Dr. Fangli Ying is a senior lecturer in the Department of Computer Science at East China University of Science and Technology (ECUST). He undertakes the supervision of both Master's and PhD students, serving as the co-supervisor for three international PhD students and the supervisor for 11 MSc students. Additionally, he holds the position of a visiting scholar at the International College of Digital Innovation, Chiang Mai University (CMU), Thailand. His research focuses on the development of industrial applications of artificial intelligence, leveraging multidisciplinary approaches to address complex industrial challenges. He actively collaborates with multiple labs at ECUST, including the State Key Laboratory of Bioreactor Engineering, the Department of Finance, and the National Engineering Laboratory for Big Data Distribution and Exchange Technologies. His academic contributions are evidenced by numerous publications in prestigious journals and conferences, such as IEEE transactions, Applied Intelligence, Neural Computing and Applications, and ICME. Dr. Ying previously received the Best Runner-up Award from ACM SIGSPATIAL GIS conference and the ESRI European scholar Award. Dr. Ying has previously been honored with the Best Runner-up Award at the ACM SIGSPATIAL GIS conference and the ESRI European Scholar Award. His current research interests span across Computer Vision, Reinforcement Learning for Portfolio Management, and Bioinformatics.

- Deep Learning and Computer Vision (Generative Models, Few-shot Learning, Computational Aesthetics)

- Bioinformatics (Computational Design of Proteins [e.g., AMPs, Nanoantibodies] and Industrial Fermentation Bioprocessing)

- Reinforcement Learning and Algorithmic Trading in Finance

l  Jiang, Jieru, Fangli Ying, and Riyad Dhuny. Unveiling Technological Evolution with a Patent-Based Dynamic Topic Modeling Framework: A Case Study of Advanced 6G Technologies. Applied Sciences 15, no. 7 (2025): 3783.

l  Dhuny, Riyad, and Fangli Ying. Enhancing Education Accessibility: Portable Microservers for Computer-Based Testing in Resource-Constrained Environments. In 2025 22nd International Learning and Technology Conference (L&T), vol. 22, pp. 36-41. IEEE, 2025.

l  Tao, Zhe, Siva Shankar Ramasamy, Nathee Naktnasukanjn, and Fangli Ying. Assessing competitiveness and complementarity in agricultural trade between China and Cambodia pre-pandemic and post-pandemic. PloS one 20, no. 4 (2025): e0321081.

l  Dhuny, Riyad, Arshad Ahmud Iqbal Peer, Aslam Aly El-Faïdal Saib, Nassirah Laloo, Leila Hafeeza Mohammad Denmamode, Nawaz Ali Mohamudally, and Fangli Ying. Home-Hosted Learning Management System for Online and Blended Learning: A Case Study. In International Conference on Computer Science and Educational Informatization, pp. 328-340. Singapore: Springer Nature Singapore, 2024.

l  Phaphuangwittayakul, Aniwat, Napat Harnpornchai, Fangli Ying, and Jinming Zhang. RailTrack-DaViT: A Vision Transformer-Based Approach for Automated Railway Track Defect Detection. Journal of Imaging 10, no. 8 (2024)

l  Phaphuangwittayakul, Aniwat, Fangli Ying, Yi Guo, Liting Zhou, and Nopasit Chakpitak. Few-shot image generation based on contrastive meta-learning generative adversarial network. The Visual Computer 39, no. 9 (2023): 4015-4028.

l  Phaphuangwittayakul, Aniwat, Fangli Ying, Yi Guo, and Surachai Santisookrat. Adaptive adversarial prototyping network for few-shot prototypical translation. Journal of Visual Communication and Image Representation 94 (2023): 103845.

l  Lebedeva, Irina, Fangli Ying, and Yi Guo. Personalized facial beauty assessment: A meta-learning approach. The Visual Computer 39, no. 3 (2023): 1095-1107.

l  Tao, Zhe, Siva Shankar Ramasamy, and Fangli Ying. Agricultural trade between Malaysia and China: Competitiveness and complementarity. Problems and Perspectives in Management 21, no. 3 (2023): 483.

l  Lebedeva, Irina, Yi Guo, and Fangli Ying. MEBeauty: a multi-ethnic facial beauty dataset in-the-wild. Neural Computing and Applications (2022): 1-15.

l  Phaphuangwittayakul, Aniwat, Yi Guo, Fangli Ying, Ahmad Yahya Dawod, Salita Angkurawaranon, and Chaisiri Angkurawaranon. An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury. Applied Intelligence (2022): 1-19.

l  Phaphuangwittayakul, Aniwat, Yi Guo, Fangli Ying, Wentian Xu, and Zheng Zheng. Self-attention recurrent summarization network with reinforcement learning for video summarization task. In 2021 IEEE International Conference on Multimedia and Expo (ICME), pp. 1-6. IEEE, 2021.

l  Lebedeva, Irina, Yi Guo, and Fangli Ying. Deep facial features for personalized attractiveness prediction. In Thirteenth international conference on digital image processing (ICDIP 2021), vol. 11878, pp. 72-80. SPIE, 2021.

l  Dawod, Ahmad Yahya, Aniwat Phaphuangwittayaku, Fangli Ying, and Salita Angkurawaranon. Adaptive Slices in Brain Haemorrhage Segmentation Based on the SLIC Algorithm. Engineering Letters 29, no. 2 (2021).

l  Phaphuangwittayakul, Aniwat, Yi Guo, and Fangli Ying. Fast adaptive meta-learning for few-shot image generation. IEEE Transactions on Multimedia 24 (2021): 2205-2217.

l  Lebedeva, I., Y. Guo, and F. Ying. Transfer learning adaptive facial attractiveness assessment. In Journal of Physics: Conference Series, vol. 1922, no. 1, p. 012004. IOP Publishing, 2021.

l  Lebedeva, Irina, Yi Guo, and Fangli Ying. MEBeauty: a multi-ethnic facial beauty dataset in-the-wild. Neural Computing and Applications (2022): 1-15.

l  Phaphuangwittayakul, Aniwat, Yi Guo, Fangli Ying, Ahmad Yahya Dawod, Salita Angkurawaranon, and Chaisiri Angkurawaranon. An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury. Applied Intelligence (2022): 1-19.