ResumeDr. Fangli Ying serves as a Lecturer, Master’s Supervisor and Co-Supervisor of Doctoral Students in the Department of Computer Science, School of Information Engineering, East China University of Science and Technology (ECUST). He also heads the Industry-University-Research Base for postgraduate programs under the Department of Computer Science. His research centers on artificial intelligence and interdisciplinary convergence, addressing practical industrial challenges via cross-disciplinary exploration. His current research directions cover applied computer vision, AI-powered quantum error correction, deep reinforcement learning for portfolio management, and deep generative models for protein and molecular design. He has published numerous papers in top-tier CCF-ranked computer science journals and conferences including ACM MM, TMM, CGF and ICLR. He was honored with the 2025 Wiley China Excellent Author Award (Q4). Dr. Ying acts as a Program Committee (PC) Member and peer reviewer for a portfolio of prestigious journals and conferences such as TIP, TMM, AAAI, ICML, ICLR and NeurIPS, and received the 2026 ICML Gold Reviewer Award. He is a recipient of the Best Paper Award at ACM SIGSPATIAL GIS and the ESRI European Scholar Award. Additionally, he is one of the core organizing committee members for MMM 2027 and ICMR 2028, two top international multimedia conferences recommended by the China Computer Federation (CCF). He has presided over and participated in multiple national and provincial research projects, including key national R&D programs of the Ministry of Science and Technology and National Natural Science Foundation of China (NSFC). To date, he has been granted 10 invention patents. Committed to deep industry-university-research cooperation, he founded the ECUST Quantum + AI Joint Industry-University Innovation Center. The industrial enzyme optimization design project developed through his industrial collaboration was listed among the Top 10 Quantum Computing Application Cases by the Shanghai Science and Technology Commission in 2025. In teaching practice, he actively supervises undergraduate students in scientific research, guiding them to publish multiple papers at flagship conferences. His students were awarded the KDD 2026 Outstanding Undergraduate Student Conference Travel Grant. He coached undergraduate teams to win the National Bronze Award in the Digital Human Reconstruction Enterprise Track of the 2023 Challenge Cup Grand Challenge Program under the Unveil the List and Take Command initiative. During the COVID-19 pandemic, he supported educational development at China University of Petroleum (Beijing) Karamay Campus in Xinjiang through teaching aid programs. His teaching accolades include the First-Class Award of ECUST Teaching Achievement Award and funding for smart curriculum development in 2025, as well as the 2025 Asia-Pacific Excellent AI Educator Award. Research- 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 - AI-driven Quantum Error Correction Publicationsl Ying Fangli, Zhihong Zhang, Liting Zhou, Cathal Gurrin, and Jinhai Wang. Identity Preserving Facial Aesthetic Enhancement via Hierarchical Promt Learning and Pivotal Tuning. In Proceedings of the 33rd ACM International Conference on Multimedia, pp. 10690-10698. 2025. l Yadan Yang, Li Yunzhe, Fangli Ying#, Aniwat Phaphuangwittayakul, and Riyad Dhuny, “Uncertainty-Aware Adjustment via Learnable Coefficients for Detailed 3D Reconstruction of Clothed Humans from Single Images”. Computer Graphics Forum e70239, 2025. l Fangli Ying, Fangli, Wilten Go, Zilong Li, Chaoqian Ouyang, Aniwat Phaphuangwittayakul, and Riyad Dhuny. Computational Design of Potentially Multifunctional Antimicrobial Peptide Candidates via a Hybrid Generative Model. International Journal of Molecular Sciences 26, no. 15 (2025): 7387. 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-Faidal 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, , 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. |
