Zenun Kastrati

Zenun Kastrati is a Senior Lecturer at the Department of Informatics at Linnaeus University (LNU). Previously, he was associated with the Department of Computer Science and Media Technology at Linnaeus University as a Postdoctoral Research Fellow. Prior to joining LNU in 2018, he worked for more than 9 years as a Lecturer/Researcher at the University of Prishtina, Kosovo. He obtained his PhD from Norwegian University of Science and Technology (NTNU), Norway, in Computer Science in 2018 and a Master degree in Computer Science through the EU TEMPUS Programme developed and implemented jointly by University of Pristina, Kosovo, Université de La Rochelle, France, and Institute of Technology Carlow, Republic of Ireland.

Teaching

Zenun is responsible for the following courses:

1IK143 Introduction to Object Oriented Programming (BSc)
1IK153 Data structures, Databases and Graphical user interfaces with an Object Oriented Programming Language (BSc)
1IK163 Development of Web-based Applications (BSc)
1IK173 Quality Assurance in Information Systems (BSc)

He is also involved in teaching for the courses:

4ME310 Adaptive and Semantic Web (MSc)
1IK424 Web Managment (BSc)

Research

Zenun's research interests focus on the field of artificial intelligence with a special focus on NLP, machine/deep learning, semantic web, sentiment analysis, and learning technologies.

My research groups

Interaction Design Research Group Interaction Design Research Group is an interdisciplinary team, addressing current societal and industrial challenges using ICT solutions through applied research…

My ongoing research projects

Publications

Article in journal (Refereed)

Imran, A.S., Hodnefjeld, H., Kastrati, Z., Fatima, N., Daudpota, S.M., et al. (2023). Classifying European Court of Human Rights Cases Using Transformer-Based Techniques. IEEE Access. 11. 55664-55676.
Status: Published
Rabani, S.T., Khanday, A.M.U.D., Khan, Q.R., Hajam, U.A., Imran, A.S., et al. (2023). Detecting suicidality on social media : Machine learning at rescue. Egyptian Informatics Journal. 24 (2). 291-302.
Status: Published
Kastrati, Z., Imran, A.S., Daudpota, S.M., Memon, M.A., Kastrati, M. (2023). Soaring Energy Prices : Understanding Public Engagement on Twitter Using Sentiment Analysis and Topic Modeling With Transformers. IEEE Access. 11. 26541-26553.
Status: Published
Kadriu, F., Murtezaj, D., Gashi, F., Ahmedi, L., Kurti, A., et al. (2022). Human-annotated dataset for social media sentiment analysis for Albanian language. Data in Brief. 43.
Status: Published
Rawat, A., Wani, M.A., Elaffendi, M., Imran, A.S., Kastrati, Z., et al. (2022). Drug Adverse Event Detection Using Text-Based Convolutional Neural Networks (TextCNN) Technique. Electronics. 11 (20).
Status: Published
Imran, A.S., Yang, R., Kastrati, Z., Daudpota, S.M., Shaikh, S. (2022). The impact of synthetic text generation for sentiment analysis using GAN based models. Egyptian Informatics Journal. 23 (3). 547-557.
Status: Published
Dalipi, F., Jokela, P., Kastrati, Z., Kurti, A., Elm, P. (2022). Going digital as a result of COVID-19 : Insights from students’ and teachers’ impressions in a Swedish university. International Journal of Educational Research Open. 3.
Status: Published
Fatima, N., Imran, A.S., Kastrati, Z., Daudpota, S.M., Soomro, A. (2022). A Systematic Literature Review on Text Generation Using Deep Neural Network Models. IEEE Access. 10. 53490-53503.
Status: Published
Ghafoor, A., Imran, A.S., Daudpota, S.M., Kastrati, Z., Soomro, A., et al. (2021). The Impact of Translating Resource-Rich Datasets to Low-Resource Languages Through Multi-Lingual Text Processing. IEEE Access. 9. 124478-124490.
Status: Published
Batra, R., Imran, A.S., Kastrati, Z., Ghafoor, A., Daudpota, S.M., et al. (2021). Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples's Attitudes toward the Vaccination Drive. Sustainability. 13 (10).
Status: Published
Yar, H., Imran, A.S., Khan, Z.A., Sajjad, M., Kastrati, Z. (2021). Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm. Sensors. 21 (14).
Status: Published
Kastrati, Z., Dalipi, F., Shariq Imran, A., Pireva Nuci, K., Ahmad Wani, M. (2021). Sentiment Analysis of Students’ Feedback with NLP and Deep Learning : A Systematic Mapping Study. Applied Sciences. 11 (9).
Status: Published
Shaikh, S., Daudpota, S.M., Imran, A.S., Kastrati, Z. (2021). Towards Improved Classification Accuracy on Highly Imbalanced Text Dataset Using Deep Neural Language Models. Applied Sciences. 11 (2). 1-20.
Status: Published
Kastrati, Z., Ahmedi, L., Kurti, A., Kadriu, F., Murtezaj, D., et al. (2021). A Deep Learning Sentiment Analyser for Social Media Comments in Low-Resource Languages. Electronics. 10 (10).
Status: Published
Imran, A.S., Daudpota, S.M., Kastrati, Z., Batra, R. (2020). Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets. IEEE Access. 8. 181074-181090.
Status: Published
Kastrati, Z., Kurti, A., Imran, A.S. (2020). WET : Word embedding-topic distribution vectors for MOOC video lectures dataset. Data in Brief. 28. 1-6.
Status: Published
Kastrati, Z., Imran, A.S., Kurti, A. (2020). Weakly Supervised Framework for Aspect-Based Sentiment Analysis on Students' Reviews of MOOCs. IEEE Access. 8. 106799-106810.
Status: Published
Kastrati, Z., Imran, A.S., Kurti, A. (2019). Integrating word embeddings and document topics with deep learning in a video classification framework. Pattern Recognition Letters. 128. 85-92.
Status: Published
Kastrati, Z., Imran, A.S., Yayilgan, S.Y. (2019). The impact of deep learning on document classification using semantically rich representations. Information Processing & Management. 56 (5). 1618-1632.
Status: Published
Kastrati, Z., Imran, A.S. (2019). Performance analysis of machine learning classifiers on improved concept vector space models. Future generations computer systems. 96. 552-562.
Status: Published
Kastrati, Z., Imran, A.S., Yildirim-Yayilgan, S. (2016). SEMCON : a semantic and contextual objective metric for enriching domain ontology concepts. International Journal on Semantic Web and Information Systems. 12 (2). 1-24.
Status: Published

