3. MetaEnzyme: Meta Pan-Enzyme Learning for Task-Adaptive Redesign, ACM MULTIMEDIA 2024 (ACMMM 2024).
4. Progressive Multi-Modality Learning for Inverse Protein Folding, ICME 2024 (Oral).
5. CCPL: Cross-modal Contrastive Protein Learning, ICPR 2024.
6. CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment, CVPR 2023 (Highlight/Oral presentation).
7. Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings, ACL 2022.
8. Enhancing Neural Sign Language Translation by Highlighting the Facial Expression Information, Neurocomputing, 2021.
9. A Document-Level Neural Machine Translation Model with Dynamic Caching Guided by Theme-Rheme Information, COLING 2020 (Co-1st Author).
10. An Improved Sign Language Translation Model with Explainable Adaptations for Processing Long Sign Sentences, Computational.
Research Experience
1. National Science and Technology Innovation - '2030 New Generation Artificial Intelligence', Major Project, 2022-2027, Implementation Leader, Westlake University, China.
2. National Science and Technology Innovation, Major Project, 2022-2023, Implementation Leader, Westlake University, China.
Education
Degree: Ph.D. Candidate; School: Westlake University & Zhejiang University; Advisor: Prof. Stan Z. Li; Time: Current; Major: Artificial Intelligence.
Background
Research Interests: AI for Life Science, Multi-Modality, NLP, CV. Biography: Pursuing his Ph.D. at the AI Lab, Westlake University, under the supervision of Chair Prof. Stan Z. Li (IEEE Fellow, IAPR Fellow, Chief Scientist of BioMap). Currently focusing on AI applications in life science, such as AI + protein design, AI + enzyme engineering. Previously worked on NLP, CV, and multi-modality research (e.g., AI for Sign Language Translation) at NLP Lab, Xiamen University. During his Ph.D., he has received several major honors, including the Westlake Dean's Award and the National Scholarship of Zhejiang University.