About
Hello, I am an Applied Scientist at Amazon. My current research focuses on Multi-Modal Learning, Retrieval-Augmented Generation (RAG), and AI Agents. I received my Ph.D. degree in Computer & Information Sciences from the University of Delaware in 2024, under the supervision of Dr. Xu Yuan. Before that, I earned my M.S. degree from the University of Louisiana at Lafayette and my B.S. degree from Shandong University.
Education
Ph.D. in Computer Science, 2024.12
University of Delaware, Newark, DE
M.S. in Computer Science, 2023.05
University of Louisiana at Lafayette, Lafayette, LA
B.S. in Software Engineering, 2016.06
Shandong University, Jinan, China
Publications
2025
10. Fudong Lin and Xu Yuan, “Long-Tailed Recognition via Information-Preservable Two-Stage Learning”. In NeurIPS 2025 (Spotlight). [PDF] [Code] [Poster]
9. Tiankuo Chu, Fudong Lin, Shubo Wang, Jason Jiang, Wiley Jia-Wei Gong, Xu Yuan, and Liyun Wang. “BoneMet: An Open Large-Scale Multi-Modal Murine Dataset for Breast Cancer Bone Metastasis Diagnosis and Prognosis”. In ICLR 2025. [PDF] [Dataset] [Code] [PyPI]
8. Fudong Lin, Jiadong Lou, Hao Wang, Brian Jalaian, and Xu Yuan. “Towards Interpretable Adversarial Examples via Sparse Adversarial Attack”. In ECML-PKDD 2025. [PDF] [Code] [Slides] [Poster]
7. Fudong Lin, Wanrou Du, Jinchan Liu, Tarikul Milon, Shelby Meche, Wu Xu, Xiaoqi Qin, and Xu Yuan. “Do Protein Transformers Have Biological Intelligence?”. In ECML-PKDD 2025. [PDF] [Code] [Dataset] [Slides] [Poster]
2024
6. Fudong Lin, Jiadong Lou, Xu Yuan, and Nian-Feng Tzeng. “Towards Robust Vision Transformer via Masked Adaptive Ensemble”. In CIKM 2024. [PDF]
5. Fudong Lin, Kaleb Guillot, Summer Crawford, Yihe Zhang, Xu Yuan, and Nian-Feng Tzeng. “An Open and Large-Scale Dataset for Multi-Modal Climate Change-aware Crop Yield Predictions”. In KDD 2024. [PDF] [Dataset] [Code] [Tutorials] [PyPI]
2023
4. Fudong Lin, Summer Crawford, Kaleb Guillot, Yihe Zhang, Yan Chen, Xu Yuan, Nian-Feng Tzeng, et. al. “MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer”. In ICCV 2023. [PDF] [Code] [Dataset] [Poster]
3. Fudong Lin, Xu Yuan, Yihe Zhang, Li Chen, Purushottam Sigdel, Lu Peng, Nian-Feng Tzeng. “Comprehensive Transformer-based Model Architecture for Real-World Storm Prediction”. In ECML-PKDD 2023. [PDF] [Slides] [Poster]
2022
2. Fudong Lin, Xu Yuan, Lu Peng, and Nian-Feng Tzeng. “Cascade Variational Auto-Encoder for Hierarchical Disentanglement”. In CIKM 2022. [PDF] [Slides]
2021
1. Yi He, Fudong Lin, Xu Yuan, and Nian-Feng Tzeng. “Interpretable Minority Synthesis for Imbalanced Classification”. In IJCAI 2021. [PDF] [Code]
Patents
- Mengjie Wang and Fudong Lin. 2020. “Video playing method, terminal, and computer readable storage medium”. CN 108024144 A, filed November 28, 2017, and issued July 10, 2020. [PDF]
Academic Services
Reviewer
- 2025: ICLR, ICML, CVPR, ICCV, AAAI, KDD
- 2024: CVPR, ECCV, ICLR, ICML, KDD, SDM
- 2023: NeurIPS, ICLR, KDD, NeurIPS AI4Science Workshop
- 2022: ICML, NeurIPS AI4Science Workshop
Honors and Awards
- 2024 CoE Graduate Student Excellence in Research (Nominee), University of Delaware
- 2024 CIS Distinguished Graduate Student Award, issued by University of Delaware
- 2023 Academic Excellence Award, issued by University of Louisiana at Lafayette
- 2022 Academic Excellence Award, issued by University of Louisiana at Lafayette
Contact
Office: Smith Hall, 18 Amstel Ave, Newark, DE 19716
Email: fudong at udel.edu