Walker Gosrich
Data & Policy Lead AI Policy
Philadelphia, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolWalker Gosrich is a data-driven AI policy lead and PhD candidate with eight years of experience at the intersection of multi-agent robotics, machine learning, and science policy. Currently advising New Jersey state government on responsible AI deployment and authoring staff-use AI policy, he pairs technical depth—Graph Neural Networks and network-flow task allocation for multi-robot systems—with practical governance expertise on AI bias, autonomous weapons, and public-sector GenAI integration. He has a track record of translating research into deployable tools and methods, leading interdisciplinary teams from swarm micro-robot construction to state-level AI tool development. As co-president of a major university science policy group and a former GAO analyst, he blends technical publication and grant success with high-impact policy briefs presented to federal and state stakeholders. Notably, he brings an engineer’s rigor to policy evaluation, developing novel methodologies for measuring AI’s societal and environmental impacts.
8 years of coding experience
4 years of employment as a software developer
Advanced Regents Diploma with Honors, 98.5, Advanced Regents Diploma with Honors, 98.5 at Plattsburgh High SchoolBachelor's Degree, Mechanical Engineering, 4.0, Bachelor's Degree, Mechanical Engineering, 4.0 at University at BuffaloPh.D., Mechanical Engineering and Applied Mechanics, Ph.D., Mechanical Engineering and Applied Mechanics at University of PennsylvaniaProgramming languages (1)
Github contributions (5)
snarayan21/task-graphs
Apr 2021 - May 2024
task assignment for multirobot teams with new, expressive task graph formulation. submitted to ICRA 2023.
Contributions:29 PRs, 117 pushes, 18 branches in 3 years
task-graphexpressiveicragraphformulation
wgosrich/task-allocation-testbed
Jun 2020 - Aug 2020
Contributions:73 commits, 49 pushes, 1 branch in 2 months
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