Daniel Gelbart
AI Researcher at Cisco Foundation AI
Boulder, Colorado, United States
Summary
👤
Senior🎓
Top SchoolDaniel Gelbart is an AI researcher and quantitative investor with 16 years of technical experience blending software engineering, mathematics, and market microstructure to build automated, market‑neutral trading systems. For over a decade he ran a quantitative fund, designing, back‑testing, and operating hedged strategies that exploit subtle structural inefficiencies across public markets while emphasizing stress testing and uncertainty quantification. His background spans embedded and backend systems engineering (including encryption and web security work) through to large‑scale data automation and real‑time decision frameworks, giving him rare fluency from low‑level performance tuning to statistical model deployment. Now at Cisco Foundation AI he focuses on AI security, bringing a practitioner’s view of robustness and operational risk to model research. He is based in Boulder and combines academic training in computer science, genetics, and mathematics with a pragmatic, systems‑first approach to turn noisy data into repeatable, auditable strategies. Notably, his career consistently marries production-grade engineering discipline with advanced quantitative research—so models are built to survive markets, not just fit historical data.
16 years of coding experience
3 years of employment as a software developer
BSc, Computer Science, Genetics, BSc, Computer Science, Genetics at The Hebrew University of JerusalemMathematics, Mathematics at Weizmann Institute of Science
Github Skills (1)
stock9
Programming languages (2)
Github contributions (5)
danielgelbart/genwriting
Jun 2015 - May 2019
Contributions:152 pushes, 1 branch in 3 years 11 months
danielgelbart/Graham
Mar 2010 - Apr 2019
My little stock portfolio managment and assesment application
Contributions:330 commits, 196 pushes in 9 years 3 months
managmentstockstock-portfolioassesment
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