Olga Goloubeva, PhD, MSc
Olga Goloubeva, PhD, MSc, is a UMGCCC faculty biostatistician and a Professor in the Department of Epidemiology and Public Health, University of Maryland School of Medicine. Dr. Goloubeva received her Ph.D. in engineering. She continued her graduate training in mathematical statistics and in 1999 earned a Master's degree in mathematical statistics from Dalhousie University, Halifax, Canada. She was an assistant professor in the Department of Mathematics and Computer Studies at the Mount Saint Vincent University, Halifax, Canada (1993-1999). In 1999, she joined St. Jude Children's Research Hospital Cancer Center as a biostatistician, where she collaborated with investigators in virology, diagnostic imaging, and radiation oncology. In 2001, Dr. Goloubeva moved to Dana Farber Cancer Institute, Boston, MA, where she collaborated as a biostatistician in CLL Consortium, the Leukemia Committee for ECOG, and the AIDS Immunology Group.
She joined UMGCCC in 2003 and has been involved in collaborative research throughout the center, including areas in breast, prostate, lung, head and neck cancer, myeloma, radiation oncology, and cancer disparities. She is currently a member of the Cancer Center Clinical Protocol Review Committee, the UMGCCC Tissue Bank Committee, the DSMQAC, UMGCCC and a member of the center's Hormone Related Cancers Program. She is a member of the UM DSM Board for Pediatrics Study of Lactobacillus. Dr. Goloubeva is a member of the NIA IRP Scientific Review Committee and two DSM Boards for NIH/NIA phase I and II clinical trials. She served as an International Topical Expert (Biostatistics & Bioinformatics) and a Voting Member for the cancer center site visit in Innsbruck, Austria. Her statistical expertise lies in the design and analysis of preclinical studies and clinical trials, evaluation of diagnostic tests, biomarkers and their combination, prognostic models of cancer and other diseases, longitudinal and hierarchical data modeling. The ongoing collaboration in research of many different cancers and diseases is reflected in her > 80 peer-reviewed publications.
Yuji Zhang, PhD, MSc
Yuji Zhang, PhD, MSc, is an Assistant Professor in the Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health at the University of Maryland School of Medicine. She is also an adjunct faculty member of the Institute of Global Health, University of Maryland Baltimore and the School of Public Health, University of Maryland College Park. Dr. Zhang received Bachelor's and Master's degrees from Southeast University in Biomedical Engineering and her PhD degree from Virginia Tech in Computer Engineering. Before joining the University of Maryland in 2014, she was an Assistant Professor at Mayo Clinic College of Medicine (2011-2014). Dr. Zhang has participated in numerous federally funded research programs in many disease areas, including many types of cancer, immunology, heart diseases, and vaccine). Specifically, she has served as Co-Investigator leading the bioinformatics and statistical effort in several NIH-funded consortium projects including the International Consortium for Prostate Cancer Genetics (ICPCG), the consortium of Extracellular non-coding RNA biomarker discovery of hepatocellular cancer, and the NHLBI Progenitor Cell Translational Consortium. As the lead faculty bioinformatician at UMGCCC and UMMC, Dr. Zhang has been actively collaborating with PIs at UMGCCC as well as other basic and translational research programs, leading to several successful research programs. Since 2011, Dr. Zhang has also been organizing/co-organizing several international workshops in the informatics field. She is the guest editor/referee for over 40 international peer-reviewed journals.
Dr. Zhang's research focuses on developing translational informatics approaches to reveal novel human disease mechanisms. She has interdisciplinary training background in bioinformatics, Computer Engineering, and Oncology. Dr. Zhang has over ten years of research experience in integrative analysis of multi-source high-dimensional biological data for novel association discovery between different biological entities (e.g., disease, drug, and gene) under different biological states. In addition, she has extensive collaborative research experience in medical informatics, ontology, software engineering, and biomedical and basic science fields. Her current research mission is to leverage the gap between the analytical needs of arising from multi-source biological "big" data in biomedical research and advanced informatics approaches.