Miao Zhang
miaozhng (at) nyu (dot) edu

I am a fourth year Ph.D. candidate at New York University, advised by Prof. Rumi Chunara. I am a member of ChunaraLab and ViDA. Currently, I mainly work on reliable AI: model generalizability and bias mitigation for my Ph.D. degree. I received my Master degree from Stanford University in CCRMA, when I performed research in federated learning for medical image analysis at QIAI advised by Prof. Daniel Rubin. In my undergrad, I worked with Prof. Dong Wang at Tsinghua University on speech processing and recognition.
I have broad interests in:
Responsible AI: Algorithmic fairness, data debiasing, and out-of-domain generalization.
Computer vision and multimodal: Label efficient representation learning.
Health and social science: To adapt pre-trained deep neural networks and LLM for domain specific applications.
news
Feb 6, 2025 | One paper is accepted by ACM Journal on Computing and Sustainable Societies. We collect high resolution satellite imagery to quantify greenspace across city of Karachi, Pakistan. A lightweight and effective augmentation strategy boosts semantic segmentation performance. Check out the project website. |
Dec 9, 2024 | One paper is accepted at AAAI 2025, presenting a data perspective/solution to unsupervised bias mitigation. See you in Philadelphia! |
Sep 18, 2024 | Our paper publishes at Proceedings of the National Academy of Sciences (PNAS). We discuss how big data driven machine learning models can ignore important variables and their effects. We propose a causal framework to improve interpretability and instruct most efficient intervention. |
Aug 13, 2024 | Very excited to present at Cohere for AI about the paper Common-Sense Bias Discovery and Mitigation for Classification Tasks. Check out the online event. |
Jun 1, 2024 | New paper to appear at AAAI/ACM conference on artificial intelligence, ethics, and society 2024. We discuss and promote fairness in self-supervised representation learning for satellite image segmentation between urban and rural areas. |