👋 Hello, I am Khoa Vo!

I am a Computer Science and Mathematics student at Arizona State University (ASU), passionate about Robotics, Autonomous Systems, and Artificial Intelligence. Originally from Vietnam, I am now based in Arizona, working on interdisciplinary research and hands-on projects at the intersection of machine learning, control systems, and computer vision.

🎸 Fun fact: I also play a mean guitar!

🔬 Research and Project Highlights

Computer Vision

• Developed face detection and recognition pipelines using PyTorch and TensorFlow.
• At LAB V2, fine-tuned Vision Transformer models for multi-label classification.
  • Integrated explainable rules to correct model predictions, improving accuracy by ~5%.
• During an internship in Germany, built a binary classifier for traffic accident detection in videos.
  • Achieved 0.7 F1 score and developed a protocol for collecting data in critical scenarios.

Robotics and Control

• Contributing to the Duckiebot project using:
  • Object detection, PID control
  • Implemented both simulation and real-world testing to follow traffic rules autonomously.

Reinforcement Learning

• Experimented with:
  • Imitation Learning (BC, BC-RNN)
  • Offline RL (TD3-BC, IQL)
• Applied these techniques to real-world robot lane-following tasks in the Duckiebot system.

🧠 Skills and Tools

Programming Languages: Python, C++, MATLAB, R, Java, Shell Script
Systems & Tools: Linux, ROS, Docker
ML/DL Frameworks: PyTorch, TensorFlow, Scikit-learn, Ray, OpenCV, Pandas
Deep Learning Models: ResNet, DenseNet, EfficientNet, ViTs
Object Detection: YOLOv3/v4/v5
Special Topics: Logic Tensor Networks (Neuro-symbolic AI)

📂 Selected Publications & Posters

• [C.1] Kricheli J. S., Vo K., et al.
  "Error Detection and Constraint Recovery in Hierarchical Multi-Label Classification."
  In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM), Oct. 2024.

• [C.2] Zhang Y., Vo K., et al.
  "Poster Abstract: Reproducible and Low-cost Sim-to-real Environment for Traffic Signal Control."
  In Proceedings of the 14th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), Apr. 2025.

• [C.3] Turnau J., Da L., Vo K., et al.
  "Joint-Local Grounded Action Transformation for Sim-to-Real Transfer in Multi-Agent Traffic Control."
  In RLC 2025.

🔗 Explore My Work

• Traffic Accident Projects: GitHub Repo
  
• LAB V2 Research: Meta-Cognitive Error Detection
  
• Duckiebot Autonomous Driving: Duckiebot Project

🤝 Looking Forward To...

• Connecting with researchers and builders in AI, robotics, and autonomy.
• Collaborating on applied machine learning and robotics challenges.
• Learning continuously to push the boundary between theory and practice.

📫 Get in Touch

• Email: ngocbach@asu.edu
  
• LinkedIn: Ngoc Bach Khoa Vo

Thanks for Visiting!

Acknowledgment

Credit to Joykishan Sharma for original README template inspiration.