Nguyen Thi Oanh

Lecturer, Department of Computer Science

Ph.D. (Computer Science, Nancy 2 University, France, 2010)
M.S. (Hanoi University of Technology – Institute de la Francophonie pour l’Informatique, 2004)
B.S. (Hanoi University of Technology, Hanoi, Vietnam, 2001)

• Computer Vision
• Content-based Retrieval

• Object detection and recognition
• Human Action Recognition
• Multimedia Information Retrieval

THI-OANH NGUYEN is an assistant professor of Computer Science at the School of Information and Communications Technology, Hanoi University of Science and Technology. She received her PhD in computer science in 2010 from Nancy 2 University, France. She has extensive experience in teaching courses on image processing and computer vision for undergraduate and graduate students. Her current research interests include image/video representation for content-based image retrieval, semantic segmentation, domain adaptation and human action recognition. She is a (co-)author of scientific papers and has participated in R&D projects funded by various national and international associations such as NAFOSTED, NICOP, AFORS, VINIF, NAVER and HUST. Furthermore, she is a member of the Vietnamese Association for Pattern Recognition (VAPR). She also serves on program committees and acts as a reviewer for many national and international conferences/journals.

• Ngo-Kien Duong, Thi-Oanh Nguyen, and Viet-Sang Dinh. 2023. MCLDA: Multi-level Contrastive Learning for Domain Adaptive Semantic Segmentation. In Proceedings of the 12th International Symposium on Information and Communication Technology (SOICT ’23). Association for Computing Machinery, New York, NY, USA, 343–350. https://doi.org/10.1145/3628797.3628938
• Tung Nguyen Quang and Thi-Oanh Nguyen. 2023. Language Knowledge-Assisted in Topology Construction for Skeleton-Based Action Recognition. In Proceedings of the 12th International Symposium on Information and Communication Technology (SOICT ’23). Association for Computing Machinery, New York, NY, USA, 443–449. https://doi.org/10.1145/3628797.3629008
• H. -H. Nguyen and T. -O. Nguyen, “HRSeg: Leveraging High-Resolution Images to Enhance Polyp Segmentation Quality,” 2023 15th International Conference on Knowledge and Systems Engineering (KSE), Hanoi, Vietnam, 2023, pp. 1-4, doi: 10.1109/KSE59128.2023.10299503.
• N. D. Manh et al., “EndoUNet: A Unified Model for Anatomical Site Classification, Lesion Categorization and Segmentation for Upper Gastrointestinal Endoscopy,” 2022 14th International Conference on Knowledge and Systems Engineering (KSE), Nha Trang, Vietnam, 2022, pp. 1-6, doi: 10.1109/KSE56063.2022.9953766.
• Nguyen Tuan Hung, Phan Ngoc Lan, Nguyen Thi Oanh, Nguyen Thi Thuy, and Dinh Viet Sang. 2022. GCEENet: A Global Context Enhancement and Exploitation for Medical Image Segmentation. In Advances in Visual Computing: 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part II. Springer-Verlag, Berlin, Heidelberg, 141–152. https://doi.org/10.1007/978-3-031-20716-7_11
• K. D. Nam et al., “A Coarse-to-fine Unsupervised Domain Adaptation Method for Cross-Mode Polyp Segmentation,” 2022 14th International Conference on Knowledge and Systems Engineering (KSE), Nha Trang, Vietnam, 2022, pp. 1-6, doi: 10.1109/KSE56063.2022.9953621.
• Nguyen Viet Manh, Kieu Dang Nam, Dinh Viet Sang, Thi-Oanh Nguyen, G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation, Procedia Computer Science, Volume 207, 2022, Pages 2698-2707, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2022.09.328.
• K. D. Nam, T. M. Nguyen, T. V. Dieu, M. Visani, T. -O. Nguyen and D. V. Sang, “A Novel Unsupervised Domain Adaption Method for Depth-Guided Semantic Segmentation Using Coarse-to-Fine Alignment,” in IEEE Access, vol. 10, pp. 101248-101262, 2022, doi: 10.1109/ACCESS.2022.3205414.
• N. T. Duc, N. T. Oanh, N. T. Thuy, T. M. Triet and V. S. Dinh, “ColonFormer: An Efficient Transformer Based Method for Colon Polyp Segmentation,” in IEEE Access, vol. 10, pp. 80575-80586, 2022, doi: 10.1109/ACCESS.2022.3195241.
• Hoang-Thuyen Nguyen and Thi-Oanh Nguyen. 2021. Attention-based network for effective action recognition from multi-view video. Procedia Comput. Sci. 192, C (2021), 971–980. https://doi.org/10.1016/j.procs.2021.08.100
• Anh-Vu Bui, Thi-Oanh Nguyen, Multi-view Human Action Recognition Based on TSN Architecture Integrated with GRU, Procedia Computer Science, Volume 176, 2020, Pages 948-955, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2020.09.090.
• X. Bui, H. Vu, O. Nguyen and K. Than, “MAP Estimation With Bernoulli Randomness, and Its Application to Text Analysis and Recommender Systems,” in IEEE Access, vol. 8, pp. 127818-127833, 2020, doi: 10.1109/ACCESS.2020.3008534. 

• Best paper award. The Seventh International Symposium on Information and Communication Technology (SoICT 2016).
• Poitou-Charentes regional scholarship: invited researcher, 2014
• French government scholarships (Bourses du gouvernement francais – BGF),2006-2009
• Lorraine regional scholarships, 2006-2009

• IT3090: Database
• IT3290/IT3290E: Database Lab
• IT4851: Multimedia Database System
• IT4090Q: Image Processing
• IT4343E / IT5409: Computer Vision

• Unsupervised Domain Adaptation Techniques for Scene Understanding