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Samuel Oschin Comprehensive Cancer Institute
Zhenqiu Liu, PhD, is the director of Bioinformatics at the Samuel Oschin Comprehensive Cancer Institute and associate professor in the Department of Medicine's Hematology/Oncology Division, and the Department of Biomedical Sciences. Prior to joining Cedars-Sinai, he was an associate professor of bioinformatics at the Department of Epidemiology and Public Health and Greenebaum Cancer Center, University of Maryland School of Medicine. Liu's research is in the broad area of bioinformatics, computational biology, and big data mining and has been funded by the National Cancer Institute and National Science Foundation. Currently his research is concentrating on survivorship prediction, biomarker identification, and pathway and network constructions with multi-source genomic data. Liu has extensive collaborative research experiences in laboratory investigations, biomarker evaluation, genomics, clinical and epidemiological researches. He earned a PhD in Operations Research with a concentration in data mining, as well as a master's degree in Computer Science, from the University of Tennessee at Knoxville. His postdoctoral training was at the Bioinformatics Cell, Telemedicine and Advanced Technology Research Center in Fort Detrick, MD, and at the Department of Statistics at Ohio State University.
Arkadiusz Gertych, PhD, is an assistant professor in the Department of Surgery and an adjunct faculty member in the Department of Pathology and Laboratory Medicine at Cedars-Sinai Medical Center. Since 2011 he has also been a research faculty member at the Biomedical Engineering Department at the University of Southern California. He received his PhD from the Silesian University of Technology of Gliwice, Poland, in 2003, and completed his postdoctoral fellowship in medical imaging and informatics at USC in 2007. Gertych has an interdisciplinary background and experience in the design and development of biomedical image analysis and pattern recognition applications in medicine, was honored one cum laude and three Certification of Merit awards by Radiological Society of North America for scientific accomplishments, and is a recipient of a grant from the National Institutes of Health. His group develops machine learning tools for studies of cellular heterogeneity in tissues, and for the recognition of tumor growth patterns to aid with challenging histopathological diagnoses. Gertych has been active as a scientific reviewer for numerous journals in theoretical and applied areas of computer science and image processing.
Miriam Nuño, PhD, is an assistant professor of Neurosurgery and a senior biostatistician in the Department of Neurosurgery. She completed her PhD in the department of Biological Statistics and Computational Biology at Cornell University in 2005 and master's degree in Applied Mathematics at Claremont Graduate University. Prior to joining Cedars-Sinai, Nuño completed a postdoctoral position at Harvard School of Public Health and UCLA Department of Biostatistics. Her experience and interests include longitudinal data analysis, missing data methods, and multivariate analysis. Mathematical modeling, prediction and simulation in the areas of emerging infectious diseases and prevention are also strong interests and experience of Nuño.
Nan Deng, PhD, is a senior research bioinformatican at the Samuel Oschin Comprehensive Cancer Institute. Prior to joining Cedars-Sinai, she was a research assistant at the Computational Biology & Data Mining Group in the Department of Computer Science at Wayne State University in Detroit, where she earned her PhD in computer science in 2014. Deng has strong computational and analytic skills with a broad interdisciplinary background in computer science, bioinformatics and statistics. She has extensive experiences in algorithm design and implementation, statistical model building and next generation sequencing (NGS) data analysis. Deng has developed novel algorithms and computational software tools for transcriptome quantification, characterization and identification using RNA-Seq, in particular detecting various types of differential splicing events between healthy and diseased human transcriptomes. She is also seeking opportunities to collaborate with biomedical researchers to study and better understand life-threatening human diseases by integrating genomics, transcriptomics, epigenetics and proteomics.
Márcio Augusto Diniz, PhD, is a faculty biostatistician at the Samuel Oschin Comprehensive Cancer Institute. He received a MS in statistics from the University of Campinas, Brazil, in 2009 and a PhD in statistics from the University of São Paulo, Brazil, in 2015. Before joining Cedars-Sinai, Diniz worked as a statistician for three years at the Medical School at the University of São Paulo, where he contributed his expertise in design of experiments, data analysis for using appropriate statistical methodologies, and teaching statistics for investigators. His experience and interests include applications of Bayesian analysis in medical research and regression models with focus on categorical and time to event responses. Ongoing projects include developing of time to event models to dose combination of cytotoxic and biologic agents in phase I clinical trials and statistical software for EWOC.
