Youngjin Kim, Ph.D

Postdoctoral Researcher | Control Theory | Robotics | Dynamic Systems | Autonomous Systems

🎓 Education

Doctor of Philosophy (Ph.D.)

University at Buffalo 2024
  • Major: Mechanical Engineering
  • Thesis: Advanced Motion Planning Strategies for Wheeled Mobile Robots: Performance, Efficiency, and Safety
  • Nominated for Dean’s Achievement Award

Master of Science (M.S.)

University at Buffalo 2020
  • Major : Mechanical Engineering
  • Thesis : Optimal Control of a Differential-Drive Mobile Robot
  • Award : 3rd Place Winner (Department Research Competition)
  • Nominated for Northeastern Association of Graduate Schools (NAGS) Best Master’s Thesis Award

Bachelor of Science (B.S.)

University at Buffalo 2018
  • Major : Mechanical Engineering
  • Award : Magna Cum Laude, Dean’s List (5 consecutive semesters)

🛠️ Work Experience

Postdoctoral Researcher

DRONES Laboratory : University at Buffalo 2024–2025
  • Designed a robust and provably safe motion planning system for a quadruped robot, enabling reliable navigation in off-road and rugged environments by combining model-based control with reinforcement learning
  • Developed an autonomous culvert inspection system using a legged robot equipped with active low-light illumination control; successfully field-tested along the Erie Canal, NY (Spotlight presentation at ICRA 2025!)
  • Supervised a team of 10+ students to deliver full-stack autonomy for an excavator in collaboration with Moog, Inc., targeting next-generation construction vehicle applications. Results presented at the ICRA 2025 Workshop on Field Robotics

Research Assistant

CoDE Laboratory : University at Buffalo 2018–2024
  • Developed exact solutions for motion planning using nonlinear root-finding—more reliable than standard numerical method
  • Designed a feedback controller with Lyapunov theory to improve tracking and stability, verified in both sim and real-world
  • Integrated safety and energy efficiency using control barrier functions and re-planning strategies
  • Designed model-based controller for car-like robots and participated in the 2023 IROS Autonomous Racing Grand Prix

Intern

Volvo Construction Equipment 2023
  • Used signal processing and frequency analysis to design control algorithms that reduce noise and vibration in asphalt compactors (Patent submitted)
  • Created an intuitive GUI for interacting with electric vehicle battery systems, streamlining operations
  • Built and tested a full-scale electric asphalt compactor prototype, including hardware-in-the-loop validation
  • Supported new interns with onboarding and project orientation to ensure a smooth transition