Scott Viteri
CS PhD Candidate At Stanford
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolScott Viteri is a Stanford CS PhD candidate focused on AI alignment and augmenting human intelligence to reduce existential risk, with 11 years of experience spanning AI, robotics, and programming languages. He combines deep theoretical grounding—MIT CS&EE undergrad and prior work in category theory, SMT solving, and interactive theorem proving—with hands-on robotics and systems engineering (contributions to the Drake robot locomotion repo and past DARPA/ROS projects). His research blends ontology mapping, neural network interpretability, and formal methods to bridge disparate intelligences, a direction he pivoted to in recognition of its moral significance. Comfortable moving between Coq reification plugins, SMT tools, and real-world robot simulations, he brings curiosity-driven rigor and a fondness for math to high-impact, interdisciplinary problems.
11 years of coding experience
3 years of employment as a software developer
Bachelors Degree, Computer Science and Electrical Engineering, Bachelors Degree, Computer Science and Electrical Engineering at Massachusetts Institute of TechnologyHigh School, High School at Chaparral High School, Scottsdale, Arizona
Spanish
Stackoverflow
43reputation
3kreached
0answers
1question
Github Skills (7)
urdf10
robotics10
drake10
matlab9
functional-programming6
openscad6
3d6
Programming languages (10)
Github contributions (5)
RobotLocomotion/drake
Oct 2014 - Jul 2015
Model-based design and verification for robotics.
Role in this project:
Back-end Developer & Robotics Engineer
Back-end Developer & Robotics EngineerContributions:19 commits, 8 PRs, 6 comments in 9 months
Contributions summary:Scott contributed to the development of robotics models and simulations within the Drake framework. Their work primarily involved creating and modifying URDF files to define virtual office environments and other robot models for simulation. The user also made changes to configuration files and model definitions, suggesting a focus on integrating and visualizing these models within the Drake system, demonstrating an understanding of robotics simulation environments.
roboticsdrake
scottviteri/MarkovianTraining
Jul 2023 - Apr 2026
Code and artifacts for the ICLR 2026 paper on rewarding chains of thought for being useful context for a model's own answer.
Contributions:59 PRs, 1140 pushes, 69 branches in 2 years 9 months
ai-alignmentchain-of-thoughtgrpoiclr-2026language-models
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