Catherine Bresee, MS, is a senior biostatistician at the Samuel Oschin Comprehensive Cancer Institute. She received her MS in biostatistics from UCLA in 2008. Previously, Bresee served as a research associate at Cedars-Sinai, Michigan State University and Lovelace Research Institute in New Mexico. She has 20 years of clinical and pre-clinical research experience. Her current interests are in clinical trial design, protocol development, and grant writing as well as longitudinal data analysis. Bresee is the biostatistical reviewer for the Cedars-Sinai Institutional Animal Care and Use Committee. She is involved in ongoing projects with the Wasserman Breast Center and the Women's Cancer Research Institute, as well as with non-cancer-related projects in urology, endocrinology, surgery and regenerative medicine.
Galen Cook-Wiens, MS, is a senior biostatistician at the Samuel Oschin Comprehensive Cancer Institute. He received an MS in biostatistics from the University of Michigan in 2006 and an MS in mathematics from the University of Iowa in 2004. Before joining Cedars-Sinai, Cook-Wiens was a senior research analyst at the University of Kansas Medical Center in Kansas City for five years. His experience includes longitudinal modeling, mixed models, propensity scoring and survival analysis. Current projects include working with regenerative medicine, the women's cancer research institute and developing EWOC software, among others.
Quanlin Li, MS, is a senior biostatistician at the Samuel Oschin Comprehensive Cancer Institute. He received an MS in statistics from Duke University in 2008 and an MS in environmental science from Peking University, China in 2004. Before joining Cedars-Sinai, Li was a statistician at the U.S. Environmental Protection Agency in Chapel Hill, North Carolina, for four years. Li has strong statistical background and programming skills. He works with investigators on study design, database management and conducts statistical analysis. Ongoing projects include multi-state survival analysis, multiple imputation method for missing data, and developing software applications in cancer phase I clinical trial (EWOC).
Sungjin Kim, MS, is a senior biostatistician at the Samuel Oschin Comprehensive Cancer Institute. She received an MS in biostatistics from UCLA in 2006. Before joining Cedars-Sinai, Sungjin was a senior biostatistician providing statistical expertise in study design, data analysis, and proposal/manuscript preparation for clinical and pre-clinical investigators at the Winship Cancer Institute of Emory University in Atlanta. She has many years of collaborative experience in various cancer researches, biomarker studies, and health service researches. Her experiences include survival analysis, longitudinal data analysis, receiver operating characteristic (ROC) analysis, propensity score analysis, meta-analysis, joinpoint regression analysis, and early phase clinical trials designs.
Heidi Gransar, MS, CCRP, is a research biostatistician in the Division of Cardiac Imaging and Nuclear Cardiology at the S. Mark Taper Foundation Imaging Center, Department of Imaging. She received her master's in biostatistics from UCLA in 2001 and has been at Cedars-Sinai since 2000. She does statistical analysis, consulting, assists in study design, and also database management for researchers in her department. She occasionally gives lectures to fellows and student interns on statistical topics. Gransar mainly uses STATA and SAS.
Jinrui Cui, MS, has been s a research biostatistician III at the Medical Genetics Institute since October 2002. He received his MS in statistics from UCLA in 2002. Cui has strong background in statistical genetics and extensive experience in programming of SAS and other statistical package. He works with investigators on study design, data collection and data management, performs increasingly complex statistical and genetic analyses, and interprets results and reports. He has been playing a major role in several cardiovascular and metabolic diseases-related family based linkage, GWAS and candidate gene studies.
James Mirocha, MS, is a senior biostatistician in the Research Institute and the Samuel Oschin Comprehensive Cancer Institute. He received his MS in mathematics from the University of Minnesota in 1975. He finished PhD coursework and qualifying exams in statistics and quantitative methods in the Graduate School of Education and Information Studies at UCLA in 2001 (ABD). Mirocha has extensive teaching experience in mathematics and statistics at the high school, community college and university levels. He has been at Cedars-Sinai since 1999. Mirocha serves on the Scientific Advisory Committee in the Clinical and Translational Research Center and on the Institutional Review Board. His main interests are in the areas of power analysis, propensity modeling, mixed and longitudinal modeling, and survival analysis. Ongoing projects are with Cardiothoracic Surgery, Trauma Research, Cardiology, Psychiatry, Pathology, Transplant and the Cancer Center.