Personal information

Name: Avar Pentel

Position: Lecturer of Computer Science

CV in ETIS, Google Scholar Profile and ORCID: 0000-0002-3789-2263

Publications

1. Debora Firmino de Souza, Sonia Sousa, Kadri Kristjuhan-Ling, Olga Dunajeva, Mare Roosileht, Avar Pentel, Mati Mõttus, Mustafa Can Özdemir, Žanna Gratšjova (2025). Trust and Trustworthiness from Human-Centered Perspective in HRI -- A Systematic Literature Review
2. Ivleva, N., Pentel, A., Dunajeva, O., Juðtðenko, V. (2024). Deep Learning Based Audio-Visual Emotion Recognition in a Smart Learning Environment. In: Towards a Hybrid, Flexible and Socially Engaged Higher Education (ICL2023): proceedings, Vol 1: 26th International Conference on Interactive Collaborative Learning, Madrid, Spain, 26-29 September 2023. Cham: Springer, 420-431. (Lecture notes in networks and systems; 899). DOI: 10.1007/978-3-031-51979-6_44
3. Ivleva, Natalja; Pentel, Avar; Dunajeva, Olga; Juštšenko, Valeria (2023). Machine Learning Based Emotion Recognition in a Digital Learning Environment. In Learning in the Age of Digital and Green Transition: Proceedings of the 25th International Conference on Interactive Collaborative Learning (ICL2022), Vol. 1: Vienna, Austria 27-30 September 2022. Ed. Auer, M.E., Pachatz, W., Rüütmann, T. Cham: Springer Nature, 405?412. (Lecture Notes in Networks and Systems; 633). DOI: 10.1007/978-3-031-26876-2_38.
4. Avar Pentel, Mihhail Derbnev, Alexander Varushchenkov, Karle Nutonen, Sergei Pavlov (2023) A method for determining the calorific value of oil shale using a statistical distribution graph of digital image elements. Estonian Patent Office. https://patentscope.wipo.int/search/en/detail.jsf?docId=EE403069721&_cid=P10-LYT95X-13727-5
5. Dunajeva, Olga; Pentel, Avar; Maksimova, Natalja (2022). COVID-19’s Impact on the Quality of Educational Process and the Academic Performance as Viewed by IT Students: A Case Study in Text Mining. In : M. E. Auer et al. (Ed.). Mobility for Smart Cities and Regional Development - Challenges for Higher Education. (417-425). Deutschland GmbH: Springer Science and Business Media. (Lecture Notes in Networks and Systems; 389). DOI: 10.1007/978-3-030-93904-5_42.
6. Dunajeva, Olga; Pentel, Avar; Maksimova, Natalja (2022). Computer Science Students Early Drop-Out Prediction Using Machine Learning: A Case Study. In: Michael E. Auer et al. (Ed.). Learning with Technologies and Technologies in Learning. Experience, Trends and Challenges in Higher Education. (523-549). Springer Nature. (Lecture Notes in Networks and Systems; 456). DOI: 10.1007/978-3-031-04286-7_25.
7. Pentel, A.; Kaiva, L.-L. (2020). Predicting students' final test results based on previous grades and demographics. In: 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA): Piraeus, Greece, 15 – 17 July 2020. IEEE, 1-6. DOI: 10.1109/IISA50023.2020.9284401.
8. Maksimova, N.; Pentel, A.; Dunajeva, O. (2020). Predicting First-Year Computer Science Students Drop-Out with Machine Learning Methods: A Case Study. In: Educating Engineers for Future Industrial Revolutions, 1329: 23rd International Conference on Interactive Collaborative Learning, TalTech Mektory, Tallinn, Estonia, 23-25 September 2020. Ed. Auer M.E., Rüütmann T. Cham: Springer, 719-726. (Advances in Intelligent Systems and Computing (AISC); 1329). DOI: 10.1007/978-3-030-68201-9_70
9. Avar Pentel (2018). Predicting User Age by Keystroke Dynamics. Artificial Intelligence and Algorithms in Intelligent Systems pp 336-343, Advances in Intelligent Systems and Computing, vol. 764, Springer.
10. Avar Pentel (2017). High Precision Handedness Detection Based on Short Input Keystroke Dynamics. 8th International Conference on Information, Intelligence, Systems & Applications (IISA), 27-30 Aug. 2017, Larnaca, Cypros, IEEE Digital Library
11. Avar Pentel (2017). Predicting Age and Gender by Keystroke Dynamics and Mouse Patterns. In Proceedings of UMAP'17 Adjunct, Bratislava, Slovakia, July 09-12, 2017, ACM Digital Library
    doi.org/10.1145/3099023.3099105
12. Avar Pentel (2017). Emotions and User Interactions with Keyboard and Mouse. 8th International Conference on Information, Intelligence, Systems & Applications (IISA), 27-30 Aug. 2017, Larnaca, Cypros, IEEE Digital Library.
13. Avar Pentel (2015). Employing Think-Aloud Protocol to Connect User Emotions and Mouse Movements. 6th IEEE International Conference on Information, Intelligence, Systems and Applications (IISA2015), Ionian University, Corfu, Greece, July 6-8, 2015. IEEE Digital Library
14. Avar Pentel (2015). Effect of Different Feature Types on Age based Classification of Short Texts. 6th IEEE International Conference on Information, Intelligence, Systems and Applications (IISA2015), Ionian University, Corfu, Greece, July 6-8, 2015. IEEE Digital Library
15. Avar Pentel (2015). Patterns of Confusion: Using Mouse Logs to Predict User's Emotional State. 5th International Workshop on Personalization Approaches in Learning Environments (PALE 2015) in conjunction with 23rd Conference on User Modelling, Adaptation and Personalization (UMAP 2015). June 30th, 2015, Trinity College, Dublin (Ireland).
16. Avar Pentel (2015). Automatic Age Detection Using Text Readability Features. Workshop on Tools and Technologies in Statistics, Machine Learning and Information Retrieval for Educational Data Mining (SMLIR), in conjuction of The 8th International Conference on Educational Data Mining (EDM 2015), June 26, 2015 - June 29, 2015, Madrid, Spain.
17. Avar Pentel (2015). Employing Relation Between Reading and Writing Skills on Age Based Categorization of Short Estonian Texts. 1st workshop on Deep Content Analytics Techniques for Personalized and Intelligent Services, in conjuction with23rd Conference on User Modelling, Adaptation and Personalization (UMAP 2015). June 30th, 2015, Trinity College, Dublin (Ireland).
18. Avar Pentel (2014) A Comparison of Different Feature Sets for Age-Based Classification of Short Texts

