Activities

Guest lecture in the DTU course 62533/62T22 “Applied Machine Learning and Big Data” (lecturer Dr. Lei You), titled "Fairness evaluation in ML. Why would we care?", May 2025.
Teaching assistant for the course "Mathematical Analysis (B2)" at USTC, Mar 2016 to Jul 2016.

"Why we need new fairness metrics and how to use them," OR seminar at CMU Tepper, Dec 2025. [slides]
"Why we need new fairness metrics and how to use them," TOC4Fairness seminar, Nov 2025.
Breaking the Wall of "Invisible inequality in machine learning research," Falling Walls Lab Denmark, Sept 2025. [slides]
"Do existing fairness measures suffice? Assessing discrimination in algorithmic decision-making," D3A workshop on machine learning theory (Long talk), Aug 2025. [slides]
"Study of FAIR ML models from a theoretical perspective," MIA seminar at DIKU, Dec 2024. [slides]
"Sub-architecture ensemble pruning in neural architecture search", SustainML reading group, Nov 2024.
"Increasing fairness via combination with learning guarantees," Fall 2023 LeT-All mentorship workshop (Session 2, Practice talk), Oct 2023. [slides]

Yijun Bian#, Lei You, and Yuya Sasaki, "Do Existing Fairness Measures Suffice? Assessing Discrimination in Algorithmic Decision-Making," in the 4th Deployable AI Workshop (DAI) at AAAI 2026, Jan 2026. [paper][poster]
Lin Zhu#, Yijun Bian#, and Lei You*, "FairSHAP: Preprocessing for fairness through attribution-based data augmentation," in the 20th Women in Machine Learning Workshop (WiML) at NeurIPS 2025, Dec 2025. [abstract][poster]
Yijun Bian and Kun Zhang, "Increasing fairness via combination with learning guarantees," in NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning (M3L), Dec 2024. [paper][poster]
Yijun Bian#, Yujie Luo#, and Ping Xu, "Does machine bring in extra bias in learning? Approximating discrimination within models quickly," in NeurIPS 2024 Workshop on Mathematics of Modern Machine Learning (M3L), Dec 2024. [paper][poster]