios Dikaiakos, “Fogify: A Fog Computing Emulation Framework”, In Proceedings of the 5th ACM/IEEE Symposium on Edge Computing (SEC ’20), San Jose, CA, USA Association for Computing Machinery, New York, NY, USA, 2020.

Moysis Symeonides, Zacharias Georgiou, Demetris Trihinas, George Pallis, Marios Dikaiakos, “[Best Demo] Emulating Geo-Distributed Fog Services”, In Proceedings of the 5th ACM/IEEE Symposium on Edge Computing (SEC ’20), San Jose, CA, USA Association for Computing Machinery, New York, NY, USA, 2020.

Trihinas, Demetris. “Interoperable Data Extraction and Analytics Queries over Blockchains.” Transactions on Large-Scale Data and Knowledge-Centered Systems XLV. Springer, Berlin, Heidelberg, 2020. 1-26.

M. Symeonides, D. Trihinas, Z. Georgiou, G. Pallis, M. Dikaiakos, “Query-Driven Descriptive Analytics for IoT and Edge Computing“, in the proceedings of the 2019 IEEE International Conference on Cloud Engineering (IC2E 2019), Prague, Czech Republic, Jun, 2019.

P. Agathangelou, D. Trihinas, I. Katakis, A Multi-Factor Analysis of Forecasting Methods: A Study on the M4 Competition. Data 2020, 5, 41. [link]

D. Trihinas, M. Symeonides, “A Study on Speculative Task Scheduling for Apache Spark in Fog Computing Realms”, In 23rd Pan-Hellenic Conference on Informatics (PCI ’19), November 28–30, 2019, Nicosia, Cyprus. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3368640.

D. Trihinas, “Datachain: A Query Framework for Blockchains.”, In Proceedings of the 11th International Conference on Management of Digital EcoSystems (ACM MEDES 2019), Nov, 2019.

P. Agathangelou, D. Trihinas, I. Katakis, “Correlation Analysis of Forecasting Methods: The Case of the M4 Competition“, International Journal of Forecasting (IJF), Special Issue Dedicated to the results of the M4 Competition, Elsevier, 2019.