• Artificial Intelligence
  • Computer Science

PhD

Toan Nguyen

TU Dortmund University
Joseph-von-Fraunhofer-Str.25
Room 225
44227 Dortmund
Germany

Academic Career and Research Areas:

Toan holds an MSc from Hongik University and a BSc in Computer Science from Can Tho University of Technology. Before joining RC Trust - TU Dortmund University, he worked as a researcher at University of Technology Sydney for two years. He also completed an internship at Yuan Ze University through the Taiwanese government-funded IIPP program and was selected as a fellow of the Bridging Divides Future Leaders Fellowship at Toronto Metropolitan University. His achievements were further recognized through the Potential Researcher Award under the Australia–Vietnam Strategic Technologies Scholarship, supported by the Australian Government, Vietnam’s Ministry of Science and Technology, University of Technology Sydney, Posts and Telecommunications Institute of Technology, and Nokia.

His research interests include Brain–Computer Interfaces (BCI), physiological computing, EEG signal processing, and human–computer interaction. His work focuses on neural signal acquisition and analysis, as well as artificial intelligence using physiological sensors and their applications in healthcare, education, robotics, and adaptive human–computer interaction systems.

 

Key Publications:

  1. Toan Nguyen, Le, L., Bai, D., Duong-Trung, N., Do, T., & Lin, C. T. (2025). Transforming Brainwaves into Language: EEG Microstates Meet Text Embedding Models for Dementia Detection. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (pp. 186-202). https://doi.org/10.18653/v1/2025.acl-srw.12
  2. Toan Nguyen, Le, L., Williams-King, D., Tang, Q. H., & Duong-Trung, N. (2026). Explainable AI for Dementia Detection Using EEG Microstates. In Companion Proceedings of the 31st International Conference on Intelligent User Interfaces (pp. 39-42). https://doi.org/10.1145/3742414.3794731
  3. Toan Nguyen, Nguyen, H., Tang, Q. H., Truong, T., Pham, V. T., Le, L., & Williams-King, D. (2025). Learning Disorder Detection Using Eye Tracking: Are Large Language Models Better Than Machine Learning?. In Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (pp. 1-13). https://doi.org/10.1145/3715669.3726785
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