Public Datasets

• Keystroke dynamics dataset labeled by age groups
• Keystroke dynamics dataset labeled by handedness

Work in Progress

• Click target prediction by mouse movements
• What keystorke and mouse dynamics tell about user personality
• Handedness, keystroke and mouse dynamics
• User gaze and mouse movement correlations in different contexts
• Predicting user posture/position by analyzing keystroke dynamics and mouse movements
• How different techology influences keystroke dynamics and mouse patterns

Supervised Master Theses

• E. Egers (2024) Identifying Web Bots Using Mouse Dynamics
• G. Volodin (2024) Reducing Electricity Costs Through the Creation of an Efficient Pump Control System
• A. Andruse (2023) Predicting the Nationality of Computer Users by Keyboard Usage Specifics Using Machine Learning Methods
• V. Rostok (2022) MetaMex NFT Marketplace Platform Development on the Elrond Blockchain
• I. Roos (2022) Sales Forecasting Using Machine Learning Methods: The Case of B2B Company
• P. Tali (2020) Quality Assurance of Chatbots Using an Example From Telia Eesti AS

Topics for supervision

Avar Pentel: Juhendatavad teemad Tallinna Ülikoolis

IEEE
DeCat Workshop (UMAP 2015), Trinity College, Dublin
Toila Gümnaasium