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Krittin Chaowakarn

k.chaowakarn [at] gmail [dot] com

Krittin Chaowakarn completed a bachelor's degree in Electrical Engineering at Sirindhorn International Institute of Technology , Thammasat University . His research experience includes multi-object detection for autonomous vehicles and real-time object detection for small-scale autonomous driving simulations. He is currently preparing to pursue graduate studies in computer science, with a research focus on visual learning for robotics.

If you are interested in his work or future research directions, please do not hesitate to contact him.

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Research

Real-Time Object Detection for Autonomous Driving: An Empirical Study in a Small-Scale Urban Environment

Krittin Chaowakarn, Michael Meidinger (PhD advisor), Andreas Herkersdorf (supervisor)
Bachelor's Thesis (TUM), 2025

Thesis (Full) / Thesis / Slides (PDF) / Slides (PowerPoint)

A comprehensive study on object detection using Duckietown and YOLO, covering latency, throughput, and hardware utilization across YOLO versions 8–12 on NVIDIA Jetson Nano 4GB.

Senior project illustration

Autonomous Human Following Robot System for Multi-Perspective Visualization

Tongroth Thorng, Krittin Chaowakarn, Ned Sureechainirun, Itthisek Nilkhamhang (advisor)
Senior Project (SIIT), 2025

Contributed to multi-robot formation research using Yahboom robots and ROS 2, simulating in Gazebo, and deployed a vision-based target tracking system integrating YOLO (detection), DeepSORT (tracking), and face recognition for human-following robots.

NV3D original preview NV3D filtered preview

NV3D: Leveraging Spatial Shape Through Normal Vector-based 3D Object Detection

Krittin Chaowakarn, Paramin Sangwongngam, Nang Htet Htet Aung, Chalie Charoenlarpnopparut
arXiv, 2025

arXiv / Code

Redundant LiDAR point clouds can be removed up to 55% through normal vector density-based and FOV-aware bin-based sampling.

Presented at a bilateral meeting between the National Institute of Information and Communications Technology and the National Electronics and Computer Technology Center as part of a smart city research collaboration between Thailand and Japan.

Teaching and Academic Service

Over the past 2.5 years, he has served in five grading roles and as a laboratory teaching assistant. He is currently serving as a teaching assistant for three additional courses this semester (January–May 2026)*, as well as a grader for a master's-level course.

  • Control Systems Laboratory (Jan–May 2026)*
  • Electronics and Microelectronics Laboratories (Jan–May 2026)*
  • Electrical Engineering Crafting Skill (Jan–May 2026)*
  • Digital Circuits Laboratory (Aug–Dec 2024)
  • Computational Mathematics: Probability — Master's Level (Mar 2026–Present)*
  • Electromagnetics (Jan–May 2024, Jan–May 2025)
  • Linear Algebra and Optimization Methods (Aug–Dec 2024)
  • Computational Tools in Electrical Engineering (Aug–Dec 2023)
  • Basic Electrical Engineering (Jan–May 2023)

Honors and Awards

  • Young Scientist and Technologist Program: Fully funded undergraduate study at SIIT (acceptance rate ≈ 0.25%)
  • Top 100 Team–KPIT Sparkle 2024: Ranked among top 100 teams (~0.45%) worldwide in KPIT Sparkle 2024, a global student innovation contest focused on vehicle technologies
  • Keio University International Workshop 2023: Selected as one of 12 institute representatives to attend a workshop at Keio University