Toni Rosiñol is a PhD-trained robotics and AI founder based in San Francisco with a decade of experience, co-founding Stack AI (YC W23) to deliver enterprise GenAI for IT. He bridges research and product: his MIT-era SLAM and geometry work surfaces in open-source contributions to GTSAM, NeRF‑SLAM and Kimera (including low-level Jacobian/retraction and cheirality fixes that improve geometric robustness). Toni combines hands-on systems engineering with customer-facing leadership—running customer support/CEO duties at Stack AI while also investing as an angel. His background spans high-stakes perception work (JPL DARPA SubT) to commercial hardware success (Velohub’s Blinkers, 3k+ units sold), reflecting a rare ability to take complex research into real-world products.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science & Artificial Intelligence., Doctor of Philosophy - PhD Computer Science & Artificial Intelligence. at Massachusetts Institute of Technology
Visiting Student, Mechanical Engineering, Visiting Student, Mechanical Engineering at Nanyang Technological University
Bachelor of Science, Mechanical Engineering, Bachelor of Science, Mechanical Engineering at EPFL (École polytechnique fédérale de Lausanne)
Master of Science, Robotics, Systems and Control, Master of Science, Robotics, Systems and Control at ETH Zurich
Contributions:1 release, 2 reviews, 423 commits in 2 years 8 months
Contributions summary:Toni's commits primarily focus on fixing formatting, indentation, and other code style issues, suggesting a focus on code maintainability and readability. The commits demonstrate interaction with the project's core logic, especially within `RosDataSource.cpp` and `RosbagDataSource.cpp`. The edits are focused on improving the structure and readability of existing code.
Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation.
Role in this project:
Back-end Developer
Contributions:2 releases, 3 reviews, 2681 commits in 3 years 7 months
Contributions summary:Toni's contributions primarily focus on the visual-inertial odometry (VIO) system, specifically related to the feature tracking component. The commits show the user working on tasks such as fixing tests, and refactoring the frontend, potentially enhancing or optimizing the performance of the feature tracker. The code changes involve modification of the feature detection algorithm.
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