Publication

G, Mortensen,Genevieve*,  Zhu, R*. ADetectoLocum: Harnessing Locally Deployable LLMs for Early Alzheimer's Disease Detection Through Voice Analysis. (AMIA informatics summit 2025)

Zhu, R., Tang, D., Tang, S., Wang, Z,. Tao, G., Ma, S., Wang, X., & Tang, H. Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering. (NDSS 2024)

Wang, Z.*, Zhu, R*, Zhou, D., Zhang, Z., Mitchell, J., Tang, H., & Wang, X. DPAdapter: Improving differentially private deep learning through noise tolerance pre-training (USENIX 2024). 

Chen, X.*, Tang, S.*, Zhu, R.*, Yan, S., Jin, L., Wang,. Z., Su, L., Wang, X., & Tang, H. (2023). The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks. (CCS 2024)

Li, Z.*, Zhu, R*, Ziahao, W., Haixu, T., & Hongfeng, C. Fairfix: Improving fairness of deep neural networks through selective amnesia and recovery. (Best Paper Award, SmartCom 2023)

Zhu, R., Tang, D., Tang, S., Wang, X., & Tang, H. (2023). Selective Amnesia: On Efficient, High-Fidelity and Blind Suppression of Backdoor Effects in Trojaned Machine Learning Models. IEEE Security and Privacy (IEEE S&P) 2023.

Li, X., Qin, Y., Zhu, R., Lin, T., Fan, Y., Kang, Y., Song, K., Zhao, F., Sun, C., Tang, H., & Liu, X. (2023). STINMatch: Semi-Supervised Semantic-Topological Iteration Network for Financial Risk Detection via News Label Diffusion. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (pp. 9304-9315). Singapore: Association for Computational Linguistics.

Tang, D., Zhu, R., Wang, X., Tang, H., & Chen, Y. (2022). Understanding Impacts of Task Similarity on Backdoor Attack and Detection. arXiv preprint arXiv:2210.06509.

Li, X., Liu, K., Zhu, R., Kang, Y., Sun, C., Song, K., & Liu, X. (2022, December). Hierarchical Multi-task Learning for Enterprise Risk Detection from Financial Documents. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3505-3508). IEEE.

Zhu, R., Jiang, C., Wang, X., Wang, S., Zheng, H., & Tang, H. (2020). Privacy-preserving construction of generalized linear mixed model for biomedical computation. Intelligent Systems for Molecular Biology(ISMB) 2020

Zhu, R., Lin, B., & Tang, H. (2020). Bounding the number of linear regions in local area for neural networks with relu activations. arXiv preprint arXiv:2007.06803.