dr. S. Wang (Shenghui)

Assistant Professor

About Me

Shenghui Wang is an assistant professor at the Human Media Interaction (HMI) group of the University of Twente. Her research interests include cognitive modeling, knowledge representation and reasoning, natural language semantics, text mining and interactive technologies. Her current research focuses on language technologies that can facilitate interactive communication between human and knowledge, with a special interest in making Cultural Heritage more inclusive and interactive. She is associated with the Hybrid Intelligence Centre and working on designing Hybrid Intelligence systems in general. 

Before joining University of Twente, Shenghui was a Research Scientist at OCLC where she explored the potentials of NLP, Data Science and visualisation technologies to address problems in the library and other Cultural Heritage domains. She also worked at Vrije Universiteit Amsterdam and Wageningen University, exploring Semantic Web and NLP technologies to improve the semantic interoperability in the domains of Cultural Heritage and Agrifood research. 

Shenghui earned a Ph.D in Computer Science from the University of Manchester (Manchester, UK), a Master in Computer Application Technology at the University of Science and Technology of China (Hefei, China), and a Bachelor in Computer Science in Anhui University (Hefei, China).

Check out these student assignments that I am happy to supervise.  




Engineering & Materials Science
Cultural Heritage
Ontology Alignment


Javdani Rikhtehgar, D. , Wang, S., Huitema, H., Alvares, J., Schlobach, S., Rieffe, C. , & Heylen, D. (2023). Personalizing Cultural Heritage Access in a Virtual Reality Exhibition: A User Study on Viewing Behavior and Content Preferences. In UMAP 2023 - Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 379-387). Association for Computing Machinery. https://doi.org/10.1145/3563359.3596666
Chiang, W-H., Ahmad, U. , Wang, S. , & Bukhsh, F. A. (2023). Investigating Aha Moment Through Process Mining. In J. Filipe, M. Smialek, A. Brodsky, & S. Hammoudi (Eds.), Proceedings of the 25th International Conference on Enterprise Information Systems (Vol. 1, pp. 164-172) https://doi.org/10.5220/0011848800003467
Wei, N., Zhao, S., Liu, J. , & Wang, S. (2023). A review for comparative text mining: From data acquisition to practical application. Journal of information science, 1-13. Advance online publication. https://doi.org/10.1177/01655515231165228
Nasri, M., Fang, Z. , Baratchi, M. , Englebienne, G. , Wang, S., Koutamanis, A., & Rieffe, C. (2023). A GNN-based Architecture for Group Detection from spatio-temporal Trajectory Data. In B. Crémilleux, S. Hess, & S. Nijssen (Eds.), Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings (pp. 327-339). (Lecture Notes in Computer Science; Vol. 13876). https://doi.org/10.1007/978-3-031-30047-9_26
Kazi, R., Amato, A. , Wang, S. , & Bucur, D. (2022). Visualization Methods for Diachronic Semantic Shift. In Proceedings of the Third Workshop on Scholarly Document Processing (9 ed., Vol. 29, pp. 89-94). (Proceedings - International Conference on Computational Linguistics, COLING).
Ginammi, A., Koopman, R. , Wang, S., Bloem, J., & Betti, A. (2022). Bolzano, Kant, and the Traditional Theory of Concepts: A Computational Investigation. In G. Ramsey, & A. De Block (Eds.), The Dynamics of Science: Computational Frontiers in History and Philosophy of Science (pp. 186-203). University of Pittsburgh Press. https://doi.org/10.2307/j.ctv31djr2f.14
Kazi, R., Amato, A. , Wang, S. , & Bucur, D. (2022). Visualisation Methods for Diachronic Semantic Shift. In Proceedings of the Third Workshop on Scholarly Document Processing (pp. 89-94). Association for Computational Linguistics (ACL). https://aclanthology.org/2022.sdp-1.10
Wei, N., Zhao, S., Liu, J. , & Wang, S. (2022). A novel textual data augmentation method for identifying comparative text from user-generated content. Electronic commerce research and applications, 53, Article 101143. Advance online publication. https://doi.org/10.1016/j.elerap.2022.101143
Liu, D., Zhu, T., Schlötterer, J. , Seifert, C. , & Wang, S. (2021). Rewriting Fictional Texts Using Pivot Paraphrase Generation and Character Modification. In K. Ekštein, F. Pártl, & M. Konopík (Eds.), Text, Speech, and Dialogue: 24th International Conference, TSD 2021, Olomouc, Czech Republic, September 6-9, 2021 Proceedings (pp. 73-85). (Lecture Notes in Computer Science; Vol. 12848). Springer. https://doi.org/10.1007/978-3-030-83527-9_6

UT Research Information System

Google Scholar Link

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Citadel (building no. 09), room H237
Hallenweg 15
7522NH  Enschede
The Netherlands

Navigate to location

Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Citadel  H237
P.O. Box 217
7500 AE Enschede
The Netherlands

Working days

Week Monday Tuesday Wednesday Thursday Friday
I normally take Wednesday afternoons off.

Social Media