Scholar
Jingyu Hu
Google Scholar ID: XLtLn9wAAAAJ
University of Bristol
Citations & Impact
Citations
75
H-index
3
i10-index
2
Publications
7
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- 1. Hu, J., Yang, M., Du, M., & Liu, W. (2025). Fine-Grained Interpretation of Political Opinions in Large Language Models. arXiv preprint.
- 2. Shu D, Zhao H, Hu J., Liu W., Cheng L. & Du, M. (2025) Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability[J]. arXiv preprint.
- 3. Hu, J., Bo, H., Hong, J., Liu, X., & Liu, W. (2025). Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning. Under-review.
- 4. Hu, J., Liu, W., & Du, M. (2024). Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning. EMNLP 2024.
- 5. Yang, R., Hu, J., Li, Z., Mu, J., Yu, T., Xia, J., … & Xiong, H. (2024). Interpretable machine learning for weather and climate prediction: A review. Atmospheric Environment, 120797.
- 6. Hu, J., Hong, J., Du, M., & Liu, W. (2024). ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups. AEQUITAS ECAI 2024.
- 7. Hu, J., Liang, Y., Zhao, W., McAreavey, K., and Liu, W. (2023) An Interactive XAI Interface with Application in Healthcare for Non-experts. xAI 2023.
- 8. Li, M., Hu, J., and Ho Ryu K. An Efficient Tool for Semantic Biomedical Document Analysis SIST 2021.
- 9. Hu J., Li M,, Zhang Z., et al. An Efficient Semantic Document Similarity Calculation Method Based on Double-Relations in Gene Ontology. FITAT.
Research Experience
- 1. Neural Networks with Bayesian Inference in ICU Data
- 2. Single-cell Differential Analysis with Explainable Machine Learning Models
- 3. Real-time Shanghai Yangshan Port’s AIS analyze .Net system
- 4. National Natural Science Foundation of China Project (No. 61702324), large-scale text mining, ontology-based graph
Education
- 1. PhD, Engineering Mathematics, University of Bristol, EPSRC-DTP funded
- 2. MSc, Data Science
- 3. BSc, Computer Science and Technology
Background
- Currently a second-year PhD candidate in Engineering Mathematics at the University of Bristol, funded by EPSRC-DTP. Research interests broadly include the ethics and trustworthiness (e.g., explainability, fairness) of AI (LLMs, graphs). Holds an MSc in Data Science and a BSc in Computer Science and Technology.
Miscellany
- 1. Languages: Native Chinese; Familiar English (PTE:72); Familiar Japanese (JLPT: N2)
- 2. Programming/Scripting: Python, Java, C#, SQL, C++, Matlab; Pytorch, PEFT
- 3. Tech: AWS, VPS, SpringBoot, HTML, Elastic Search, Android Studio, Git, Neo4j, Mysql, Flask
- 4. Reviewer: ACL, ECAI, AISTATS, AAAI ReLM, Journal of Pattern Recognition, ACM Computing Surveys
Co-authors