Paris Syminelakis
Staff Software Engineer - Autonomy Evaluation
Washington DC-Baltimore Area United States
Summary
👤
Senior🎓
Top SchoolParis Syminelakis is a Staff Software Engineer and ML researcher with a decade of experience building evaluation frameworks and statistical tooling for autonomy and high-stakes systems. He combines a Stanford Ph.D. in Electrical Engineering and deep theoretical work — including the fastest-known algorithms for fast evaluation of kernel methods in high dimensions — with hands-on product delivery at Cruise and GM, where he led teams producing simulation signal-density, coverage tooling, and regulatory compliance metrics. His background spans systematic trading research at Voleon, sub-linear algorithms at Berkeley, and prior work in recommender systems and systems biology, giving him a rare blend of theory, applied statistics, and domain diversity. Known for turning complex probabilistic ideas into operational metrics and pipelines, he also designs onboarding curricula and rapid metric development processes that scale across cross-functional teams.
10 years of coding experience
2 years of employment as a software developer
Diploma Electrical and Computer Engineering, Diploma Electrical and Computer Engineering at National Technical University of AthensDoctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at Stanford University
Github Skills (22)
dimensions8
convex8
minecraft8
numerical-optimization7
convex-optimization7
ubuntu7
optimization7
chroot6
kernel6
modeling6
python6
debian6
evaluation6
shell5
chromeos5
Programming languages (2)
Github contributions (3)
kexinrong/rehashing
May 2019 - May 2019
fast kernel evaluation in high dimensions via hashing
Contributions:34 commits, 3 pushes, 1 comment in 6 days
hashingkerneldimensionsevaluation
cvxpy/cvxpy
Sep 2015 - Sep 2015
A Python-embedded modeling language for convex optimization problems.
Contributions:1 comment, 1 issue in 1 day
pythonconvex-optimizationproblemsoptimizationconvex
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