Jian Lou
HIC-ZJU 100 Young Professor
Zhejiang University
Email: jian.lou@hoiying.net (Primary) & jian.lou@zju.edu.cn
I am currently a HIC-ZJU 100 Young Professor at Zhejiang University. I was an associate professor at Xidian University from 2021 to 2022. I was a Post-doc in the Department of Computer Science at Emory University from 2019 to 2021. I was very fortunate to be hosted by Prof. Li Xiong. I obtained my Ph.D. in Computer Science at Hong Kong Baptist University in 2018, supervised by Prof. Yiu-ming Cheung. Prior to that, I received a B.S. in Mathematics from Zhejiang University in 2013.
Professional Appointments
2022 - Present Zhejiang University HIC-ZJU 100 Young Professor
2021 - 2022 Xidian University Associate Professor
2019 - 2021 Emory University Postdoctoral Fellow
Education
2013 - 2018 Hong Kong Baptist University Ph.D. in Computer Science
2009 - 2013 Zhejiang University B.S. in Mathematics
Research Interests
Privacy-preserving Machine Learning & Data Analytics
Differential Privacy
Machine Unlearning
News and Activities
May 2024: One paper is accepted to ACM CCS 2024.
April 2024: One paper is accepted to ACM CCS 2024.
February 2024: One paper is accepted to CVPR 2024.
January 2024: I will serve as an Area Chair for ICML 2024.
January 2024: One paper is accepted to WWW 2024.
December 2023: I will serve as a PC member for ACM CCS 2024.
Publications
* denotes student collaborator.
2024
Junxu Liu, Jian Lou, Li Xiong, Jinfei Liu, Xiaofeng Meng, “Cross-silo Federated Learning with Record-level Personalized Differential Privacy", ACM CCS'24.
with Yuke Hu*, Jiaqi Liu*, Wangze Ni, Feng Lin, Zhan Qin, Kui Ren, “ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach", ACM CCS'24.
Fereshteh Razmi, Jian Lou, Li Xiong, “Does Differential Privacy Prevent Backdoor Attacks in Practice?", DBSec'24.
Wen Yin, Jian Lou, Pan Zhou, Yulai Xie, Dan Feng, Yuhua Sun, Tailai Zhang, Lichao Sun, “Temperature-based Backdoor Attacks on Thermal Infrared Object Detection", CVPR'24.
Qiuchen Zhang, Hong kyu Lee, Jing Ma, Jian Lou, Carl Yang, Li Xiong, “DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy", WWW'24.
Wenjie Wang, Pengfei Tang, Jian Lou, Yuanming Shao, Lance Waller, Yi-an Ko, Li Xiong, “IGAMT: Privacy Preserved Electronic Health Record Synthetic Approach with Heterogeneity and Irregularity", AAAI'24.
Lanlan Chen, Kai Wu, Jian Lou, Jing Liu, “Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics", AAAI'24.
with Hongwei Yao*, Zhan Qin, Kui Ren, “PromptCARE: Prompt Copyright Protection by Watermark Injection and Verification", S&P/Oakland'24.
Hongwei Yao*, Jian Lou, Zhan Qin, “PoisonPrompt: Backdoor Attack on Prompt-based Large Language Models", ICASSP'24.
Congcong Fu*, Hui Li, Jian Lou, Huizhen, Li, Jiangtao Cui, “DP-starJ: A Differentially Private Scheme towards Analytical Star-Join Queries", SIGMOD'24.
Xiaochen Li, Weiran Liu, Jian Lou, Yuan Hong, Lei Zhang, Zhan Qin, Kui Ren, “Local Differentially Private Heavy Hitter Detection in Data Streams with Bounded Memory", SIGMOD'24.
Yuchen Yang*, Bo Yuan*, Jian Lou, Zhan Qin, “SCRR: Stable Malware Detection under Unknown Deployment Environment Shift by Decoupled Spurious Correlations Filtering", IEEE Transactions on Dependable and Secure Computing, 2024.
2023
Yifei Ren*, Jian Lou, Li Xiong, Joyce Ho, Xiaoqian Jiang, Sivasubramanium Bhavani, “MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning", ML4H'23.
with Jiaqi Liu*, Zhan Qin, Kui Ren, “Certified Minimax Unlearning with Generalization Rates and Deletion Capacity", NeurIPS'23.
