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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.  

 

 

Expertise

Engineering & Materials Science
# Labels
# Ontology
# Semantics
Mathematics
# Cultural Heritage
# Libraries
# Ontology
# Ontology Alignment
# Semantics

Organisations

Publications

Recent
Malnatsky, E. , Wang, S., Hindriks, K., & Ligthart, M. (2024). Shaping Relatable Robots: A Child-Centered Approach to Social Personalization. In HRI'24: Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (pp. 127-129). Association for Computing Machinery. https://doi.org/10.1145/3610978.3638374
Wang, S., Kulyk, D., Rikhtehgar, D. J. , Heylen, D., & Rieffe, C. J. (2023). Correlating Eye Gaze with Object to Enrich Cultural Heritage Knowledge Graph. CEUR workshop proceedings, 3632.
Javdani Rikhtehgar, D. , Wang, S. , Heylen, D. K. J., & Rieffe, C. (2023). diVRsity: exploring diversity in VR. Abstract from ICT Open 2023, Utrecht, Netherlands.
Javdani Rikhtehgar, D. , Wang, S., Schlobach, S. , & Heylen, D. K. J. (2023). Ontology-Based Modeling of User-Environment Interaction in a Virtual Reality Exhibition. In Proceedings 17th International Conference on Metadata and Semantics Research, MTSR 2023 University of Milano-Bicocca.
Wang, S., Li, Q., & Koopman, R. (2023). Co-attention-Based Pairwise Learning for Author Name Disambiguation. In D. H. Goh, S.-J. Chen, & S. Tuarob (Eds.), Leveraging Generative Intelligence in Digital Libraries: Towards Human-Machine Collaboration - 25th International Conference on Asia-Pacific Digital Libraries, ICADL 2023, Proceedings (pp. 240-249). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14458). Springer. https://doi.org/10.1007/978-981-99-8088-8_21
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 (pp. 89-94). (Proceedings - International Conference on Computational Linguistics, COLING). Association for Computational Linguistics (ACL). https://aclanthology.org/2022.sdp-1.10

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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

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Mailing Address

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

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

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University of Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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