Yan-Ran Wang (Joyce)

          Email: wangyanran100@gmail.com OR joycewyr@stanford.edu

Yan-Ran Wang (Joyce) is a postdoc research fellow at Stanford Center for Artificial Intelligence in Medicine & Imaging - Stanford AIMI. Her research lies in the intersection of computer vision and biomedical data analysis, with a particular focus on Machine Learning challenges inspired by healthcare and human diseases. Joyce is dedicated to advancing machine learning technology for multimodal biomedical data and contributes to the development of AI applications in safer medical imaging, precise disease diagnosis, and personalized medicine, covering oncology and cardiology. She earned her Ph.D. in Computer Science from Northwestern University (Evanston) in 2019 and previously served as a research intern at Snapchat Research. Joyce joined Stanford's Biomedical Data Science and Radiology department in 2019.

Timeline:

2019-now
Stanford Postdoc Research Fellow
AI-enabled medical solutions with an emphasis on adhering to the underlying biology
Mentor: Akshay Chaudhari
2014 - 2019
Northwestern Computer Science Ph.D. student
Deep Learning, Computer Vision, Biomedical Data Analysis
Spring, Fall 2017
Snapchat Computer Vision Research Intern
Semi-supervised Video Segmentation
Summer 2013
UCLA Graduate Summer School Selected Participant
IPAM on Computer Vision
2011 - 2014
Fudan Computer Science: MSc
Computer Vision, Big Video Data Science
2008 - 2011
Anhui University: BSc
Three-year Special Talent Bachelor Program

Publications:

Google Scholar  ·  Reseach Gate

Wang, YR.J., Yang, K., Wen, Y., Wang, P.C., Hu, Y.P., Lai, Y.F., Wang, Y.F., Zhao, K.K., Tang, S.Y., ..., Luo, Y., Liu, D., Zhao, P., Lin, Keldon, Wu, Joseph C., Zhao, S.H.
Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging
Nature Medicine (2024) Impact Factor: 82.9
Paper ·  Supplementary Data ·  BibTex ·  Code ·  Project Webpage

Wang, YR.J., Wang, P.C., Yan, Z.H., Zhou, Q., Gunturkun, F., Li, P., Hu, Y.S., Wu, W., Zhao, K.K., ..., Vogel, H., Han, S., Lu, T., Wu, F., Gong, J.
Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures
Cancer Cell (2024) Impact Factor: 50.3
Paper ·  Supplementary Data ·  Demo Video ·  BibTex ·  Code ·  Project Webpage

Wang, YR.J., Qu, L., Sheybani, N., Luo, X., Wang, J., Hawk, K., Thakor, A., Gatidis, S., Xiao, X., Pribnow, A., Rubin, D., Daldrup-Link, H.
AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans
Radiology: Artificial Intelligence (RAI2023)
Paper ·  Supplementary Data ·  BibTex ·  Project Webpage

Wang, YR.J., Wang, P.C., Adams, L., Sheybani, N., Qu, L., Sarrami, A., Theruvath, A., Gatidis, S., Ho, T., Zhou, Q., Pribnow, A., Thakor, A., Rubin, D., Daldrup-Link, H.
Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models
European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI2023)
Paper ·  Supplementary Data ·  BibTex ·  Project Webpage

Wang, YR.J., Baratto, L., Hawk, K., Theruvath, J., Pribnow, A., Thakor, A., Gatidis, S., Lu, R., Gummidipundi, S., Garcia-Diaz, J., Rubin, D., Daldrup-Link, H.
Artificial Intelligence enables whole body Positron Emission Tomography Scans with minimal radiation exposure
European Journal of Nuclear Medicine and Molecular Imaging (EJNMMI2021)
Paper ·  Supplementary Data ·  BibTex ·  Project Webpage

Wang, YR.J., Baratto, L., Hawk, K., Theruvath, J., Pribnow, A., Thakor, A., Lu, R., Rubin, D., Daldrup-Link, H.
Reducing the Dose of Whole-body PET Scans of Pediatric Cancer Patients to that of a Chest X-ray Using Neural Networks with Attention-weighted Loss Function
World Molecular Imaging Congress (WMIC2020)

Ho, T.,Wang, YR.J., Daldrup-Link, H.
Artificial Intelligence for Bone Cancer Imaging
Bone Cancer - Bone Sarcomas and Bone Metastases - From Bench to Bedside - 3rd Edition - Book Chapter (Elsevier2020)

Punjabi, A., Martersteck, A.,Wang, YR.J., Parrish, T., Katsaggelos, A., Alzheimer’s Disease Neuroimaging Initiative
Neuroimaging Modality Fusion in Alzheimer’s Classification Using Convolutional Neural Networks
PLoS one (PLoS one 2019)
Paper ·  BibTex

Wang, YR.J., Chen, S., Wang, H., Higgins, J., Hill, V., Parrish, T., Katsaggelos, A.
A 3D Cross-hemisphere Neighborhood Difference ConvNet for Chronic Stroke Lesion Segmentation
IEEE International Conference on Image Processing (ICIP2019)
Paper ·  Poster ·  BibTex ·  Project Webpage

Yang, L., Wang, YR.J., Xiong, X., Yang, J., Katsaggelos, A.
Efficient Video Object Segmentation via Network Modulation
Conference on Computer Vision and Pattern Recognition (CVPR2018)
Paper ·  Poster ·  BibTex ·  Women in Computer Vision (WiCV) Funding

Yang, L., Wang, YR.J., Xiong, X., Yang, J.
Modulated Image Segmentation
Application Number: 16/192,457, Docket Number: P00593-US1, Inventor Reference: I-08559 (US Patent 2018)

Wang, YR.J., Wang, X., Katsaggelos, A., Parrish, T.
A Deep Symmetry ConvNet for Stroke Lesion Segmentation
International Conference on Image Processing (ICIP2016)
Paper ·  Poster ·  BibTex ·  1st Place of Outstanding Student Poster, Northwestern

Wang, YR.J., Wang, X., Katsaggelos, A., Parrish, T.
3D Convolutional Neural Network for Chronic Stroke Lesion Segmentation
Human Brain Mapping (HBM2016)

Wang, YR.J., Dai, Q., Feng, R., Jiang, Y.
Beauty is Here: Evaluating Aesthetics in Videos Using Multimodal Features and Free Training Data
ACM Multimedia (ACMM2013)
Paper ·  BibTex

Jiang, Y., Wang, YR.J., Feng, R., Xue, X., Zheng, Y., Yang, H.
Understanding and Predicting Interestingness of Videos
Association for the Advancement of Artificial Intelligence (AAAI2013)
Paper ·  BibTex

Pet Project:

Are you excited by the idea of using your expertise and your experience to support colledge students around the world? Are you struggling with the transition into graduate school, college or the drastic change in the learning environment?
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Mentorship:

Teaching:

In 2018, I designed and was the instructor for a class of 16 incoming Northwestern undergraduates. The class is part of the EXCEL program with a goal of preparing the engineering students to enter a required course and foster students' leadership skills and their commitment to diversity issues.
Linear Algebra and Introduction to MATLAB
Hodge EXCEL Program, Northwestern (EXCEL2018)
Course Syllabus ·  Course Schedule ·  Course Review Sheets

Service:

Misc: