Wayne (Wei-Teng) CHU
Incoming Master of Science in Electrical Engineering (MSEE) Student
Stanford University
Incoming Master of Science in Electrical Engineering (MSEE) Student
Stanford University
The term “journeyman” seems to epitomize Wayne's undergraduate life. Instead of the life within the comfort zone all the way to graduation in the homeland, he enriched last two college years with his footage across those prestigious campus worldwide. From the exchange life in Nanyang Technological University in Singapore, the summer internship in UC San Diego, to the exchange experience in UC Berkeley, these experiences made him gain a harvest and international perspective that most students cannot have.
Actively seeking research or internship opportunity which is starting from May 2025. My research interests lie at the intersection of Robotics, Computer Vision, AI, and Antonomous Driving.
Master of Science in Electrical Engineering
M.S. Program in Electrical Engineering
Bachelor of Science in Interdisciplinary Program of Engineering
Concentration: Electrical Engineering / Power Mechanical Engineering
Automotive AI Algorithm Development Intern
AMR Development Intern
Sep. 2024 - Nov. 2024, Feb. 2025 -
Retrained image segmentation models applicable to quadruped robots and autonomous vehicles. Developed a customized semantic segmentation dataset by combining ADE20k and Mapillary-Vistas, tailored to meet real-world application requirements. Tested the model's inference output on an autonomous car using the NVIDIA Omniverse platform, focusing on the Mask2Former and SparseDrive.
Technology Innovation Group of Chairman Office Intern
June 2023 - Sep. 2023
Designed an Android app that controls the car's air conditioner temperature using the driver's voice. Utilized Azure Speech Service to convert speech into text, then transformed the text into intent with Dialog Flow for natural language processing. Leveraged CarAPI to operate the air conditioning system based on voice commands.
[video]
Jan. 2023 - Nov. 2023
[HSCC Lab], National Tsing Hua University
Adviced by Jang-Ping Sheu, I developed a novel landing guidance system using laser sensors to enhance the accuracy and reliability of drone landings in challenging environments.
[report] [slides] [video] [paper]
Jun. 2023 - Aug. 2023
[MURO Lab], UC San Diego
Supervised by Jorge Cortés, I implemented real-time obstacle avoidance for mobile robots using computer vision model and ROS2, improving navigation efficiency in dynamic environments.
[report] [slides] [video] [paper]
(† Corresponding author)
MASS 2024
[pdf]
@INPROCEEDINGS{10723664,
author={Kuo, Yung-Ching and Chu, Wei-Teng and Cho, Yu-Po and Sheu, Jang-Ping},
booktitle={2024 IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS)},
title={Laser-Assisted Guidance Landing Technology for Drones},
year={2024},
pages={670-675},
doi={10.1109/MASS62177.2024.00107}}
Y. -C. Kuo, W. -T. Chu, Y. -P. Cho and J. -P. Sheu, "Laser-Assisted Guidance Landing Technology for Drones," 2024
IEEE 21st International Conference on Mobile Ad-Hoc and Smart Systems (MASS), Seoul, Korea, Republic of, 2024,
pp. 670-675, doi: 10.1109/MASS62177.2024.00107
PMAE 2023 (The Best Oral Presentation Award)
[pdf]
@InProceedings{10.1007/978-981-97-4806-8_17,
author="Chu, Wei-Teng",
editor="Mo, John P. T.",
title="Dodging Dynamical Obstacles Using Turtlebot4 Camera Feed",
booktitle="Proceedings of the 10th International Conference on Mechanical, Automotive and Materials Engineering",
year="2024",
publisher="Springer Nature Singapore",
pages="195--204",
isbn="978-981-97-4806-8"
}
Chu, WT. (2024). Dodging Dynamical Obstacles Using Turtlebot4 Camera Feed. In: Mo,
J.P.T. (eds) Proceedings of the 10th International Conference on Mechanical, Automotive
and Materials Engineering. CMAME 2023. Lecture Notes in Mechanical Engineering.
Springer, Singapore. https://doi.org/10.1007/978-981-97-4806-8_17