Zenun Kastrati

Docent

Institutionen för informatik Fakulteten för teknik

zenun.kastrati@lnu.se

0470-70 85 82

070-308 69 16

Zenun Kastrati is an Associate professor 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. His 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.

Undervisning

Zenun is responsible for the following courses:

1IK161 Fundamentals of Programming (BSc)
1IK162 Object Oriented Programming and Data Structures (BSc)
1IK163 Development of Web-based Applications (BSc)
1IK173 Quality Assurance in Information Systems (BSc)
1IK172 Introduction to Data Analytics (BSc)

He is also involved in teaching the courses:

4ME310 Adaptive and Semantic Web (MSc)

Mina forskargrupper

Interaction Design Research Group Interaction Design Research Group är en tvärvetenskaplig forskargrupp. Vi möter aktuella utmaningar i samhället och näringslivet genom tillämpade, forskningsbaserade…

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Mina avslutade forskningsprojekt

Publikationer

Artikel i tidskrift (Refereegranskat)

Fahad, M., Mobeen, N.E., Imran, A.S., Daudpota, S.M., Kastrati, Z., et al. (2025). Deep insights into gastrointestinal health: A comprehensive analysis of GastroVision dataset using convolutional neural networks and explainable AI. Biomedical Signal Processing and Control. 102.
Status: Publicerad
Kastrati, Z., Fatima, S., Kurti, A., Daudpota, S.M., Imran, A.S. (2024). Analyzing and Predicting the Helpfulness of Reviews in MOOCs Context Using Deep Learning. Procedia Computer Science. 246. 772-781.
Status: Publicerad
Kastrati, M., Kastrati, Z., Shariq Imran, A., Biba, M. (2024). Leveraging distant supervision and deep learning for twitter sentiment and emotion classification. Journal of Intelligent Information Systems. 62. 1045-1070.
Status: Publicerad
Zulfiqar, A., Muhammad Daudpota, S., Shariq Imran, A., Kastrati, Z., Ullah, M., et al. (2024). Synthetic Image Generation Using Deep Learning : A Systematic Literature Review. Computational intelligence. 40 (5).
Status: Publicerad
Ahmed, A., Imran, A.S., Manaf, A., Kastrati, Z., Daudpota, S.M. (2024). Enhancing wrist abnormality detection with YOLO : Analysis of state-of-the-art single-stage detection models. Biomedical Signal Processing and Control. 93.
Status: Publicerad
Ahmed, A., Imran, A.S., Kastrati, Z., Daudpota, S.M., Ullah, M., et al. (2024). Learning from the few : Fine-grained approach to pediatric wrist pathology recognition on a limited dataset. Computers in Biology and Medicine. 181.
Status: Publicerad
Fatima, N., Daudpota, S.M., Kastrati, Z., Imran, A.S., Hassan, S., et al. (2023). Improving news headline text generation quality through frequent POS-Tag patterns analysis. Engineering applications of artificial intelligence. 125.
Status: Publicerad
Ghafoor, A., Imran, A.S., Daudpota, S.M., Kastrati, Z., Shaikh, S., et al. (2023). SentiUrdu-1M : A large-scale tweet dataset for Urdu text sentiment analysis using weakly supervised learning. PLOS ONE. 18 (8).
Status: Publicerad
Ali, S., Akhlaq, F., Imran, A.S., Kastrati, Z., Daudpota, S.M., et al. (2023). The enlightening role of explainable artificial intelligence in medical & healthcare domains : A systematic literature review. Computers in Biology and Medicine. 166.
Status: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
Haq, B., Daudpota, S.M., Imran, A.S., Kastrati, Z., Noor, W. (2023). A Semi-Supervised Approach for Aspect Category Detection and Aspect Term Extraction from Opinionated Text. Computers, Materials and Continua. 77 (1). 115-137.
Status: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
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: Publicerad
Kastrati, Z., Imran, A.S. (2019). Performance analysis of machine learning classifiers on improved concept vector space models. Future Generation Computer Systems. 96. 552-562.
Status: Publicerad
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: Publicerad

Konferensbidrag (Refereegranskat)

Ahmed, A., Imran, A.S., Ullah, M., Kastrati, Z., Daudpota, S.M. (2024). Navigating Limitations With Precision : A Fine-Grained Ensemble Approach To Wrist Pathology Recognition On A Limited X-Ray Dataset. 2024 IEEE International Conference on Image Processing (ICIP). 3077-3083.
Akhlaq, F., Ali, S., Imran, A.S., Daudpota, S.M., Kastrati, Z. (2024). Diving Deep into Bone Anomalies on the FracAtlas Dataset Using Deep Learning and Explainable AI. Proceedings of the 2024 International Conference on Engineering & Computing Technologies (ICECT). 1-6.
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.
Kastrati, Z., Kurti, A., Dalipi, F., Ferati, M. (2023). Leveraging Topic Modeling to Investigate Learning Experience and Engagement of MOOC Completers. Methodologies and Intelligent Systems for Technology Enhanced Learning, 13th International Conference : 13th International Conference. MIS4TEL 2023. 54-64.
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.
Taralrud, H.P.F., Salah, A.A., Imran, A.S., Kastrati, Z. (2023). Multimodal Sentiment Analysis for Personality Prediction. 2023 International Conference on Frontiers of Information Technology (FIT). 55-60.
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.
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.
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.
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). 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.
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.
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.

Artikel, forskningsöversikt (Refereegranskat)

Taj, S., Imran, A.S., Kastrati, Z., Daudpota, S.M., Memon, R.A., et al. (2023). IoT-based supply chain management : A systematic literature review. Internet of Things : Engineering Cyber Physical Human Systems. Elsevier. 24.
Status: Publicerad

Kapitel i bok, del av antologi (Övrigt vetenskapligt)

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.