Dr Congying (Grace) Guan is a Lecturer in Fashion Management at NTU.
Dr Congying Guan obtained a PhD in Apparel Recommendation System from the School of Design, Northumbria University in 2018, and a BA in Industrial Design from Southwest Jiaotong University in China in 2008. During her PhD, she conducted the feasibility study for prototyping a Novel Apparel Recommendation system that can enhance the customer experience in digital fashion shopping. Prior to joining Northumbria, she was a visiting academic and first-year PhD student at the Computer-Aided Design and Engineering research group, Brunel University where she studied 3D Body Scanning and Clothing Virtual Trying-on. Previously Congying was a part-time lecturer at Chengdu University of Information Technology in China.
Dr Guan’s research has been focusing on design innovations through the emerging technology of AI and Big Data. Her thesis reinterpreted and transformed the fashion communications from the early theories in fashion language and semiotics into an application field in online fashion recommendation system. Three comparative models were designed with differences in machine learning algorithms and apparel data types. As a result, the study found the pros and cons of each model and method as well as the best model with the highest predictability in recognising clothes design and judging semantic meanings, which has exemplified the feasibilities under different conditions.
- Digital Fashion Technology
- Fashion Recommendation System
- Fashion e-retailing
- Online Customer Experience
- Design Innovation
- 2018 - ‘AI in Fashion’ section Chair, the 6th World Conference on Information Systems and Technologies (WorldCIST 2018)
- 2012 - Co-editor, IEEE Proceedings of the 18th International Conference on Automation and Computing (ICAC'12)
- Guan, Congying, Qin, Sheng-feng and Long, Yang (2019) Apparel-based deep learning system design for apparel style recommendation. International Journal of Clothing Science and Technology, 31 (3). pp. 376-389. ISSN: 0955-6222
- Guan, Congying, Qin, Sheng-feng, Ling, Wessie and Long, Yang (2018) Enhancing apparel data based on fashion theory for developing a novel apparel style recommendation system. In: WorldCIST'18 2018, AISC 747 proceedings. Springer, pp. 1–10. ISBN 9783319776996
- Guan, Congying, Qin, Sheng-feng, Ling, Wessie and Ding, Guofu (2016) Apparel Recommendation System Evolution: An empirical review. International Journal of Clothing Science and Technology, 28 (6). pp. 854-879. ISSN 0955-6222
- Guan, Congying and Qin, Sheng-feng (2015) Robotic Stylist: A design oriented apparel recommendation system. In: IASDR2015 INTERPLAY Proceedings. The International Association of Societies of Design Research, Brisbane, pp. 839-850. ISBN 9780646943183
- Wang, Shuxia, Qin, Sheng-feng and Guan, Congying (2014) Feature-Based Human Model for Digital Apparel Design. IEEE Transactions on Automation Science and Engineering, 11(2), 620-626. ISSN 1545-5955
- Wang, Shuxia, Qin, Sheng-feng, Guan, Congying, Yu, Sui Huai (2013) Parametric human body model for digital apparel design. Applied Mechanics and Materials, pp. 121-124
- Qin, Sheng-feng, Chen, Wenhua, Liu, Jiyin and Guan, Congying (2012) Integration of Design and Engineering: Proceedings of the 18th International Conference on Automation and Computing (ICAC '12). Brunel University Press, Uxbridge. ISBN 9781908549006
- Guan, Congying, Xu, Bochu, Qin, Sheng-feng and Wang, Shuxia (2012) A new apparel design and online shopping framework for mass customization and best fit. In: 18th International Conference on Automation and Computing (ICAC), Loughborough, pp. 1-5. ISBN 9781908549006
- Guan, Congying and Xu, Bochu (2010) Research in the structure and form of brand image of high-speed railway. In: IEEE the 11th International Conference on Computer-aided Industrial Design & Conceptual Design (CAID&CD), Yiwu, pp. 52-55. ISBN 9781424479740
- Guan, Congying and Bai, Wenjing (2010) Variables and Invariants in Product Image Design Management: Case Study on the Development of "Swatch". In: International Conference on Optimization Design (ICOD 2010), Wuhan, pp. 425-428. ISBN 9780791859582
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