I am a Ph.D. student in ECE at Purdue University under the supervision of Prof. Jing Gao. Before coming to Purdue, I spent two wonderful years at University of Michigan to acquire my MS degree in Statistics. Prior to that, I got my BS degree from Xiamen University.
My research spans mitigating harmful biases, enhancing reliablility, and improving efficiency of AI/ML. If you are interested in my work and want to discuss more, feel free to reach out to me via email.
Educations
2021-26 (Expected) Purdue University
Ph.D. in Electrical and Computer Engineering
2019-21 University of Michigan
M.S. in Applied Statistics
2013-17 Xiamen University
B.S. in Statistics
Selected Publications
Here are a few papers that align with my current interests best.
ICLR'25 Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning.
Tianci Liu, Ruirui Li, Yunzhe Qi, Hui Liu, Xianfeng Tang, Tianqi Zheng, Qingyu Yin, Monica Cheng, Jun Huan, Haoyu Wang, Jing Gao.
EMNLP'24 RoseLoRA: Row and Column-wise Sparse Low-Rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning.
Haoyu Wang, Tianci Liu, Ruirui Li, Monica Cheng, Tuo Zhao, Jing Gao.
(Oral, 2.8%)
ICML'24 LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models.
Tianci Liu, Haoyu Wang, Shiyang Wang, Yu Cheng, Jing Gao
(Spotlight, 3.5%)
ICLR'24 Towards Poisoning Fair Representations.
Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao.
AAAI'23 SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.
Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao.
(Distinguished Paper Award, 12 out of 8777 submissions)
ICML'23 Optimization for Amortized Inverse Problems.
Tianci Liu*, Tong Yang*, Quan Zhang, Qi Lei (Equal Contribution).