Postdoctoral Fellow at KTH Royal Institute of Technology
Stockholm, Sweden
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Summary
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Yixi Cai is a robotics postdoctoral fellow at KTH’s Digital Futures with eight years of experience bridging academic research and efficient, production-minded code. Holding a PhD in Mechatronics, Robotics, and Automation from The University of Hong Kong and a BE from Beihang, she focuses on how robots perceive and model the world, especially through spatial data structures. Her open-source work includes refactoring and optimizing an incremental k-d tree implementation to remove PCL dependencies, tighten performance, and simplify builds—demonstrating a knack for both core algorithm design and pragmatic engineering. Based in Stockholm, she combines rigorous research with hands-on systems development, favoring lightweight, custom data types for real-time robotic applications.
8 years of coding experience
Bachelor of Engineering - BE, Automation, 3.84/4.0, Bachelor of Engineering - BE, Automation, 3.84/4.0 at Beihang University
This repository provides implementation of an incremental k-d tree for robotic applications.
Role in this project:
Back-end Developer
Contributions:96 commits, 6 PRs, 32 pushes in 1 year 3 months
Contributions summary:Yixi's primary contribution focused on refactoring and optimizing the incremental k-d tree implementation. They deleted the dependency on the PCL library and implemented a custom point type and vector for improved efficiency. Further commits involved removing debugging statements and comments to clean up the code. Finally, they integrated a makefile to manage the build process and updated the demo file, showcasing their efforts in core algorithm implementation and project setup.
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Yixi Cai - Postdoctoral Fellow at KTH Royal Institute of Technology