Eric A. RossView profile
Research Professor
Eric A. Ross is a Research Professor and Assistant Vice President of Biometrics and Information Sciences at Fox Chase Cancer Center, where he directs both the Biostatistics and Bioinformatics Facility and the Population Studies Facility within the Cancer Prevention and Control program. He holds a PhD in Statistics from Temple University, an ScM in Biostatistics from Johns Hopkins University, and a BA in Biological Sciences from the University of Delaware. His research interests include biostatistics, bioinformatics, clinical trial design, cancer research, and health informatics. He specializes in developing innovative statistical methodologies for oncology trials and integrating large-scale data using web-based technologies to improve cancer research and patient outcomes. His recent publications highlight a strong focus on clinical trial methodology, molecular oncology, and data integration. Key themes include risk-adapted therapies for bladder cancer, confounding control in clinical studies, and reproductive factors in breast cancer. His work often involves multicenter collaborations and leverages genomic and epidemiological data to identify biomarkers and optimize treatment strategies. Dr. Ross is a member of the American Statistical Association and the International Biometrics Society. His scientific contributions are reflected in over 200 peer-reviewed publications, with recent work appearing in high-impact journals such as Journal of Clinical Oncology , Annals of Internal Medicine , and Clinical Cancer Research . He leads a multidisciplinary team providing biostatistical and informatics support across clinical, translational, and basic science research at Fox Chase. His lab emphasizes improving research efficiency, data quality, and the application of advanced computational tools in cancer investigations. He has collaborated extensively with researchers in urology, oncology, and epidemiology, contributing to significant advances in personalized cancer therapy and data-driven decision making.







