Journal Publications
Employees’ acceptance of AI-based emotion analytics from speech on a group level in virtual meetings
Behn, O., Leyer, M., & Iren, D. (2024). Employees’ acceptance of AI-based emotion analytics from speech on a group level in virtual meetings. Technology in Society, 76, 102466. [PDF]
MILSDeM: Guiding immersive learning system development and taxonomy evaluation
Mat Sanusi, K. A., Majonica, D., Iren, D., Fanchamps, N., & Klemke, R. (2024). MILSDeM: Guiding immersive learning system development and taxonomy evaluation. Education and Information Technologies, 1-34. [PDF]
Multimodal and immersive systems for skills development and education
Di Mitri, D., Limbu, B., Schneider, J., Iren, D., Giannakos, M., & Klemke, R. (2024). Multimodal and immersive systems for skills development and education. British Journal of Educational Technology. [PDF]
Explainable machine learning for predicting the mechanical properties in bainitic steels
Ackermann, M., Iren, D., & Yao, Y. (2023). Explainable machine learning for predicting the mechanical properties in bainitic steels. Materials & Design, 230, 111946. [PDF]
Automated segmentation of martensite-austenite islands in bainitic steel
Ackermann, M., Iren, D., Wesselmecking, S., Shetty, D., & Krupp, U. (2022). Automated segmentation of martensite-austenite islands in bainitic steel. Materials Characterization, 191, 112091. [PDF]
Aachen-Heerlen annotated steel microstructure dataset
Iren, D., Ackermann, M., Gorfer, J., Pujar, G., Wesselmecking, S., Krupp, U., & Bromuri, S. (2021). Aachen-Heerlen annotated steel microstructure dataset. Scientific data, 8(1), 140. [PDF]
Using AI to predict service agent stress from emotion patterns in service interactions
Bromuri, S., Henkel, A. P., Iren, D., & Urovi, V. (2021). Using AI to predict service agent stress from emotion patterns in service interactions. Journal of Service Management, 32(4), 581-611. [PDF]
• Literati award.
Half human, half machine – augmenting service employees with AI for interpersonal emotion regulation
Henkel, A.P., Bromuri, S., Iren, D. and Urovi, V. (2020), "Half human, half machine – augmenting service employees with AI for interpersonal emotion regulation", Journal of Service Management, Vol. 31 No. 2, pp. 247-265. https://doi.org/10.1108/JOSM-05-2019-0160 [PDF]
• Robert Johnston highly commended award.
• Responsible research in business & management honor roll.
Identification and analysis of handovers in organisations using process model repositories
Leyer, M., Iren, D. and Aysolmaz, B. (2020), "Identification and analysis of handovers in organisations using process model repositories", Business Process Management Journal, Vol. 26 No. 6, pp. 1599-1617. https://doi.org/10.1108/BPMJ-01-2019-0041 [PDF]
Cost of Quality in Crowdsourcing
Iren, D., & Bilgen, S. (2014). Cost of Quality in Crowdsourcing. Human Computation, 1(2). https://doi.org/10.15346/hc.v1i2.14 [PDF]
AiOLoS: A model for assessing organizational learning in software development organizations
Chouseinoglou, O., Iren, D., Karagöz, N. A., & Bilgen, S. (2013). AiOLoS: A model for assessing organizational learning in software development organizations. Information and Software Technology, 55(11), 1904-1924. [PDF]
Conference Proceedings
Unilateral Facial Action Unit Detection: Revealing Nuanced Facial Expressions
Iren, D., & Tan, D. S. (2024). Unilateral Facial Action Unit Detection: Revealing Nuanced Facial Expressions. In IEEE Affective Computing and Intelligent Interfaces. [PDF]
Shaping and evaluating a system for affective computing in online higher education using a participatory design and the system usability scale
Shingjergji, K., Urlings, C., Iren, D., & Klemke, R. (2024, March). Shaping and evaluating a system for affective computing in online higher education using a participatory design and the system usability scale. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 382-391). [PDF]
Ethical risks, concerns, and practices of affective computing: a thematic analysis
Iren, D., Yildirim, E., & Shingjergji, K. (2023, September). Ethical risks, concerns, and practices of affective computing: a thematic analysis. In 2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (pp. 1-4). IEEE. [PDF]
Informative Speech Features based on Emotion Classes and Gender in Explainable Speech Emotion Recognition
