Recent Projects

Solving Fairness in Computer Vision

Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data, TMLR 2023

Ensuring Fairness Amid Data Distribution Shifts

Improving Fair Training under Correlation Shifts, ICML 2023

Lowering the Barrier of Fair AI Development

FairBatch: Batch Selection for Model Fairness, ICLR 2021
Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data, TMLR 2023
Sample Selection for Fair and Robust Training, NeurIPS 2021

Supporting Multiple Trustworthy AI Goals Together

Sample Selection for Fair and Robust Training, NeurIPS 2021
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training, ICML 2020
Machine Learning Robustness, Fairness, and their Convergence, SIGKDD 2021
Data Cleaning for Accurate, Fair, and Robust Models, DEEM @ SIGMOD 2019

Focusing on Data-Centric AI

Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective, VLDB Journal 2022
A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective, IEEE TKDE 2021
Inspector Gadget: A Data Programming-Based Labeling System for Industrial Images, VLDB 2021

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