Team
Aayesha Zia
PreDoc Researcher
Aayesha is a Doctoral student and Project assistant at TU Wien. She holds Master Degree in Computer Science. She worked in the areas of Healthcare and Education by employing the recent techniques of Machine Learning, Explainable AI, NLP, and Learning Analytics. Her research interests are to develop tools and systems for providing intelligent recommendations and personalized support to users in diverse domains.
Teaching
Activities & Talks
- Participated in Girl’s Day holding a practical session on Fashion Recommender Systems
Supervisions
Master Thesis
- Comparative Analysis of Fashion Captioning and Multimodal Fashion Recommendation by Gwendolyn Rippberger
Publications
2023
Informative Feedback and Explainable AI-Based Recommendations to Support Students’ Self-regulation Journal Article
In: Technology, Knowledge and Learning, pp. 1–24, 2023.
A Transformer-Based Approach for the Automatic Generation of Concept-Wise Exercises to Provide Personalized Learning Support to Students Proceedings Article
In: European Conference on Technology Enhanced Learning, pp. 16–31, Springer 2023.
2022
Fuzzy-Based Automatic Epileptic Seizure Detection Framework. Journal Article
In: Computers, Materials & Continua, vol. 70, no. 3, 2022.
2021
Explainable AI for data-driven feedback and intelligent action recommendations to support students self-regulation Journal Article
In: Frontiers in Artificial Intelligence, vol. 4, pp. 723447, 2021.
A step towards improving knowledge tracing Proceedings Article
In: 2021 International Conference on Advanced Learning Technologies (ICALT), pp. 38–39, IEEE 2021.
An ensemble approach for question-level knowledge tracing Proceedings Article
In: International Conference on Artificial Intelligence in Education, pp. 433–437, Springer 2021.
Generation of automatic data-driven feedback to students using Explainable Machine Learning Proceedings Article
In: International Conference on Artificial Intelligence in Education, pp. 37–42, Springer 2021.
Automatic and intelligent recommendations to support students’ self-regulation Proceedings Article
In: 2021 International Conference on Advanced Learning Technologies (ICALT), pp. 336–338, IEEE 2021.
A word embeddings based clustering approach for collaborative learning group formation Proceedings Article
In: International Conference on Artificial Intelligence in Education, pp. 395–400, Springer 2021.
Catching Group Criteria Semantic Information When Forming Collaborative Learning Groups Proceedings Article
In: Technology-Enhanced Learning for a Free, Safe, and Sustainable World: 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, Bolzano, Italy, September 20-24, 2021, Proceedings 16, pp. 16–27, Springer 2021.
Machine learning-based EEG signals classification model for epileptic seizure detection Journal Article
In: Multimedia Tools and Applications, vol. 80, pp. 17849–17877, 2021.