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Rad-onc researcher, data scientist join UMMC faculty

Published on Thursday, October 27, 2016

Published on October 27, 2016

The Medical Center is proud to announce the following additions to its faculty and leadership staff.

Swati Dhar, Ph.D.


Dr. Swati Dhar, a former postdoctoral research fellow at the UMMC Cancer Institute, has joined the Medical Center faculty as an instructor in radiation oncology.

She completed her doctoral studies focusing on T cell immunotherapy for breast and prostate cancer at the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai, India, in 2009. She then served as a senior scientist in the R&D Department of Biocon LLC, India's largest biopharmaceutical company, in 2010 before coming to the UMMC Cancer Institute in 2011 as a postdoctoral research fellow in the lab of Dr. Anait S Levenson. Presently, she is working in the lab of Dr. Yin-Yuan Mo on gene editing mechanisms.

The author or coauthor of 10 scientific peer-reviewed publications, one book chapter and more than 15 national and international presentations, she also serves as an ad hoc reviewer for Libertas Academica publications. She also is an associate member at the American Association for Cancer Research. Her research interests include mechanisms of tumor immune evasion and role of non-coding RNAs in oncogenesis.


Yunyun Zhou, Ph.D.


Dr. Yunyun Zhou, previously a computational biologist at UT Southwestern Medical Center in Dallas, has joined the Medical Center faculty as an assistant professor in the Department of Data Science.

After receiving her B.S. in electrical engineering in 2004 and her M.S. in electrical engineering in 2007 from Nanjing University, China, Zhou earned her Ph.D. in electrical and computer engineering at Washington State University, Pullman, in 2012. She then joined the UT Southwestern Medical Center faculty as a computational biologist.

The author or coauthor of 17 articles in peer-reviewed professional publications, Zhou has been a participant in a number of National Institutes of Health-funded scientific projects. Her research interests include machine learning applications in quantitative biomedical data, such as cancer, cardiovascular disease, depression, etc.

She has established high throughput computational skills on NGS data analysis, such as WGS, mRNAseq, MethySeq, etc. She also has focused on tools development, such as translating her novel algorithms and research findings to user-friendly software and database with the hope of contributing precision medicine in high quality big-data areas.