Jinfei Liu, Pengyun Zhu, Long Wen, Feng Xue, Jian Lou, Zhibo Wang, Kui Ren, “CAPP-130 : A Dataset of Chinese Application Privacy Policy Summarization and Interpretations", NeurIPS'23 Datasets and Benchmarks Track.
with Shuijing Zhang*, Li Xiong, Xiaoyu Zhang, Jing Liu, “Closed-form Machine Unlearning for Matrix Factorization", CIKM'23.
Junxu Liu, Jian Lou, Li Xiong, Xiaofeng Meng, “Personalized Differentially Private Federated Learning without Exposing Privacy Budgets", CIKM'23.
Yulin Jin*, Xiaoyu Zhang, Jian Lou, Xiaofeng Chen, “ACQ: Few-shot Backdoor Defense via Activation Clipping and Quantizing", ACM MM'23.
with Junxu Liu*, Mingsheng Xue*, Xiaoyu Zhang, Li Xiong, Zhan Qin, “MUter: Machine Unlearning on Adversarial Training Models", ICCV'23.
Yulin Jin*, Xiaoyu Zhang, Jian Lou, Xu Ma, Xiaofeng Chen, Zilong Wang, “Explaining Adversarial Robustness of Neural Networks from Clustering Effect Perspective", ICCV'23.
Haocheng Xia, Jinfei Liu, Jian Lou, Zhan Qin, Kui Ren, Yang Cao, Li Xiong, “Equitable Data Valuation Meets the Right to be Forgotten in Model Markets", VLDB'23.
Fereshteh Razmi, Jian Lou, Li Xiong, Yuan Hong, “Interpretation Attacks on Interpretable Models with Electronic Health Records", ECML-PKDD'23.
Yiling He*, Jian Lou, Zhan Qin, Kui Ren, “FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Risk Analysis", ACM CCS'23.
Hongwei Yao*, Zheng Li, Kunzhe Huang, Jian Lou, Zhan Qin, Kui Ren, “RemovalNet: DNN Fingerprint Removal Attacks", IEEE Transactions on Dependable and Secure Computing, 2023.
2022
Kaixin Yuan*, Jing Liu, Jian Lou, “Higher-Order Masked Graph Neural Networks for Traffic Flow Prediction", ICDM'22.
Farnaz Tahmasebian*, Jian Lou, Li Xiong, “RobustFed: A Truth Inference Approach for Robust Federated Learning", CIKM'22.
Congcong Fu*, Hui Li, Jian Lou, Jiangtao Cui, “DP-HORUS: Differentially Private Hierarchical Count Histograms under Untrusted Server", CIKM'22.
with Xiaoyu Zhang, Yulin Jin*, Tao Wang, Xiaofeng Chen, “Purifier: Plug-and-play Backdoor Mitigation for Pre-trained Models Via Anomaly Activation Suppression", ACM MM'22.
Yuhua Sun, Tailai Zhang, Xingjun Ma, Pan Zhou, Jian Lou, Zichuan Xu, Xing Di, Yu Cheng, Lichao Sun, “Backdoor Attacks on Crowd Counting", ACM MM'22.
Junxu Liu*, Jian Lou, Li Xiong, Jinfei Liu, Xiaofeng Meng, “Projected Federated Averaging with Heterogeneous Differential Privacy", VLDB'22.
Pengfei Tang*, Wenjie Wang*, Jian Lou, Li Xiong, “Generating Adversarial Examples with Distance Constrained Adversarial Imitation Networks", IEEE Transactions on Dependable and Secure Computing, 2022.
2021
with Haowen Lin*, Li Xiong, Cyrus Shahabi, “Integer-arithmetic-only Certified Robustness for Quantized Neural Networks", ICCV'21.
with Qiuchen Zhang*, Jing Ma*, Li Xiong, “Private Stochastic Non-convex Optimization with Improved Utility Rates", IJCAI'21.
with Wenjie Wang*, Pengfei Tang*, Li Xiong, “Certified Robustness to Word Substitution Attack with Differential Privacy", NAACL'21.
with Jing Ma*, Qiuchen Zhang*, Li Xiong, Joyce Ho, “Communication Efficient Federated Generalized Tensor Factorization for Collaborative Health Data Analytics", WWW'21.
Jinfei Liu, Jian Lou,Junxu Liu, Li Xiong, Jian Pei, Jimeng Sun, “Dealer: An End-to-End Model Marketplace with Differential Privacy", VLDB'21.
Yiu-ming Cheung, Jian Lou, Feng Yu, “Vertical Federated Principal Component Analysis on Feature-wise Distributed Data", WISE'21.
Jing Ma*, Qiuchen Zhang*, Jian Lou, Li Xiong, Joyce Ho, Sivasubramanium Bhavani, “Communication Efficient Tensor Factorization for Decentralized Healthcare Networks", ICDM'21.
