Ruihan Wu (吴睿涵)
I am currently a postdoctoral researcher at the University of California, San Diego, fortunately advised by Kamalika Chaudhuri. My research interests mainly lie in trustworthy machine learning, with a focus on privacy and robustness. My recent interests are privacy-preserving machine learning and online adaptation to distribution shift.
I received my Ph.D. from Cornell University, where I was very fortunate to be advised by Kilian Q. Weinberger. Prior to that, I received my B.E. in computer science from Yao Class at Tsinghua University.
Email: ruw076 [at] ucsd [dot] edu or rw565 [at] cornell [dot] edu
Publications and Manuscripts
Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning
Ruihan Wu*, Xiangyu Chen*, Chuan Guo, Kilian Q Weinberger
--In Conference on Uncertainty in Artificial Intelligence (UAI), 2023. [pdf] [code]
Does Label Differential Privacy Prevent Label Inference Attacks?
Ruihan Wu*, Jin Peng Zhou*, Kilian Q Weinberger, Chuan Guo
--In International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. [pdf] [code]
Differentially Private Multi-Party Data Release for Linear Regression
Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q Weinberger, Chong Wang
--In Conference on Uncertainty in Artificial Intelligence (UAI), 2022. [pdf] [code][video]
Online Adaptation to Label Distribution Shift
Ruihan Wu, Chuan Guo, Yi Su, Kilian Q. Weinberger
--In Advances of Neural Information Processing (NeurIPS), 2021. [pdf] [code][video]
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Ruihan Wu, Chuan Guo, Awni Hannun, Laurens van der Maaten
--In Advances of Neural Information Processing (NeurIPS), 2021. [pdf] [code]
Correlator Convolutional Neural Networks as an Interpretable Architecture for Image-like Quantum Matter Data
Cole Miles, Annabelle Bohrdt, Ruihan Wu, Christie Chiu, Muqing Xu, Geoffrey Ji, Markus Greiner, Kilian Q. Weinberger, Eugene Demler, Eun-Ah Kim
--Nature Communications, 2021. [pdf]
Making Paper Reviewing Robust to Bid Manipulation Attacks
Ruihan Wu*, Chuan Guo*, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
--In International Conference on Machine Learning (ICML), 2021. [pdf] [code][video]
On Hiding Neural Networks Inside Neural Networks
Chuan Guo*, Ruihan Wu*, Kilian Q. Weinberger
unpublished manuscript, 2020 [pdf] [code]
Scalable Lattice Influence Maximization
Wei Chen*, Ruihan Wu*, Zheng Yu*
--IEEE Transactions on Computational Social Systems (TCSS), 2020. [pdf]
Product Kernel Interpolation for Scalable Gaussian Processes
Jake Gardner, Geoff Peiss, Ruihan Wu, Kilian Q. Weinberger, Andrew G. Wilson
--In International Conference on Artificial Intelligence and Statistics (AISTATS), 2018. [pdf]
Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes
Lunjia Hu, Ruihan Wu, Tianhong Li, Liwei Wang
--In Conference on Learning Theory (COLT), 2017. [pdf]
Selected Awards
LinkedIn PhD Award, 2022
National Scholarship (top 2% in Tsinghua University), 2017
Gold Medal in Chinese Mathematical Olympiad , 2013