Yildirim, H. E., & Iren, D. (2023, September). Informative Speech Features based on Emotion Classes and Gender in Explainable Speech Emotion Recognition. In 2023 11th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (pp. 1-8). IEEE. [PDF]
Augmented Reality and Affective Computing for Nonverbal Interaction Support of the Visually Impaired
Iren, D., Shingjergji, K., Böttger, F., Urlings, C., Osinga, J. M., Van De Goor, S., ... & Klemke, R. (2023, March). Augmented Reality and Affective Computing for Nonverbal Interaction Support of the Visually Impaired. In 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (pp. 360-363). IEEE.[PDF]
Interpretable Explainability for Face Expression Recognition
Shingjergi, K., Iren, Y. D., Klemke, R., Urlings, C. C. J., & Böttger, F. (2023, March). Interpretable Explainability for Face Expression Recognition. In The first International Conference on Hybrid Human-Artificial Intelligence. Zenodo.[PDF]
Experts’ evaluation of a proposed taxonomy for immersive learning systems
Sanusi, K. A. M., Iren, D., & Klemke, R. (2022, November). Experts’ evaluation of a proposed taxonomy for immersive learning systems. In International Conference on Games and Learning Alliance (pp. 247-257). Cham: Springer International Publishing.[Source]
IMPECT-Sports: Using an Immersive Learning System to Facilitate the Psychomotor Skills Acquisition Process.
Sanusi, K. A. M., Slupczynski, M., Geisen, M., Iren, D., Klamma, R., Klatt, S., & Klemke, R. (2022, October). IMPECT-Sports: Using an Immersive Learning System to Facilitate the Psychomotor Skills Acquisition Process. In MILeS@ EC-TEL (pp. 34-39).[PDF]
Interpretable explainability in facial emotion recognition and gamification for data collection
Shingjergji, K., Iren, D., Böttger, F., Urlings, C., & Klemke, R. (2022, October). Interpretable explainability in facial emotion recognition and gamification for data collection. In 2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII) (pp. 1-8). IEEE.[PDF]
Privacy-preserving and scalable affect detection in online synchronous learning
Böttger, F., Cetinkaya, U., Di Mitri, D., Gombert, S., Shingjergji, K., Iren, D., & Klemke, R. (2022, September). Privacy-preserving and scalable affect detection in online synchronous learning. In European Conference on Technology Enhanced Learning (pp. 45-58). Cham: Springer International Publishing.[PDF]
Algorithmic Decision Making and Model Explainability Preferences in the Insurance Industry: A Delphi Study
Schotman, E., & Iren, D. (2022, June). Algorithmic Decision Making and Model Explainability Preferences in the Insurance Industry: A Delphi Study. In 2022 IEEE 24th Conference on Business Informatics (CBI) (Vol. 1, pp. 235-242). IEEE.[Source]
Investigating the design opportunities for mood self-tracking and regulating
Overdijk, R., Iren, D., & Karahanoğlu, A. (2022). Investigating the design opportunities for mood self-tracking and regulating.[PDF]
Examining the impact of data augmentation for psychomotor skills training in human-robot interaction
Majonica, D., Klemke, R., & Iren, Y. D. (2021, September). Examining the impact of data augmentation for psychomotor skills training in human-robot interaction. In Sixteenth European Conference on Technology Enhanced Learning: Technology-Enhanced Learning for a Free, Safe, and Sustainable World.[PDF]
Governance and communication of algorithmic decision making: a case study on public sector
Jonk, E., & Iren, D. (2021, September). Governance and communication of algorithmic decision making: a case study on public sector. In 2021 IEEE 23rd Conference on Business Informatics (CBI) (Vol. 1, pp. 151-160). IEEE.[PDF]
A method for objective performance benchmarking of teams with process mining and DEA
Aysolmaz, B., Nemeth, M., & Iren, D. (2021, June). A method for objective performance benchmarking of teams with process mining and DEA. In 29th European Conference on Information Systems (ECIS 2021): Human values crisis in a digitizing world (p. 1773). AIS Electronic Library.[PDF]
Acceptance of AI for delegating emotional intelligence: Results from an experiment
Aysolmaz, B., Leyer, M., & Iren, D. (2021). Acceptance of AI for delegating emotional intelligence: Results from an experiment. In Proceedings of the 54th Hawaii International Conference on System Sciences (pp. 6307-6316).[PDF]
• Best paper candidate.
