Tijana Markovic, Postdoctoral research fellow
Tijana obtained her PhD degree in Software Engineering from the Faculty of Ogranizational Sciences, University of Belgrade (Serbia). Her doctoral dissertation "Software tool for investigating structural regression algorithms based on GCRF model" was defended in 2018. During her PhD studies, she was a visiting researcher at the Temple University (Philadelphia, USA), in the Center for Data Analytics and Biomedical Informatics, headed by professor Zoran Obradovic.
Tijana Markovic (former Vujicic), is currently a postdoc in the Division of Computer Science and Software Engineering (CSE). Her main research interests are applied machine learning and artificial intelligence. During her PhD, Tijana was working on structured machine learning for social networks, and more concretely on Gaussian conditional random fields extensions for directed graphs. Currently she is working on machine learning techniques for intrusion and anomaly detection/classification in industrual context.
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Federated Learning for Network Anomaly Detection in a Distributed Industrial Environment (Dec 2023) Alireza Dehlaghi Ghadim, Tijana Markovic, Miguel Leon Ortiz, David Söderman , Per Erik Strandberg International Conference on Machine Learning and Applications 23 (ICMLA'23)
Enhanced Simulation Environment to Support Research in Modular Manufacturing Systems (Oct 2023) Björn Leander, Tijana Markovic, Miguel Leon Ortiz 49th Conference of the IEEE Industrial Electronics Society 2023 (IECON 2023)
An Authorization Service supporting Dynamic Access Control in Manufacturing Systems (Oct 2023) Ivan Radonjic , Enna Basic , Björn Leander, Tijana Markovic IEEE 9th World Forum on Internet of Things 2023 (WFIoT2023)
The Westermo network traffic data set (Oct 2023) Per Erik Strandberg, David Söderman , Alireza Dehlaghi Ghadim, Miquel A. Ribot , Tijana Markovic, Sasikumar Punnekkat, David Buffoni Data In Brief 23 (DIB 23)
Federated Learning for Network Anomaly Detection in a Distributed Industrial Environment (Aug 2023) Alireza Dehlaghi Ghadim, Tijana Markovic, Per Erik Strandberg, David Söderman , Miguel Leon Ortiz International Conference on Machine Learning and Applications 23 (ICMLA'23)
Multi-Objective Optimization on Autoencoder for Feature Encoding and Attack Detection on Network Data (Jul 2023) Miguel Leon Ortiz, Tijana Markovic, Sasikumar Punnekkat Genetic and Evolutionary Computation Conference (GECCO 2023)