Apr. 2026
Starting in June 2026, I will join Nimble as an AI Robotics Research Intern.
News
Recent updates on papers, research, and more activities.
Mar. 2026
FINS, Efficient Construction of Implicit Surface Models From a Single Image for Motion Generation, was accepted to ICRA 2026 and is now available on arXiv.
Sep. 2025
I joined the Stanford Vision and Learning Lab (SVL) at Stanford, advised by Prof. Fei-Fei Li.
Sep. 2025
I began my M.S. in Electrical Engineering at Stanford University, focusing on robotics and computer vision.
🌟 Highlight 🌟
I am passionate about robotics and computer vision, and I have explored these areas through research, internships, and hands-on engineering projects. In the summer of 2023, I developed a vision-based dynamic obstacle avoidance system for TurtleBot4 at UC San Diego using only depth camera inputs. My internship at ITRI further deepened my interest in sim-to-real robotics, especially in building perception pipelines that remain reliable in real-world environments.
Before starting my M.S. at Stanford, I also conducted remote research in computer vision and robotics with Prof. Weiming Zhi and Dr. Tianyi Zhang at the DROP Lab, Carnegie Mellon University. My recent work spans 3D vision, robot learning, and embodied intelligence, with a focus on building systems that connect strong perception models to robust real-world robot behavior.
Education
Stanford University, CA
M.S. Student, Electrical Engineering
Concentration: Robotics / Computer Vision
- Duration: Sep. 2025 - Apr. 2027 (Expected)
National Tsing Hua University, Taiwan
Bachelor of Science in Interdisciplinary Program of Engineering
Concentration: Electrical Engineering / Power Mechanical Engineering
- Graduated with Distinction
- GPA: 4.15 / 4.30
- Duration: Sep. 2020 - Jan. 2024
Work Experience
Stanford Artificial Intelligence Laboratory (SAIL)
Graduate Researcher @ Stanford Vision and Learning Lab
Sep. 2025 - In Progress
Current work:
- Building a real-to-sim-to-real pipeline that generates controllable digital cousins to reduce the sim-to-real gap in robot learning.
- Collecting real-world data and developing a replay workflow that transfers observed behavior back into simulation for faster iteration and policy evaluation.
Industrial Technology Research Institute (ITRI)
Automotive AI Algorithm Development Intern
Sep. 2024 - Nov. 2024, Mar. 2025 - Jul. 2025
Mask2Former Semantic Segmentation
I built a custom semantic segmentation pipeline for robotics and autonomous driving by merging and re-annotating Mapillary and ADE20k, converting the data to COCO format, and training Mask2Former with NVIDIA TAO Toolkit. The final model was deployed in ROS2 and delivered real-time inference at about 15 FPS on robot and vehicle platforms.
Person Re-Identification (Re-ID)
I developed a real-time pedestrian detection and re-identification pipeline using YOLO11n, OSNet, and cosine-similarity matching. By exporting models to ONNX and TensorRT for acceleration, the system achieved about 25 FPS and was suitable for robotics and automotive deployment.
Sim2Real Quadruped Robot Terrain Traversal
I developed a sim-to-real terrain traversal pipeline for the Unitree Go2 that combined Gazebo simulation, RealSense point clouds, and elevation mapping for locomotion over uneven ground. I also integrated point-cloud processing with reinforcement learning gait policies, added VIO and forward kinematics to handle sensor interruptions, and validated the full system on the physical robot.
Foxconn
Technology Innovation Group of Chairman Office Intern
Jun. 2024 - Sep. 2024
I built an Android in-vehicle app for voice-based A/C control, making HVAC adjustment more intuitive for drivers. The end-to-end pipeline connected Azure Speech Service, Dialogflow intent parsing, and CarAPI to execute temperature control commands in the vehicle.
Featured Research
Featured Research
Efficient Construction of Implicit Surface Models From a Single Image for Motion Generation
Advised by Dr. Tianyi Zhang, Prof. Matthew Johnson-Roberson, and Prof. Weiming Zhi
We present Fast Image-to-Neural Surface (FINS), a lightweight framework capable of reconstructing high fidelity signed distance fields (SDF) from a single image in 10 seconds.