Jing Ma*, Qiuchen Zhang*, Jian Lou, Li Xiong, Joyce Ho, “Temporal Network Embedding via Tensor Factorization", CIKM'21.
Jinfei Liu, Qiongqiong Lin, Jiayao Zhang, Kui Ren, Jian Lou, Junxu Liu, Li Xiong, Jian Pei, Jimeng Sun, “Demonstration of Dealer: An End-to-End Model Marketplace with Differential Privacy", VLDB'21 Demo Track.
with Yiu-ming Cheung, “An Uplink Communication Efficient Approach to Feature-wise Distributed Sparse Optimization with Differential Privacy”, IEEE Transactions on Neural Networks and Learning Systems, 2021.
Qiquan Shi, Yiu-ming Cheung, Jian Lou, “Robust Tensor SVD and Recovery with Rank Estimation", IEEE Transactions on Cybernetics, 2021.
2020
with Yiu-ming Cheung, “Projection-free Online Empirical Risk Minimization with Privacy-preserving and Privacy Expiration", WI-IAT'20 (Best in Theoretical Paper Award).
with Yifei Ren*, Li Xiong, Joyce Ho, “Robust Irregular Tensor Factorization and Completion for Temporal Health Data Analysis", CIKM'20.
Qiuchen Zhang*, Jing Ma*, Yonghui Xiao, Jian Lou, Li Xiong, “Broadening Differential Privacy for Deep Learning Against Model Inversion Attacks", Bigdata'20.
Qiuchen Zhang*, Jing Ma*, Jian Lou, Li Xiong, Xiaoqian Jiang, “Towards Training Robust Private Aggregation of Teacher Ensembles Under Noisy Labels", Bigdata'20.
with Yiu-ming Cheung, “Robust Low-rank Tensor Minimization via a New Tensor Spectral k-Support Norm”, IEEE Transactions on Image Processing, 2020.
Meng Pang, Yiu-ming Cheung, Binghui Wang, Jian Lou, “Synergistic Generic Learning for Face Recognition From a Contaminated Single Sample per Person", IEEE Transactions on Information Forensics and Security, 2020.
2019 and before
Jing Ma*, Qiuchen Zhang*, Jian Lou, Joyce Ho, Li Xiong, Xiaoqian Jiang, "Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis", CIKM'19.
with Wenwen Li, Shuo Zhou, Haiping Lu, “Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI", MLMI@MICCAI'19.
with Yiu-ming Cheung, "Uplink Communication Efficient Differentially Private Sparse Optimization With Feature-Wise Distributed Data", AAAI'18.
Meng Pang, Yiu-ming Cheung, Risheng Liu, Jian Lou, and Chuang Lin, “Toward efficient image representation: Sparse concept discriminant matrix factorization", IEEE Transactions on Circuits and Systems for Video Technology, 2018.
with Yiu-ming Cheung, “Proximal Average Approximated Incremental Gradient Descent for Composite Penalty Regularized Empirical Risk Minimization”, Machine Learning, 2017.
with Yiu-ming Cheung, “Scalable Spectral k-Support Norm Regularization for Robust Low Rank Subspace Learning", CIKM'16.
with Yiu-ming Cheung, “Efficient Generalized Conditional Gradient with Gradient Sliding for Composite Optimization", IJCAI'15.
with Yiu-ming Cheung, “Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization", ACML'15.
Services
Conference Program Committee Member
International Conference on Very Large Data Bases (VLDB): 2024 2023
ACM Conference on Computer and Communications Security (ACM CCS): 2024 2022
International Conference on Machine Learning (ICML): 2024 (Area Chair) 2023 2022
Conference on Language Modeling (COLM): 2024
International Conference on Learning Representations (ICLR): 2024
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR): 2024
Conference on Neural Information Processing Systems (NeurIPS): 2023 2022
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): 2022
International Joint Conference on Artificial Intelligence (IJCAI): 2022
AAAI Conference on Artificial Intelligence (AAAI): 2022 2021 2020 2019
International Conference on Artificial Intelligence and Statistics (AISTATS): 2021
ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL): 2021 2020
IEEE International Conference on Big Data (IEEE Bigdata): 2021 2020
Journal Reviewer
IEEE Transactions on Dependable and Secure Computing
IEEE Transactions on Image Processing
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Biomedical Engineering
ACM Transactions on Computing for Healthcare
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Cybernetics
IEEE Signal Processing Letters
IEEE Communications Letters