Conference paper (Refereed)

Dalipi, F., Kastrati, Z., Öberg, T. (2023). The Impact of Artificial Intelligence on Tourism Sustainability : A Systematic Mapping Review. 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), Dubai, United Arab Emirates. 119-125.
Uzairi, A., Kurti, A., Kastrati, Z. (2023). A Deep Learning-based Solution for Identification of Figurative Elements in Trademark Images. 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). 1-7.
Ali, S., Imran, A.S., Kastrati, Z., Daudpota, S.M. (2023). Visualizing Research on Explainable Artificial Intelligence for Medical and Healthcare. 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) : 17-18 March 2023, Sukkur, Pakistan. 1-6.
Kastrati, M., Biba, M., Imran, A.S., Kastrati, Z. (2022). Sentiment Polarity and Emotion Detection from Tweets Using Distant Supervision and Deep Learning Models. Foundations of Intelligent Systems. ISMIS 2022. 13-23.
Dalipi, F., Ferati, M., Kurti, A., Kastrati, Z. (2022). Investigating the FAIRness of Science and Technology Open Data : A Focus in the Scandinavian Countries. HCI International 2022 Posters. HCII 2022. : 24th International Conference on Human-Computer Interaction, HCII 2022, Virtual Event, June 26 – July 1, 2022, Proceedings, Part I. 276-283.
Edalati, M., Imran, A.S., Kastrati, Z., Daudpota, S.M. (2022). The Potential of Machine Learning Algorithms for Sentiment Classification of Students’ Feedback on MOOC. Intelligent Systems and Applications : Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1. 11-22.
Kurti, A., Dalipi, F., Ferati, M., Kastrati, Z. (2021). Increasing the Understandability and Explainability of Machine Learning and Artificial Intelligence Solutions : A Design Thinking Approach. Human Interaction, Emerging Technologies and Future Applications : Proceedings of the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2021), April 28-30, 2021, Strasbourg, France. 37-42.
Rääf, S.A., Knöös, J., Dalipi, F., Kastrati, Z. (2021). Investigating Learning Experience of MOOCs Learners Using Topic Modeling and Sentiment Analysis. 19th International Conference on Information Technology Based Higher Education and Training (ITHET). 1-7.
Kastrati, Z., Arifaj, B., Lubishtani, A., Gashi, F., Nishliu, E. (2020). Aspect-Based Opinion Mining of Students’ Reviews on Online Courses. Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence. 510-514.
Ferati, M., Dalipi, F., Kastrati, Z. (2020). Open Government Data Through the Lens of Universal Design. Universal Access in Human-Computer Interaction. Applications and Practice : 14th International Conference, UAHCI 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part II. 331-340.
Imran, A.S., Kastrati, Z., Svendsen, T.K., Kurti, A. (2019). Text-Independent Speaker ID Employing 2D-CNN for Automatic Video Lecture Categorization in a MOOC Setting. 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI). 273-277.
Kastrati, Z., Kurti, A., Hagelbäck, J. (2019). The Effect of a Flipped Classroom in a SPOC : Students' Perceptions and Attitudes. ICETC 2019: Proceedings of the 2019 11th International Conference on Education Technology and Computers. 246-249.
Kastrati, Z., Imran, A.S., Kurti, A. (2019). Transfer Learning to Timed Text Based Video Classification Using CNN. Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics.
Imran, A.S., Dalipi, F., Kastrati, Z. (2019). Predicting Student Dropout in a MOOC : An Evaluation of a Deep Neural Network Model. Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence. 190-195.
