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.
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.
Zahra Razaee, PhD, is a postdoctoral scientist at the Samuel Oschin Comprehensive Cancer Institute. She received her MA in statistics from the University of Michigan, Ann Arbor, in 2014 and a PhD in statistics from UCLA in 2017. While doing her PhD at UCLA, she was a main instructor in Introduction to Statistical Programming in R and also a statistician at the UCLA Statistical Consultation Center. Her research experience lies in the intersection of machine learning and statistical network analysis with application to biomedical data. She currently works on dose finding for drug combination in phase I/II clinical trials using Bayesian approaches under the supervision of Mourad Tighiouart, PhD.
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.
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 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.
Michael Luu, MPH, is a research biostatistician at the Samuel Oschin Comprehensive Cancer Institute. Luu received his master’s in public health with an emphasis in biostatistics and epidemiology at the University of Southern California in 2015. He is a proficient R programmer who was also trained in SAS, STATA and SPSS. His experience involves survival analysis, predictive modeling and data visualizations, among other areas. Current and past projects involve analysis of large national inpatient databases such as the National Cancer Database, SEER-Medicare from the National Cancer Institute, Healthcare Cost and Utilization Project, California’s Office of Statewide Health Planning and Development and Pediatrics Health Information Systems. Before joining Cedars-Sinai in 2016, he served as a biostatistician at Children’s Hospital Los Angeles for the Division of Neonatology and Department of Anesthesia Critical Care Medicine.
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Translations may not be available for some articles, including PDF documents, maps, video legends and text that appears in the photos. Also, some of the features on the website may not work in the translated versions.