Incoming Master of Science in Electrical Engineering (MSEE) Student
Stanford University
waynechu@stanford.edu
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.
Currently, Wayne is remotely conducting research in computer vision and robotics under the supervision of Dr. William Zhi and Dr. Tianyi Zhang at the DROP Lab, Carnegie Mellon University.
M.S. Candidate, Electrical Engineering
Bachelor of Science in Interdisciplinary Program of Engineering
Concentration: Electrical Engineering / Power Mechanical Engineering
Automotive AI Algorithm Development Intern
Sep. 2024 - Nov. 2024, Feb. 2025 -
Combined and re-annotated Mapillary and ADE20k datasets to fulfill requirements for quadruped robots and autonomous vehicles. Converted to COCO format and trained a custom Mask2Former model using NVIDIA TAO Toolkit. Integrated into ROS2 for real-time video inference on robotic and vehicle platforms.
Built a real-time pedestrian detection and re-ID pipeline using YOLOv11n and OSNet. Employed cosine similarity for feature matching and exported models in .onnx and .engine formats. Achieved real-time inference at ~25 FPS for surveillance, robotics, and automotive use cases.
Technology Innovation Group of Chairman Office Intern
June 2024 - Sep. 2024
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