Imran, A.S., Kastrati, Z., Svendsen, T.K., Kurti, A. (2019). Text-Independent Speaker ID for Automatic Video Lecture Classification Using Deep Learning. Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence, April 19-22, 2019, Bali, Indonesia. 175-180.
Dalipi, F., Imran, A.S., Kastrati, Z. (2018). MOOC Dropout Prediction Using Machine Learning Techniques : Review and Research Challenges. Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON) - Emerging Trends and Challenges of Engineering Education. 1007-1014.
Kastrati, Z., Yayilgan, S.Y. (2017). Supervised Ontology-Based Document Classification Model. Proceedings of the International Conference on Compute and Data Analysis, ICCDA'17. 245-251.
Kastrati, Z., Yayilgan, S.Y. (2017). Improving document classification effectiveness using knowledge exploited by ontologies. Natural language processing and information systems : 22nd International Conference on Applications of Natural Language to Information Systems, NLDB 2017, Liège, Belgium, June 21-23, 2017, Proceedings. 435-438.
Imran, A.S., Kastrati, Z. (2016). Pedagogical document classification and organization using domain ontology. Learning and Collaboration Technologies : Third International Conference, LCT 2016, Held as Part of HCI International 2016, Toronto, ON, Canada, July 17-22, 2016, Proceedings. 499-509.
Kastrati, Z., Yayilgan, S.Y., Hjelsvold, R. (2016). Automatically Enriching Domain Ontologies for Document Classification. WIMS '16 : Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics. 1-4.
Kastrati, Z., Imran, A.S., Yayilgan, S.Y. (2015). An improved concept vector space model for ontology based classification. 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS). 240-245.
Kastrati, Z., Imran, A.S., Yayilgan, S.Y. (2015). A General Framework for Text Document Classification Using SEMCON and ACVSR. Human Interface and the Management of Information. Information and Knowledge Design : HIMI 2015. 310-319.
Kastrati, Z., Imran, A.S. (2015). Document image classification using SEMCON. 2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA). 1-6.
Dalipi, F., Yayilgan, S.Y., Kastrati, Z. (2015). Enhancing the Learner’s Performance Analysis Using SMEUS Semantic E-learning System and Business Intelligence Technologies. Learning and Collaboration Technologies. LCT 2015. 208-217.
Kastrati, Z., Imran, A.S., Yayilgan, S.Y. (2015). SEMCON : Semantic and contextual objective metric. Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015). 65-68.
Kastrati, Z., Yayilgan, S.Y., Imran, A.S. (2015). Using Context-Aware and Semantic Similarity Based Model to Enrich Ontology Concepts. Natural Language Processing and Information Systems. 137-143.
Kastrati, Z., Imran, A.S., Yayilgan, S.Y. (2014). Building Domain Ontologies for Hyperlinked Multimedia Pedagogical Platforms. HCI International 2014 - Posters’ Extended Abstracts : International Conference, HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings, Part II. 95-100.
Kastrati, Z., Imran, A.S. (2014). Adaptive Concept Vector Space Representation Using Markov Chain Model. Knowledge Engineering and Knowledge Management : 19th International Conference, EKAW 2014, Linköping, Sweden, November 24-28, 2014. Proceedings. 203-208.
Picovici, D., Denieffe, D., Kastrati, Z. (2010). Subjective-based Quality Assessment for Online Games. Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques. 1-6.

Chapter in book (Other academic)

Kastrati, Z., Imran, A.S., Yildirim-Yayilgan, S. (2018). A Hybrid Concept Learning Approach to Ontology Enrichment. Innovations, Developments, and Applications of Semantic Web and Information Systems. IGI Global. 85-119.