I am an assistant professor in the CSE department at The Ohio State University and a part-time research scientist at Yahoo! Research. My research interest is in theoretical and applied machine learning with fairness and privacy guarantees, robust machine learning, distributed learning, and efficient machine learning for tiny devices.

Current Graduate Students

Zhiqun Zuo

Zhongteng Cai

Ding Zhu

Recent News

2024

• New paper titled “Imposing Fairness Constraints in Synthetic Data Generation” is accepted in the 27th International Conference on Artificial Intelligence and Statistics (AISTATS).

• Recieved a grant from the college of engineering to build safe, robust, and interpretable AI models for large-scale systems.

2023

• New paper titled “Counterfactually Fair Representation” is accepted in the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS).

• New paper titled “Loss Balancing for Fair Supervised Learning” is accepted in the International Conference of Machine Learning (ICML).

• New paper titled “Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions” is accepted (for oral presentation) in the AAAI Conference on Artificial Intelligence.

• New paper titled “Counterfactual Fairness in Synthetic Data Generation” is accepted in the Neurips workshop on Synthetic Data for Machine Learning.

• New paper titled “Towards Fair Representation Learning in Knowledge Graph with Stable Adversarial Debiasing” is accepted in the ICDM workshop on Knowledge Graph.

• Recived an NSF Grant to buid a safe and private AI system for health monitoring with my collaborators at UIUC and UCSD.

• Recived an NSF Grant to improve fairness and robustness of AI in dynamic environmnets.