Machine Learning, Computer Vision, Multi-modality Modeling, Robustness in Healthcare
Yao Qin received her PhD degree in Computer Science and Engineering at UC San Diego in 2020. After that, she worked as a research scientist at Google Research. Her research focuses on robustness of machine learning, including adversarial robustness and out-of-distribution generalization. In addition, Yao also has an interest in developing general machine learning algorithms and applying them to computer vision, natural language processing and healthcare applications, especially diabetes.
Yao has extensively published papers at the top conferences and journals, including Neural Information Processing Systems (NeurIPS), International Conference on Machine Learning (ICML), International Conference on Learning Representations (ICLR), Computer Vision and Pattern Recognition (CVPR), International Journal of Computer Vision (IJCV), European Conference on Computer Vision (ECCV), etc. Due to her contributions to the machine learning area, She has been selected as EECS Rising Star at MIT, 2021.