Miao Zhang

According to our database, Miao Zhang authored at least 10 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Quantifying Greenspace with Satellite Images in Karachi, Pakistan, Using a New Data Augmentation Paradigm.

Miao Zhang, Hajra Arshad, Manzar Abbas, Hamzah Jehanzeb, Izza Tahir, Javerya Hassan, Zainab Samad, Rumi Chunara

ACM J. Comput. Sustain. Soc., 2025

2024

Leveraging CLIP for Inferring Sensitive Information and Improving Model Fairness.

Miao Zhang, Rumi Chunara

CoRR, 2024

Impact on Public Health Decision Making by Utilizing Big Data Without Domain Knowledge.

Miao Zhang, Salman Rahman, Vishwali Mhasawade, Rumi Chunara

CoRR, 2024

FLHetBench: Benchmarking Device and State Heterogeneity in Federated Learning.

Junyuan Zhang, Shuang Zeng, Miao Zhang, Runxi Wang, Feifei Wang, Yuyin Zhou, Paul Pu Liang, Liangqiong Qu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Mitigating Urban-Rural Disparities in Contrastive Representation Learning with Satellite Imagery.

Miao Zhang, Rumi Chunara

Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) - Full Archival Papers, October 21-23, 2024, San Jose, California, USA, 2024

2022

SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.

Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin

IEEE J. Biomed. Health Informatics, 2022

Fair contrastive pre-training for geographic images.

Miao Zhang, Rumi Chunara

CoRR, 2022

Segmenting across places: The need for fair transfer learning with satellite imagery.

Miao Zhang, Harvineet Singh, Lazarus Chok, Rumi Chunara

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging.

Liangqiong Qu, Niranjan Balachandar, Miao Zhang, Daniel L. Rubin

CoRR, 2021

2020

Federated Learning for Breast Density Classification: A Real-World Implementation.

Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer

Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020