Sara Sepasian is a Software Engineer with 10 years of experience building infrastructure, internal tooling, and backend services at Facebook in San Francisco. She blends a strong engineering foundation (BS in Computer Engineering, MEng in Engineering Management) with research experience in AI and neuroscience, having contributed usability-focused documentation and example datasets to the pycortex fMRI visualization toolkit. Beyond production engineering, she teaches and mentors at Hackbright Academy and has created curricula to help women transition into tech, reflecting a long-term commitment to widening access for underrepresented groups. Sara also applies her operational skills to civic causes, co-leading a national PPE sourcing effort during COVID-19 and serving on nonprofit boards to drive product and performance improvements. Known for clear technical communication and practical problem-solving, she moves between low-level firmware, backend systems, and data-science adjacent tooling. Her profile combines production-scale infrastructure work with hands-on education and impactful open-source contributions.
10 years of coding experience
7 years of employment as a software developer
San José State University
Master of Engineering - MEng, Engineering Managment and leadership specialized in software, Master of Engineering - MEng, Engineering Managment and leadership specialized in software at Santa Clara University
SPCS, Theoretical and Mathematical Physics, Decision Leadership and Negotiation, SPCS, Theoretical and Mathematical Physics, Decision Leadership and Negotiation at Stanford University
Pycortex is a python-based toolkit for surface visualization of fMRI data
Role in this project:
Full-stack Developer
Contributions:74 commits, 12 PRs, 49 pushes in 3 years 3 months
Contributions summary:Sara primarily contributed to the documentation and example datasets within the pycortex repository, significantly enhancing the project's usability. They added new examples for visualizing different types of data, including volume, vertex, and RGB data, and expanded on existing examples by incorporating features like colormaps, 2D visualizations, and arithmetic operations. Furthermore, the user updated descriptions and clarified the purpose and functionality of various plotting methods, like those for geodesic paths, and retinotopy data.
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