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 and research scientist at OCLC, Leiden, Netherlands. Her research interests include cognitive modelling, knowledge representation and reasoning, natural language semantics, text and data mining. She currently focuses on applying NLP and data science technologies to solve problems in the library and other Cultural Heritage domains.

Shenghui has worked at Free University Amsterdam and Wageningen University, exploring Semantic Web and language technologies to improve the semantic interoperability in the domain of cultural heritage and agrifood research. She 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).


Engineering & Materials Science
Cultural Heritage
Ontology Alignment


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, [101143]. 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
Bhowmick, A., Singhal, A. , & Wang, S. (2021). Augmenting context-aware citation recommendations with citation and co-authorship history. In W. Glänzel, S. Heeffer, P-S. Chi, & R. Rousseau (Eds.), 18th International Conference on Scientometrics & Informetrics, ISSI 2021: Proceedings (pp. 115-120). International Society for Scientometrics and Informetrics.
Li, R., Tian, P. , & Wang, S. (2021). Study concept drift in 150-year english literature. CEUR workshop proceedings, 2871, 153-163.
Deichmann, D., Moser, C., Birkholz, J. M., Nerghes, A., Groenewegen, P. , & Wang, S. (2020). Ideas with impact: How connectivity shapes idea diffusion. Research policy, 49(1), [103881]. https://doi.org/10.1016/j.respol.2019.103881
Koopman, R. , Wang, S. , & Englebienne, G. (2019). Fast and discriminative semantic embedding. In S. Dobnik, S. Chatzikyriakidis, & V. Demberg (Eds.), IWCS 2019 - Proceedings of the 13th International Conference on Computational Semantics - Long Papers (pp. 235-246). Association for Computational Linguistics (ACL).
Koopman, R. , & Wang, S. (2019). A two-step approach toward subject prediction. In G. Catalano, C. Daraio, M. Gregori, H. F. Moed, & G. Ruocco (Eds.), 17th International Conference on Scientometrics and Informetrics, ISSI 2019 - Proceedings: 2-5 September 2019 Sapienza University of Rome, Italy (Vol. I, pp. 1038-1043). International Society for Scientometrics and Informetrics.
Wang, S., & Koopman, R. (2019). Embed First, Then Predict. Knowledge Organization, 46(5), 364-370. https://doi.org/10.5771/0943-7444-2019-5-364
Wang, S., Koopman, R. , & Englebienne, G. (2019). Non-Parametric Subject Prediction. In A. Doucet, A. Isaac, K. Golub, T. Aalberg, & A. Jatowt (Eds.), Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, September 9-12, 2019, Proceedings (pp. 312-326). (Lecture Notes in Computer Science; Vol. 11799). Springer. https://doi.org/10.1007/978-3-030-30760-8_27
Castermans, T., Verbeek, K., Speckmann, B., Westenberg, M. A. , Koopman, R. , Wang, S., van den Berg, H., & Betti, A. (2018). SolarView: Low Distortion Radial Embeddings with a Focus. IEEE transactions on visualization and computer graphics, 25(10), 2969-2982. https://doi.org/10.1109/TVCG.2018.2865361

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Affiliated Study Programmes



Courses Academic Year  2022/2023

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses Academic Year  2021/2022

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

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Mailing Address

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