Applying Scrum in Data Science Projects
Baijens, J., Helms, R., & Iren, D. (2020). Applying Scrum in Data Science Projects. In 2020 IEEE 22nd Conference on Business Informatics (CBI) (Vol. 1, pp. 30-38). IEEE.
[PDF]
Preventing Algorithmic Bias in the Development of Algorithmic Decision-Making Systems: A Delphi Study
Aysolmaz, B., Iren, D., & Dau, N. (2020). Preventing Algorithmic Bias in the Development of Algorithmic Decision-Making Systems: A Delphi Study. In Proceedings of the 53rd Hawaii International Conference on System Sciences.[PDF]
Detecting role inconsistencies in process models
Aysolmaz, B.; Iren, D.; & Reijers, H. A., (2019). "Detecting Inconsistencies in Process Models". in Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research Papers.
https://aisel.aisnet.org/ecis2019_rp/27 [PDF]
Leveraging business process improvement with natural language processing and organizational semantic knowledge
Iren, D., & Reijers, H. A. (2017). Leveraging business process improvement with natural language processing and organizational semantic knowledge. In Proceedings of the 2017 International Conference on Software and System Process (pp. 100-108). [Source]
Using social media to reveal social and collective perspectives on music
Iren, D., Liem, C. C., Yang, J., & Bozzon, A. (2016). Using social media to reveal social and collective perspectives on music. In Proceedings of the 8th ACM Conference on Web Science (pp. 296-300). [PDF]
Cost models of quality assurance in crowdsourcing
Iren, D., & Bilgen, S. (2014). Cost models of quality assurance in crowdsourcing. In 2014 IEEE Fifth International Conference on Communications and Electronics (ICCE) (pp. 504-509). IEEE.
Utilization of synergetic human-machine clouds: a big data cleaning case
Iren, D., Kul, G., & Bilgen, S. (2014, June). Utilization of synergetic human-machine clouds: a big data cleaning case. In Proceedings of the 1st International Workshop on CrowdSourcing in Software Engineering (pp. 15-18). [PDF]
An effort prediction model based on BPM measures for process automation
Aysolmaz, B., İren, D., & Demirörs, O. (2013). An effort prediction model based on BPM measures for process automation. In Enterprise, Business-Process and Information Systems Modeling (pp. 154-167). Springer, Berlin, Heidelberg.
Book Chapters
Unpacking collective judging practices in entrepreneurial pitching competitions: a social practice perspective
Hamacher, L., Ormiston, J., & Iren, D. (2022). Unpacking collective judging practices in entrepreneurial pitching competitions: a social practice perspective. In Research Handbook on Entrepreneurship as Practice (pp. 282-283). Edward Elgar Publishing. [Source]
Whitepapers
Eyes on the prize: eye tracking for business value
Hermens, F., & Iren, Y. D. (2023). Eyes on the prize: eye tracking for business value.[PDF]
Digital twins: Virtual representation of physical systems
Iren, Y. D. (2021). Digital twins: Virtual representation of physical systems.[PDF]