||I am an Assistant Professor with joint appointments in Radiology, Biomedical Informatics, and Bioengineering. I am also a member of the Biomedical Informatics Training Program Core Faculty, University of Pittsburgh Cancer Institute (UPCI) and Magee-Womens Research Institute, and the Intelligent Systems Program (ISP) of Computer Science at Pitt. My background is in Computer Science (Computer Vision) with additional postdoctoral training (at University of Pennsylvania, School of Medicine, Department of Radiology) in clinical imaging and radiology research specialized in breast cancer research. My research interfaces a broad range of interdisciplinary in computational science and medicine for translational and clinical applications. My main research areas include computational biomedical imaging analysis, big (health) data coupled with machine/deep learning, imaging-based clinical studies, radiomics/radiogenomics, and artificial intelligence in clinical informatics/workflows. Current research interests center on computational breast imaging and clinical studies for investigating quantitative imaging-derived biomarkers, models, and systems for breast cancer screening, risk assessment, diagnosis, prognosis, and treatment, towards improving individualized clinical decision-making and precision medicine.
My research is supported (as a sole Principle Investigator) by National Institute of Health (NIH)/National Cancer Institute (NCI) (R01), Radiological Society of North America (RSNA), University of Pittsburgh Medical Center (UPMC), UPCI-Institute of Precision Medicine, Pitt Clinical and Translational Science Institute, and Nvidia, Inc. I established and lead a multidisciplinary research team with complimentary expertise, including computer scientists, radiologists, pathologists, medical oncologists, biostatisticians, geneticists, postdocs, senior research specialists, students, and international visiting scholars. I have published more than 50 journal and conference papers and participated as key research personnel in more than 20 research projects granted by international-wide research agencies. I have mentored/co-mentored more than 25 students (both undergraduate and graduate) in their research or theses, several of which have resulted in co-authored publications. I am a regular reviewer for many grant agencies/study sections, renowned journals, and conferences.
||1. Shandong Wu, Wendie A. Berg, Margarita L. Zuley, Brenda F. Kurland, Rachel C. Jankowitz, Robert Nishikawa, David Gur, and Jules H. Sumkin, Breast MRI contrast enhancement kinetics of normal parenchyma correlate with presence of breast cancer, Breast Cancer Research, May 2016, 18:76, 2016.
2. Justin C Brown, Despina Kontos, Mitchell Schnall, Shandong Wu, Kathryn H Schmitz. The Dose-Response Effects of Aerobic Exercise on Body Composition and Breast Tissue among Women at High Risk for Breast Cancer: A Randomized Trial. Cancer Prevention Research, 9(7): 581-8, Jul. 2016.
3. Kathryn H. Schmitz, Nancy I. Williams, Despina Kontos, Susan Domchek, Knashawn H. Morales, Wei-Ting Hwang, Lorita L. Grant, Laura DiGiovanni, Domenick Salvatore, Desire Fenderson, Mitchell Schnall, Mary Lou Galantino, Jill Stopfer, Mindy S. Kurzer, Shandong Wu, Jessica Adelman, Justin C. Brown, Jerene Good, Dose Response Effects of Aerobic Exercise on Estrogen Among Women at High Risk for Breast Cancer: A Randomized Controlled Trial, Breast Cancer Research and Treatment, 154(2):309-18, Nov. 2015.
4. Shandong Wu, Susan P. Weinstein, Michael J DeLeo III, Emily F. Conant, Jinbo Chen, Susan M. Domchek, Despina Kontos, Quantitative assessment of Background Parenchymal Enhancement in breast MRI predicts response to Risk-Reducing Salpingo-Oophorectomy: Preliminary evaluation in a cohort of BRCA1/2 mutation carriers, Breast Cancer Research, 17(1):67-77, May 2015.
5. Schmitz KH, Williams NI, Kontos D, Kurzer M, Schnall M, Domchek S, Stopfer J, Galantino ML, Hwang W, Morales K, Shandong Wu, DiGiovanni L, Salvatore D, Fenderson D, Good J, Sturgeon K, Grant L, Bryan CJ, Adelman J. Women In Steady Exercise Research (WISER) Sister: Study Design and Methods. Contemporary Clinical Trials. 41:17-30, Mar. 2015.
6. Yong Wang, Shiqiang Hu, and Shandong Wu. Visual tracking based on group sparsity learning, Machine Vision and Applications, volume 26, issue 1, pp 127-139, Jan. 2015.
7. Jieyang Ju, Ruosha Li, Suicheng Gu, Joseph Ken Leader, Xiaohua Wang, Yahong Chen, Bin Zheng, Shandong Wu, David Gur, Frank Sciurba, and Jiantao Pu. Impact of emphysema heterogeneity on pulmonary function. PLoS ONE, volume 9, issue 11, pp. e113320, Nov 2014.
8. Shandong Wu, Susan P. Weinstein, Emily F. Conant, and Despina Kontos. Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method. Medical Physics 40(12):122301-12, Nov. 2013.
9. Shandong Wu, Susan P. Weinstein, Emily F. Conant, Mitchell D. Schnall, and Despina Kontos, Automated chest wall line detection for whole-breast segmentation in sagittal breast MR images, Medical Physics, vol. 40, no. 4, pp. 042301-12, Apr. 2013.
10. Shandong Wu, Susan P. Weinstein, and Despina Kontos, Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI,Medical Image Computing & Computer-Assisted Intervention (MICCAI), Part II, Lecture Notes in Computer Science (LNCS) 7511, pp. 437-445. H. Delingette, P. Golland, K. Mori (eds.). Springer-Verlag Berlin Heidelberg, Sep. 2012.
11. Kingsley Osuala, Kathleen Telusma, Saad M. Khan, Shandong Wu, Mubarak Shah, Candice Baker, Sabikha Alam, Ibrahim Abukenda, Aura Fuentes, Hani B. Seifein, and Steven N. Ebert, Distinctive left-sided distribution of adrenergic-derived myocytes in the adult mouse heart, PLoS ONE, vol. 6, no. 7, pp. e22811, Jul. 2011.
12. Shandong Wu, Omar Oreifej, Mubarak Shah, Action Recognition in Videos Acquired by a Moving Camera Using Motion Decomposition of Lagrangian Particle Trajectories, International Conference on Computer Vision (ICCV2011), Barcelona, Spain, 6-13 Nov. 2011.
13. Shandong Wu and Y.F. Li, Motion Trajectory Reproduction from Generalized Signature Description, Pattern Recognition, vol. 43, no. 1, pp. 204-221, Jan. 2010.
14. Shandong Wu, Brian E. Moore, and Mubarak Shah, Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes, IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13-18, 2010.
15. Shandong Wu and Y.F. Li, Flexible Signature Descriptions for Adaptive Motion Trajectory Representation, Perception and Recognition, Pattern Recognition, vol. 42, no. 1, pp. 194-214, Jan. 2009.
16. Shandong Wu and Y.F. Li, On Signature Invariants for Effective Motion Trajectory Recognition, The International Journal of Robotics Research, vol. 27, no. 8, pp. 895-917, Aug. 2008.