Shandong Wu

Full Professor, Radiology, University of Pittsburgh

Joined

February 2019

Names

Shandong Wu

Emails

****@upmc.edu (Confirmed)

Personal Links

Career & Education History

Full Professor

Radiology, University of Pittsburgh (pitt.edu)

2020 – Present

Advisors, Relations & Conflicts

Coauthor

Despina Kontos

2011 – 2013

Coauthor

Mubarak Shah

2009 – 2011

Expertise

Deep Learning

2015 – Present

Breast Imaging

2011 – Present

Medical Imaging

2009 – Present

Artificial intelligence

2009 – Present

Computer Vision

2009 – Present

Publications

FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning
Guangyu Sun, Matias Mendieta, Jun Luo, Shandong Wu, Chen Chen
- Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)
- Readers: Everyone
Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models
Jun Luo, Chen Chen, Shandong Wu
- ICLR 2025 Poster
- Readers: Everyone
Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning
Saba Dadsetan, Mohsen Hejrati, Shandong Wu, Somaye Hashemifar
- Accepted by TMLR
- Readers: Everyone
Cross-Domain Self-Supervised Deep Learning for Robust Alzheimer's Disease Progression Modeling
Saba Dadsetan, Mohsen Hejrati, Shandong Wu, Somaye Hashemifar
- 22 Sept 2022 (modified: 13 Feb 2023)
- ICLR 2023 Conference Withdrawn Submission
- Readers: Everyone
Adapt to Adaptation: Learning to Personalize for Cross-Silo Federated Learning
Jun Luo, Shandong Wu
- 29 Sept 2021 (modified: 13 Feb 2023)
- ICLR 2022 Conference Withdrawn Submission
- Readers: Everyone

Shandong Wu

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

FedPerfix: Towards Partial Model Personalization of Vision Transformers in Federated Learning

Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models

Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning

Cross-Domain Self-Supervised Deep Learning for Robust Alzheimer's Disease Progression Modeling

Adapt to Adaptation: Learning to Personalize for Cross-Silo Federated Learning

Co-Authors