Yuyin Zhou
I am currently an Assistant Professor of Computer Science and Engineering at University of California, Santa Cruz. Before that, I was a Postdoctoral Fellow at Stanford University, working closely with Prof. Lei Xing and Prof. Matthew Lungren. I have received my Ph.D. degree in Computer Science at Johns Hopkins University, under the supervision of Bloomberg Distinguished Professor Alan Yuille.
Our group is focusing on advancing biomedical artificial intelligence, primarily in the field of medical image analysis. Our ultimate goal is to match medical experts in decision-making. Specifically, we focus on: 1) creating innovative and cutting-edge medical multimodal model; 2) building real-world learning systems that ensure fair, trustworthy and real-time feedacks to clinicians, caregivers, and even patients; 3) one-shot/few-shot adaptation of open foundation models to diverse medical tasks; 4) synthetic data generation aligned with clinical knowledge.
I am looking for multiple self-motivated PhD/interns to work on machine learning, computer vision and AI for healthcare. Welcome to apply from here and drop me an email with your CV and publications (if any).
Due to the large amount of emails I receive, I may not be able to respond to each one individually.
Recent News
- [2024/07] BioMedGPT is accepted by Nature Medicine
- [2024/07] TransUNet is accepted by Medical Image Analysis
- [2024/07] One paper is accepted by ECCV 2024
- [2024/05] One paper is early accepted by MICCAI 2024
- [2024/04] We are organizing the MICCAI 2024 tutorial on Foundation Models For Medical ImagING (FOMMIA)
- [2024/04] We are organizing the MICCAI 2024 workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis (MOVI)
- [2024/03] One paper about using self-supervised learning to improve gene expression has been accepted by Briefings in Bioinformatics
- [2024/02] Five papers have been accepted by CVPR 2024
- [2024/02] Two papers have been accepted by ISBI 2024
- [2024/01] We are organizing the first Workshop on Foundation Models for Medical Vision workshop in conjunction with CVPR 2024. Join us in the “SEGMENT ANYTHING IN MEDICAL IMAGES ON LAPTOP” challenge to build lightweight medical foundation models. We welcome your contribution to pushing medical foundation models into real-world clinics! Top-performing teams will be invited to submit their groundbreaking solutions as co-authors in a summarization paper to a top-tier journal.
- [2024/01] I am serving as an area chair for MICCAI 2024
- [2024/01] I am serving as an area chair for CHIL 2024
- [2024/01] Our MicroSegNet has been accepted by Computerized Medical Imaging and Graphics. We present the first public micro-ultrasound dataset of 75 patients for prostate segmentation at this link. Enjoy!
- [2023/10] 3D TransUNet is out (code and paper)!! 3D TransUNet-Enc achieves the 2nd place in BraTs2023 for brain metastases segmentation
- [2023/08] I will serve as an area chair for CVPR 2024
- [2023/08] I am serving as an area chair for ICLR 2024
- [2023/06] 2 papers are accepted by MICCAI 2023
- [2023/03] We are organizing ICML2023 workshop on Interpretable ML in Healthcare
- [2023/03] I received the Hellman Fellowship
- [2023/02] 1 paper is accepted by CVPR 2023
- [2023/01] I am serving as an area chair for MICCAI 2023
- [2022/12] We are organizing the CVPR 2023 MCV workshop
- [2022/12] I am serving as an area chair for CHIL 2023
- [2022/12] One paper accepted by IEEE TMI (Paper)
- [2022/09] One paper has been accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (Paper)
- [2022/09]One paper has been accepted by Neurips 2022
- [2022/09]I am selected as a finalist for MICCAI 2022 Young Scientist Publication Impact Award