Jui-te Huang
Research Assistant at Carnegie Mellon University Robotics Institute
Pittsburgh, Pennsylvania, United States
Summary
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Senior🎓
Top SchoolJui-te Huang (Ray) is a robotics PhD student and research assistant at Carnegie Mellon University's Robotics Institute, specializing in radar-inertial odometry and mapping with 4D mmWave imaging radar for robust state estimation in adverse conditions. With eight years of research experience across academia and industry—including internships at Bosch USA and the University of Washington—he focuses on ML and SLAM methods for radar-visual-inertial sensor fusion and radar signal processing. His background includes work on DARPA Subterranean Challenge systems, deep reinforcement learning for UGV navigation, and building LiDAR SLAM and multi-modal sensing stacks. Ray blends signal-level radar expertise with higher-level perception and mapping algorithms, making him adept at turning noisy radar returns into reliable spatial estimates. Based in Pittsburgh, he brings a hands-on approach to bridging theory and real-world robotic deployments. An interesting nuance: he routinely integrates imaging radar concepts from defense and automotive domains to improve autonomy in GPS-denied and visually degraded environments.
8 years of coding experience
3 years of employment as a software developer
MS, BS, Electrical and Computer Engineering, MS, BS, Electrical and Computer Engineering at National Chiao Tung UniversityDoctor of Philosophy - PhD, Robotics, Doctor of Philosophy - PhD, Robotics at Carnegie Mellon University
Github Skills (15)
deep-learning6
machine-learning6
xla5
robotics4
neural-network4
numpy4
computer-vision3
autograd2
jax2
artificial-intelligence2
reinforcement-learning2
adc1
ros1
ros-node1
intelligent1
Programming languages (8)
Github contributions (5)
huangjuite/vrx
Feb 2020 - Mar 2020
vrx gazebo
Contributions:20 commits, 19 pushes, 1 branch in 1 month
gazebo
huangjuite/huangjuite.github.io
Jun 2020 - Mar 2025
Contributions:66 pushes, 2 branches in 4 years 9 months
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