Stanford University
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Jack Topper
Graduate, Stanford Center for Professional Development
BioJack Topper is a Scientific Software Engineer at NASA’s Community Coordinated Modeling Center (CCMC), where he designs and operates large-scale scientific data and modeling systems supporting the global space-weather research community. His work focuses on automating high-performance computing workflows, building resilient data pipelines, and translating complex scientific models into reliable, user-facing services.
He collaborates closely with domain scientists to bridge research objectives and production-grade software, and has taken on technical leadership responsibilities spanning system architecture, reliability, and user adoption. His interests sit at the intersection of optimization, decision systems, machine learning, and large-scale infrastructure, with an emphasis on how mathematical models and data-driven methods inform real-world operational decisions.
Jack is currently pursuing Stanford’s Data, Models, and Optimization Certificate through the Stanford Center for Professional Development, including coursework in convex optimization and related decision-science foundations. -
Alice Tor
Ph.D. Student in Electrical Engineering, admitted Autumn 2022
BioPhD candidate in Electrical Engineering, advised by Dr. Paul Nuyujukian
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Diana Tordoff
Instructor, Obstetrics & Gynecology - General
BioDiana M. Tordoff, PhD, MPH is an epidemiologist with expertise in LGBTQ+ health equity and gynecological health research. Dr. Tordoff completed her PhD and MPH in Epidemiology at the University of Washington and received a BA with honors in Mathematics from Vassar College. She is also an affiliated researcher with The PRIDE Study (pridestudy.org), where she recently completed a postdoctoral fellowship. Her current research focuses on the impact of exogenous hormones (gender affirming hormones and menopause hormone therapy) on sexual and gynecological health. Her research interests include sexual and reproductive health, menopause, the vaginal microbiome, molecular epidemiology, intersectionality, and community-engaged research methods.
