Scholar
Fan Zhang
Google Scholar ID: KbC_-7cAAAAJ
CSE PhD Student, The Chinese University of Hong Kong (CUHK)
Citations & Impact
Citations
182
H-index
5
i10-index
3
Publications
19
Co-authors
5
list available
Publications
Resume (English only)
Academic Achievements
- - Paper accepted by NeurIPS 2025 Datasets and Benchmarks Track: 'CellVerse: Do Large Language Models Really Understand Cell Biology?'
- - Paper accepted by ACL 2025: 'A Survey on Foundation Language Models for Single-cell Biology'
- - Paper accepted by AAAI 2025: 'DREAM: Decoupled Discriminative Learning with Bigraph-aware Alignment for Semi-supervised 2D-3D Cross-modal Retrieval'
- - Paper accepted by NeurIPS 2024: 'Semi-supervised Knowledge Transfer Across Multi-omic Single-cell Data'
- - Paper accepted by TPAMI 2024: 'HOPE: A Hierarchical Perspective for Semi-supervised 2D-3D Cross-Modal Retrieval'
- - Paper accepted by TIP 2024: 'FATE: Learning Effective Binary Descriptors with Group Fairness'
- - Paper accepted by NAACL 2024: 'DEMO: A Statistical Perspective for Efficient Image-Text Matching'
- - Paper accepted by CVPR 2024: 'Fine-grained Prototypical Voting with Heterogeneou'
Research Experience
- - Research Intern at Tongyi Lab, Alibaba Group, starting from April 2025
- - Research Intern at Tencent YouTu Lab, starting from August 2024
Education
- - Ph.D. in Computer Science and Engineering, The Chinese University of Hong Kong, supervised by Prof. Pheng-Ann Heng, from 2025 to present
Background
- - Research Interests: Large Language Models (LLMs), Multimodal AI, and AI for Science, particularly in Healthcare, Life Science, and Cognitive Science.
- - Professional Field: Computer Science and Engineering
- - Brief Introduction: Currently a Ph.D. student at the Department of Computer Science and Engineering, The Chinese University of Hong Kong (CUHK), focusing on post-training, understanding, reasoning, and agentic techniques of LLMs, multimodal understanding, image-text matching, and affective computing, as well as scientific foundation models, especially in healthcare, life science, and cognitive science.
Miscellany
- - Email: fzhang@link.cuhk.edu.hk
- - Wechat: ZF_Karl
