Kooktae Lee

Dr. Kooktae Lee is recruiting a highly motivated PhD student to join the Department of Mechanical Engineering at Texas Tech University starting in Fall 2026 . The position is supported by NSF funding . The research group (ICON Lab: Innovative Control Of Networked multi-agent systems Laboratory) works on multi-robot systems , multi-agent systems , formation control , distributed optimization , networked control systems , and AI-driven robotics . Application areas include infrastructure inspection, smart farming, environmental monitoring (wildlife/wildfire), search and rescue, and planetary exploration. Preferred background includes a strong foundation in control theory and mathematics, plus practical experience with MATLAB , Python , ROS/Gazebo , and/or Isaac Sim . Experience with robot hardware such as UAVs or mobile robots is a plus. Eligibility is limited to U.S. domestic students or international students currently in the U.S. who are eligible for a SEVIS transfer . Interested applicants should email their CV and academic transcripts directly to Dr. Lee. For more information, the post links to the ICON Lab website and a LinkedIn research page.

One PhD position is available in autonomous multi-robot systems at Texas Tech University in Spring 2027 . The position is in Dr. Kooktae Lee’s research group and is supported by NSF funding . The project focuses on bridging rigorous control algorithms with practical robotic systems. Research topics include multi-robot coordination , swarm intelligence , autonomous UAV and mobile robot systems , density-driven optimal control (D²OC) , AI-enabled decision-making and control , and real-world robotic experiments for applications such as infrastructure inspection, smart farming, environmental monitoring, search and rescue, and planetary exploration. Preferred preparation includes experience with ROS2 , robotic software development, NVIDIA Isaac Sim , Gazebo , autonomous navigation, sensor integration, perception/control pipelines, and programming in Python and/or C++ . Hardware experience with UAVs, mobile robots, LiDAR, cameras, embedded systems, or field robotics is highly valued. A background in robotics, control systems, optimization, or autonomous systems is desirable, and MATLAB is a plus. Interested applicants should email their CV and academic transcripts directly to [email protected] . Students already studying in the U.S. who are eligible for SEVIS transfer are especially encouraged to apply.