Harvard Catalyst Profiles

Contact, publication, and social network information about Harvard faculty and fellows.

Zezhong Ye, Ph.D.

Title
Institution
Department
Address
Profile Picture

Biography
Xiamen University, Xiamen, ChinaB.S.07/2012Chemistry
Washington University, St. Louis, MOM.A.08/2015Physical Chemistry
Washington University, St. Louis, MOPh.D.06/2019Physical Chemistry
Washington University School of Medicine, St. Louis, MOPostdoc02/2021Radiology
Harvard Medical School, BostonPostdocRadiation Oncology
2020
ISMRM Summa Cum Laude Merit Award
2019
ANA Annual Meeting Poster Award
2019
ISMRM Summa Cum Laude Merit Award
2018
JMRI Distinguished Reviewer Award
2018
RSNA Travel Award for Young Investigators
2018
ISMRM-ESMRMB Magna Cum Laude Merit Award
2017
ISMRM Magna Cum Laude Merit Award
2015
Siteman Cancer Center Oncologic Imaging Program Poster Award

Overview
I am a postdoctoral research fellow in radiation oncology and artificial intelligence (AI) in medicine. My current research is focused on developing, validating and applying novel AI algorithms to address a wide range of clinical challenges in the area of radiation oncology. I am interested in combing state-of-the-art AI techniques (e.g. deep learning (DL), radiomics) and cancer imaging (e.g. CT, MRI) to develop clinical decision-making tools that advance personalized cancer care and can be effectively translated into the clinic. I am particularly interested in building fully-automated imaging-based scan-to-prediction platform to better predict cancer patient outcomes that could facilitate and optimize clinical trials as well guide treatment personalization strategies. My current working projects include DL outcome prediction studies on head and neck cancer (HNC) as well as pediatric low-grade glioma. Previously, I have worked on developing advanced diffusion MRI methods along with machine learning algorithms to noninvasively detect and characterize multiple types of cancers, including glioblastoma (GBM), high-grade pediatric brain tumor as well as prostate cancer.

Bibliographic
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
Updating...
This operation might take several minutes to complete. Please do not close your browser.
Local representatives can answer questions about the Profiles website or help with editing a profile or issues with profile data. For assistance with this profile: HMS/HSDM faculty should contact contactcatalyst.harvard.edu. For faculty or fellow appointment updates and changes, please ask your appointing department to contact HMS. For fellow personal and demographic information, contact HMS Human Resources at human_resourceshms.harvard.edu. For faculty personal and demographic information, contact HMS Office for Faculty Affairs at facappthms.harvard.edu.
Ye's Networks
Click the
Explore
buttons for more information and interactive visualizations!
Concepts (61)
Explore
_
Co-Authors (32)
Explore
_
Similar People (60)
Explore
_
Same Department 
Explore
_
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.