Dr Emilija Strelcenia
- strelceniae at bournemouth dot ac dot uk
- PGR
Biography
Dr Emilija Strelcenia has completed her PhD Research under the title "A New Generative Adversarial Network for Improving Classification Performance for Imbalanced Data" at the Bournemouth University.
Prior to this achievement, she earned a degree in computer security and forensics, fostering a strong passion for AI, Cybersecurity, and Internet Crime Prevention through ongoing research pursuits.
She has presented her findings to a variety of audiences, including conferences and corporate meetings, as well as publishing in peer-reviewed journals. Her accomplishments have been recognized by numerous conferences, including IEEE 2022 The Third International Conference on Artificial Intelligence Technology (CAIT 2022), IEEE 2022 12th International Conference on Power and Energy Systems (ICPES 2022) and IEEE 2022 3rd International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA '22). She has earned several awards in acknowledgement of her invaluable contributions.
Research
A New Generative Adversarial Network for Improving Classification Performance for Imbalanced Data
Favourites
- Strelcenia, E. and Prakoonwit, S., 2023. Improving Cancer Detection Classification Performance Using GANs in Breast Cancer Data. IEEE Access, 11, 71594-71615.
Journal Articles
- Strelcenia, E. and Prakoonwit, S., 2023. Effective Feature Engineering and Classification of Breast Cancer Diagnosis: A Comparative Study. BioMedInformatics, 3 (3), 616-631.
- Strelcenia, E. and Prakoonwit, S., 2023. Improving Classification Performance in Credit Card Fraud Detection by Using New Data Augmentation. AI (Switzerland), 4 (1), 172-198.
- Strelcenia, E. and Prakoonwit, S., 2023. A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection. Machine Learning and Knowledge Extraction, 5 (1), 304-329.
- Strelcenia, E. and Prakoonwit, S., 2023. Improving Cancer Detection Classification Performance Using GANs in Breast Cancer Data. IEEE Access, 11, 71594-71615.
Conferences
- Strelcenia, E. and Prakoonwit, S., 2023. A New GAN-based data augmentation method for Handling Class Imbalance in Credit Card Fraud detection. Proceedings of the 10th International Conference on Signal Processing and Integrated Networks, SPIN 2023, 627-634.
- Strelcenia, E. and Prakoonwit, S., 2022. Comparative Analysis of Machine Learning Algorithms using GANs through Credit Card Fraud Detection. In: 2022 International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA) 15-16 December 2022 Skopje, North Macedonia. Proceedings - 2022 International Conference on Computing, Networking, Telecommunications and Engineering Sciences Applications, CoNTESA 2022, 1-5.
- Strelcenia, E. and Prakoonwit, S., 2022. GAN-based Data Augmentation for Credit Card Fraud Detection. Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022, 6812-6814.
- Strelcenia, E. and Prakoonwit, S., 2022. Generating Syntetic Data for Credit Card Fraud Detection Using GANs. 2022 International Conference on Computers and Artificial Intelligence Technologies, CAIT 2022, 42-47.
Theses
- Strelcenia, D.E., 2023. A New Generative Adversarial Network for Improving Classification Performance for Imbalanced Data. PhD Thesis. Bournemouth University, Faculty of Science and Technology.
Honours
- Best Paper Award (IEEE International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications 2022 (IEEE CoNTESA '22), 2022)
- Excellent presentation (IEEE International Conference on Power and Energy Systems (ICPES 2022), 2022)
- Significant contribution and best presentation selected of the conference (IEEE 2022 International Conference on Computers and Artificial Intelligence Technologies (CAIT), 2022)