Our method fuses a multi-resolution hash grid and efficient optimization to achieve state-of-the-art accuracy while being an order of magnitude faster than existing methods.
The scalability and real-world usability of FINS were also tested through robotic surface-following experiments, showing its utility in a wide range of tasks and datasets.
Selected Projects
Additional projects spanning robotics, embedded systems, and applied computer vision.
Smart Fridge
Jun. 2024 - Sep. 2024
Google Hardware Product Sprint (HPS) Program
I developed a smart refrigerator system that combined food recognition, expiration tracking, and recipe recommendation with Google Gemini. The project focused on turning inventory awareness into actionable suggestions, helping users reduce food waste by surfacing recipes based on soon-to-expire ingredients.
Laser-Assisted Guidance Landing Technology for Drones
Jan. 2023 - Nov. 2023
[HSCC Lab], National Tsing Hua University
Advised by Prof. Jang-Ping Sheu.
I developed a laser-assisted landing system to improve drone landing accuracy in settings where GPS can drift by several meters. By combining embedded electronics, 3D-printed mechanical design, and low-power laser sensing, the system achieved 30-40 cm landing accuracy and demonstrated the feasibility of laser-based localization for future UAV platforms.
Dodging Dynamical Obstacles Using TurtleBot4 Camera Feed
Jun. 2023 - Aug. 2023
[MURO Lab], UC San Diego
Supervised by Prof. Jorge Cortés.
I built a real-time dynamic obstacle avoidance system for TurtleBot4 using ROS2 and vision-based sensing with an OAK-D Pro camera. The system combined obstacle tracking, RRT* path planning, and Bezier-curve smoothing to achieve reliable and collision-free navigation in dynamic environments using an affordable camera-first setup.
Publications
(† Corresponding author)
Efficient Construction of Implicit Surface Models From a Single Image for Motion Generation
BibTeX
@misc{chu2025fins,
title = {Efficient Construction of Implicit Surface Models From a Single Image for Motion Generation},
author = {Wei-Teng Chu and Tianyi Zhang and Matthew Johnson-Roberson and Weiming Zhi},
year = {2025},
eprint = {2509.20681},
archivePrefix = {arXiv},
primaryClass = {cs.RO},
url = {https://arxiv.org/abs/2509.20681},
}
Plain Text
W.-T. Chu, T. Zhang, M. Johnson-Roberson, and W. Zhi, "Efficient Construction of Implicit Surface Models From a Single Image for Motion Generation," arXiv preprint arXiv:2509.20681, 2025. [Online]. Available: https://doi.org/10.48550/arXiv.2509.20681
Laser-Assisted Guidance Landing Technology for Drones
BibTeX
@INPROCEEDINGS{kuo2024laserlanding,
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}
}
Plain Text
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
Dodging Dynamical Obstacles Using Turtlebot4 Camera Feed
BibTeX
@InProceedings{chu2024dynamicobstacles,
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"
}
Plain Text
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
Selected Awards
Academic Honors
- 2024 Outstanding Graduate Award of NTHU (Top 1 in the Department)
- 2024 Member of the Phi Tau Phi Scholastic Honor Society (Top 1% of Graduands in NTHU)
- 2021, 2020 Academic Achievement Award of NTHU
Research Awards
- 2024 The Excellence Award in the Undergraduate Research Competition
- 2024 The 2nd Place in Undergraduate Research Poster Interpretation Competition
- 2022 The Excellence Award in the Asia-Pacific Mechanics Contest for College Students
Scholarships
- 2023, 2019 Dr. Chu Shun-I ZyXEL Scholarship (Top 15 in the Total of 2200 Seniors)
- 2023 UC San Diego J. Yang Scholarship Award
- 2023, 2022, 2021 NTHU & IPE Outgoing Exchange Student Scholarship
- 2022 Jason International Charity Fund Scholarship Award by Acer Inc.