Dr. Long is an Associate Professor at the UCLA Anderson School of Management. Her research concentrates on healthcare operations management and entails developing data-driven mathematical models of disease progression or healthcare systems. The primary goal is to improve medical decision-making under uncertainty and, ultimately, to strengthen the efficiency and quality of healthcare delivery. At UCLA, she teaches the core probability and statistics course for MBA students. She was previously a faculty member at the Yale School of Management, and received a PhD in Management Science & Engineering from Stanford and a BS in Operations Research from Cornell.

In 2014, Elisa was diagnosed with triple-negative breast cancer at the age of 33, and subsequently learned that she carries a BRCA1 genetic mutation despite no family history. As many survivors can attest, undergoing cancer treatment involves a tornado of dense information, ambiguous statistics, and complex decisions that must be made during a highly sensitive time. The experience inspired Elisa to develop an online decision support tool to help fellow BRCA sisters facing similar circumstances, so that every woman can have the best information available to make the right personalized decision for herself.

For questions about the BRCAlive tool, please contact Dr. Elisa Long at elisa.long@anderson.ucla.edu.

Eike Nohdurft, PhD

Research Collaborator
Solution Manager at McKinsey & Company

Dr. Nohdurft’s research interests are to enable physicians and patients make more informed decisions, and previously built mathematical models for several healthcare-related decision problems, including cancer prevention in BRCA carriers and resource allocation for the Ebola epidemic in West Africa.

Eike received a PhD from WHU, Otto Beisheim School Management in Vallendar, Germany and collaborated with Professor Long on developing the mechanics behind BRCAlive. In his current role at McKinsey in Hamburg, he assists clients with reducing product and procurement complexity through leveraging advanced analytics techniques on large-scale datasets.

Dr. Ganz is a medical oncologist and Distinguished Professor at the UCLA David Geffen School of Medicine and the UCLA Fielding School of Public Health. She directs the Center for Cancer Prevention & Control Research at the UCLA Jonsson Comprehensive Cancer Center, where she leads the scientific program focused on Patients and Survivors. She was elected to the Institute of Medicine in 2007 and received the American Cancer Society Medal of Honor in 2010. She previously served on the National Cancer Institute Board of Scientific Advisors and on the American Society of Clinical Oncology Board of Directors. She received an MD from UCLA and a BA from Harvard.

Dr. Ganz has focused much of her clinical and research efforts in the areas of breast cancer and its prevention. In 1997, she established the UCLA Family Cancer Registry and Genetic Evaluation Program, which serves patients, survivors, and those at high risk for familial/hereditary cancers. She has authored more than 400 peer-reviewed publications and edited four books on evidence-based cancer care, survivorship and quality of care, and breast cancer outcomes.

Tianyang Liu

Web Developer

Tianyang implemented the statistical model of personalized cancer risk predictions using R Shiny, and added new surgery selection features for users. He is currently a master’s student in Applied Statistics at UCLA, and previously received a BS in Applied Mathematics also at UCLA.

Yidan Wang, MS

Web Developer
Software Engineer at Google

With a background in data analytics and software engineering, Yidan helped develop interactive data visualizations for the BRCAlive Tool, and scripts to optimize the algorithm through data sharing, aggressive caching and smarter sampling. He received a master’s in Business Analytics at UCLA and a master’s in Computer Science at Cornell University.