My name with ^ indicates the students (in bold font) are mainly advised by me when doing the corresponding project.
“Exploring the Opportunities and Challenges of Graph Neural Networks in Electrical Engineering”
Eli Chien, Mufei Li, Anthony Aportela, Kerr Ding, Shuyi Jia, Supriyo Maji, Zhongyuan Zhao, Javier Duarte, Victor Fung, Callie Hao, Yunan Luo, Olgica Milenkovic, David Pan, Santiago Segarra, Pan Li
[Nature Reviews Electrical Engineering 2024]
"Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States, "
[ICML 2026, arXiv]
"The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search, "
"MAPLE: Metadata Augmented Private Language Evolution,"
[TPDP 2026, arXiv]
"DPrivBench: Benchmarking LLMs’ Reasoning for Differential Privacy"
Erchi Wang, Pengrun Huang, Eli Chien, Om Thakkar, Kamalika Chaudhuri, Yu-Xiang Wang, Ruihan Wu
[TPDP 2026 (contributed talk), arXiv, huggingface, github]
"The Access–Similarity Lens: An Operational Copyright Framework for Generative Models"
Amit Saha*, Yinan Huang*, Pan Li, Eli Chien^
[TPDP 2026]
"Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness,"
Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li.
[NeurIPS 2025, code]
"Differentially Private Relational Learning with Entity-level Privacy Guarantees,"
Yinan Huang, Haoteng Yin, Eli Chien, Rongzhe Wei, Pan Li.
"Privately Learning from Graphs with Applications in Fine-tuning Large Language Models,"
Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li.
"Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning,"
Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreačić, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien^.
[arXiv, ICML 2025]
“Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness,”
Eli Chien, Pan Li.
[arXiv, ICLR 2025]
“Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning”
Eli Chien, Haoyu Wang, Ziang Chen, Pan Li.
[arXiv, NeurIPS 2024 (spotlight), ICLR 2024 PrivML workshop (spotlight), TPDP 2024]
“Certified Machine Unlearning via Noisy Stochastic Gradient Descent”
Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
[arXiv, NeurIPS 2024]
“Differentially Private Graph Diffusion with Applications in Personalized PageRanks”
Rongzhe Wei, Eli Chien, Pan Li
[arXiv, NeurIPS 2024]
“On the Inherent Privacy Properties of Discrete Denoising Diffusion Models”
Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
[TMLR]
“Machine Unlearning of Pre-trained Large Language Models”
Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue
“Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning”
Zheyuan Liu*, Guangyao Dou*, Yijun Tian, Chunhui Zhang, Eli Chien^, Ziwei Zhu^
[TheWebConf 2024, arXiv]
“Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection”
Eli Chien*, Wei-Ning Chen*, Chao Pan*, Pan Li, Ayfer Özgür, Olgica Milenkovic.
“Efficient Model Updates for Approximate Unlearning of Graph-Structured Data” (a.k.a Certified Graph Unlearning)
Eli Chien*, Chao Pan*, Olgica Milenkovic.
[ICLR 2023, NeurIPS 2022 GLFrontiers Workshop, arXiv (workshop version), code]
“Unlearning Nonlinear Graph Classifiers in the Limited Training Data Regime”
Chao Pan*, Eli Chien*, Olgica Milenkovic.
[TheWebConf 2023, arXiv, code]
"LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation,"
Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li
[ICLR 2025 (Spotlight), arXiv, code]
"PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation,"
Eli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic, Hsiang-Fu Yu
“Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction,”
Eli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S Dhillon.
[ICLR2022, arxiv, code, OGB leaderboard]
“You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks,”
Eli Chien*, Jianhao Peng*, Chao Pan*, Olgica Milenkovic.
“Adaptive Universal Generalized PageRank Graph Neural Network,”
Eli Chien*, Jianhao Peng*, Pan Li, Olgica Milenkovic.
[ICLR2021, arXiv, code, slides]
"Multi-MotifGAN (MMGAN): Motif-targeted Graph Generation and Prediction,''
Anuththari Gamage, Eli Chien, Jianhao Peng, Olgica Milenkovic.
[ICASSP 2020, arXiv]
"Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls,"
Saurav Prakash, Jin Sima, Chao Pan, Eli Chien, Olgica Milenkovic
[TMLR]
"Provably Accurate and Scalable Linear Classifiers in Hyperbolic Spaces,"
Chao Pan*, Eli Chien*, Puoya Tabaghi,Jianhao Peng, Olgica Milenkovic.
[KAIS 2022, arXiv, ICDM 2021 conference version]
"HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering,"
Eli Chien, Puoya Tabaghi, Olgica Milenkovic.
"Highly Scalable and Provably Accurate Classification in Poincare Balls,"
Eli Chien*, Chao Pan*, Puoya Tabaghi, Olgica Milenkovic.
[ICDM 2021 (Regular), arXiv(Long version), code]
"Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs,''
Eli Chien*, Pan Li*, Olgica Milenkovic.
[ITW 2021, arXiv(Long version)]
"Active learning in the geometric block model,''
Eli Chien, Antonia Maria Tulino, Jaime Llorca.
[AAAI 2020, arXiv]
"Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection,''
Pan Li*, Eli Chien*, Olgica Milenkovic.
"HS^2: Active Learning over Hypergraphs with pointwise and pairwise queries,''
I (Eli) Chien, Huozhi Zhou, Pan Li.
"On the Minimax Misclassification Ratio of Hypergraph Community Detection,''
I Chien*, Chung-Yi Lin*, I-Hsiang Wang.
[Transactions on Information Theory 2019, arxiv]
"Community detection in hypergraphs: Optimal statistical limit and efficient algorithms,''
I Chien, Chung-Yi Lin, I-Hsiang Wang.
"On the fundamental statistical limit of community detection in random hypergraphs,''
Chung-Yi Lin, I (Eli) Chien, I-Hsiang Wang.
[ISIT 2017, online access]
“Support Estimation with Sampling Artifacts and Errors,”
Eli Chien, Olgica Milenkovic, Angelia Nedich.
[ISIT 2021, arXiv (full)]
"Query K-means Clustering and the Double Dixie Cup Problem,''
I (Eli) Chien, Chao Pan, Olgica Milenkovic.
"Small-sample estimation of the mutational support and distribution of SARS-CoV-2,"
Vishal Rana, Eli Chien, Jianhao Peng and Olgica Milenkovic
[TCBB 2022, Earlier version: medRxiv]
"Interplay between cohesin and RNA polymerase II in regulating chromatin interactions and gene transcription,"
Minji Kim, Ping Wang, Patricia A Clow, Eli Chien, Xiaotao Wang, Jianhao Peng, Haoxi Chai, Xiyuan Liu, Byoungkoo Lee, Chew Yee Ngan, Olgica Milenkovic, Jeffrey H Chuang, Chia-Lin Wei, Rafael Casellas, Albert W Cheng, Yijun Ruan
[Nature Structural & Molecular Biology 2026]
"Representer Point Selection for Explaining Regularized High-dimensional Models,"
Che-Ping Tsai, Jiong Zhang, Hsiang-Fu Yu, Eli Chien, Cho-Jui Hsieh, Pradeep Kumar Ravikumar
[ICML 2023, arXiv]