Service-centric Networking
Aikaterini Katsarou
Wissenschaftlicher Werdegang
Katerina Katsarou erhielt ihr Diplom von der Fakultät für Elektrotechnik und Computertechnik-Polytechnische Fakultät der Universität Patras und ihren Master in Informatik von der Universität Ioannina.
Während ihres Studiums besuchte sie Kurse im Bereich Data Mining, Statistische Algorithmen für medizinische Anwendungen und Advanced Topics in Relational Databases. Sie nahm an Forschungsprojekten am Department of Computer Technology and Informatics der University of Patras teil und war Laborassistentin am Department of Computer Science and Engineering der University of Ioannina.
Im Januar 2018 wechselte sie als Forscherin im Bereich Data Science und Machine Learning in die Service-centric Networking-Gruppe von Prof. Dr. Axel Küpper an den Telekom Innovation Laboratories.
Interessen
- Sentiment Analysis
- Context-aware Recommender Systems
- Deep Learning
- Stock market and Cryptocurrency prices forecasting
- Community detection in online social networks
- R, Python, SQL
Preise & Auszeichnungen
- DeepFlow: Towards Network-Wide Ingress Traffic Prediction Using Machine Learning At Large Scale - ISNCC 2020 Best Paper Award (The 2020 International Symposium on Networks, Computers and Communications, Montreal - Canada, October 20 - 22, 2020)
Publikationen
2023
K.
Katsarou,
R.
Jeney and
K.
Stefanidis,
"MUTUAL: Multi-Domain Sentiment Classification via Uncertainty Sampling"
in Proceedings of the 38th ACM/SIGAPP Symposium On Applied Computing (SAC 2023),
ACM (accepted for publication),
2023.
K.
Katsarou,
N.
Douss and
K.
Stefanidis,
"REFORMIST: Hierarchical-Attention Networks for Multi-Domain Sentiment Classification with Active Learning"
in Proceedings of the 38th ACM/SIGAPP Symposium On Applied Computing (SAC 2023),
ACM,
2023.
pp. 919-928.
C.
Landin,
J.
Liu,
K.
Katsarou and
S.
Tahvili,
"Time-series anomaly detection using Convolutional Neural Networks in the manufacturing process"
in Proceedings of the 5th IEEE International Conference on Artificial Intelligence Testing (AITest 2023),
IEEE,
2023.
pp. 90-98.
2022
K.
Katsarou,
G.
Yu and
F.
Beierle,
"WhatsNextApp: LSTM-based Next-App Prediction With App Usage Sequences"
,
IEEE Access,
vol. 10,
pp. 18233-18247,
2022.
IEEE.
2021
H.
Dinh-Tuan,
K.
Katsarou and
P.
Herbke,
"Optimizing Microservices with Hyperparameter Optimization"
in Proceedings of the 17th International Conference on Mobility, Sensing and Networking (MSN2021),
IEEE,
2021.
pp. 685-686.
K.
Katsarou,
S.
Sunder,
K.
Semertzidis and
V.
Woloszyn,
"Sentiment Polarization in Online Social Networks: The Flow of Hate Speech"
in Eighth International Conference on Social Network Analysis, Management and Security (SNAMS 2021),
IEEE,
2021.
pp. 01-08.
2020
T.
Hagemann and
K.
Katsarou,
"A Systematic Review on Anomaly Detection for Cloud Computing Environments"
in 3rd Artificial Intelligence and Cloud Computing Conference (AICCC 2020),
Association for Computing Machinery,
2020.
pp. 83-96.
S.
Fischer,
K.
Katsarou and
O.
Holschke,
"DeepFlow: Towards Network-Wide Ingress Traffic Prediction Using Machine Learning At Large Scale"
in International Symposium on Networks, Computers and Communications (ISNCC 2020),
IEEE,
2020.
pp. 1-8.
T.
Hagemann and
K.
Katsarou,
"Reconstruction-based Anomaly Detection for the Cloud: A Comparison on the Yahoo! Webscope S5 Dataset"
in Proceedings of the 2020 4th International Conference on Cloud and Big Data Computing,
ACM,
2020.
pp. 68–75.
K.
Katsarou,
C.
Ounoughi,
A.
Mouakher and
C.
Nicolle,
"STCMS: A Smart Thermal Comfort Monitor For Senior People"
in 2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE),
IEEE,
2020.
pp. 187-192.
2019
D.
Hatzinikolaou and
K.
Katsarou,
"An Account of Principal Components Analysis and Some Cautions on Using the Correct Formulas and the Correct Procedures in SPSS"
,
International Journal of Statistics and Applications,
vol. 9,
no. 5,
pp. 160-169,
2019.
Scientific & Academic Publishing.
K.
Katsarou and
D. S.
Shekhawat,
"CRD-Sentense: Cross-Domain Sentiment Analysis Using An Ensemble Model"
in Proceedings of the 11th International Conference on Management of Digital EcoSystems (MEDES 2019),
Association for Computing Machinery,
2019.
pp. 88-94.
