Janet is a results-oriented and CELT Certified analytical consultant with several years of experience in evaluating process variations and risk factors through statistical modeling. Moreover, she excels at utilizing in-depth working knowledge of project management techniques, including process mapping and logic building to increase efficiency and streamline the communication process. she is skilled at applying quantitative analysis and data-mining skills to develop deep analytical insights around product usability, correctness, and the end-to-end experience across a variety of data sets and platforms. She is highly effective at working in cross-functional teams and fostering long-term professional relationships with key stakeholders to achieve organizational objectives. In her spare time, Janet is an outdoorsy person, a big fan of Marvel movies, and loves to spend time with her dog and family.

Dr. Disep Ojukwu is a research assistant in the Department of Neurosurgery at Stanford University School of Medicine. Under the direction of Dr. Atman Desai, Dr. Ojukwu focuses on health disparities in spinal neurosurgery outcomes. She received her MD/MBA dual degree from St. George’s University School of Medicine and her Master of Public Health (MPH) degree from Loma Linda University School of Public Health as a triple major in epidemiology, international health, and biostatistics. She obtained her Bachelor of Science degree in Biochemistry from UCLA. Before attending medical school, she worked as a public health statistician at a county health department in California and was actively involved in investigating disparate health outcomes among minority communities

Golnaz Moallem is a postdoctoral research fellow at the Personalized Integrative Medicine Laboratory in the Department of Radiology at Stanford University. Her research interests include machine learning and computer vision applications in clinical data analysis, particularly the design and development of deep vision systems for medical image analysis including image classification and object detection. She completed her B.S. degree in electrical engineering from Isfahan University of Technology, and her M.S. and PhD degrees in Electrical Engineering from Texas Tech University.

Paymon was born and raised in the San Francisco Bay Area, before heading to Los Angeles for his undergraduate studies. At UCLA, he received his Bachelor’s and Master’s degrees in Bioengineering, with a concentration in Neuroengineering. Paymon then moved back to the Bay Area to conduct research for Stanford’s Spine Artificial Intelligence Laboratory, Neural Prosthetics Translational Laboratory (NPTL), and Radiological Sciences Laboratory (RSL). He is currently an M.D./M.B.A candidate at Tulane University School of Medicine, while continuing his research efforts for Stanford’s Spine Outcomes Laboratory. His research interests include the development and implementation of artificial intelligence methods to impact healthcare practices within neurosurgery.

Michael Jin is a current Stanford medical student interested in leveraging big data analytics to understand and predict neurosurgical outcomes. He has co-authored manuscripts published in journals such as Neurosurgery, Journal of Neurosurgery, and The Spine Journal, while contributing several textbook chapters and conference podium presentations at national and international neurosurgery meetings. His hobbies include hiking, traveling, and photography, and he derives his motivation from all his mentors at Stanford Neurosurgery as well as the all the patients he has the privilege to interact with and their stories.