Ana Quispe is a research scientist with 14 years of experience building robot manipulation pipelines that enable bimanual manipulators to handle household objects with partial or missing information. Based at TRACLabs in Houston, she blends perception, planning, and control expertise from a PhD in Robotics at Georgia Tech to deliver practical, end-to-end solutions for autonomous manipulation and motion planning. Her work spans academic and industry settings—from Google Summer of Code contributions to OpenCV and PCL to adding a planning library to the widely used DART robotics toolkit—demonstrating strong back-end and kinematics skills. Known for choosing grad school after reading an RRT paper, she combines a theorist’s curiosity with a practitioner’s focus on benchmarking and real-world utility.
14 years of coding experience
7 years of employment as a software developer
BS, Mechatronics Engineering, BS, Mechatronics Engineering at Universidad Nacional de Ingenieria
Master of Science (MSc), Computational Perception and Robotics, Master of Science (MSc), Computational Perception and Robotics at Georgia Institute of Technology
Contributions:137 commits, 4 comments, 2 issues in 2 years 4 months
Contributions summary:Ana contributed to the `dartsim/dart` project by adding a planning library to the codebase. The primary focus of the code additions appears to be the implementation of the core classes, like `World`, `Object`, `Robot`, and `Robot`, that would serve as a foundation for planning functionalities. Their work included the creation of header and implementation files, indicating the development of backend logic and class structures. The modifications also suggest work related to kinematics.
Contributions:2 PRs, 2 pushes, 1 branch in 2 years 9 months
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