Jeffrey K. Johnson is a PhD Candidate in Computer Science at Indiana University (IU) and a member of the Intelligent Motion Laboratory (IML). He joined the PhD program at IU in 2009 after several years working professionally as a software developer. As a member of the IML, his work revolves generally around perception and planning under uncertainty, including coordinated motion planning for multi-manipulator articulated robots, and, particularly, trajectory planning for automobiles.

His primary research topics include optimization, adaptive control and planning for robotic systems, machine learning, aspects of computational geometry, and algorithm analysis. In particular, he has worked with colleagues at the IML on projects including online surface classification from 3D sensor data, perception-based motion model calibration for underactuated manipulators, semi-autonomous collision avoidance systems for automobiles, and optimal fixed-path velocity planning for mobile agents.

In 2012, he worked at TRACLabs, Inc. to assist in the development of a motion planning toolkit for mobile dual-armed manipulators as part of a NASA SBIR. In 2013, he worked with the autonomous driving team at Bosch RTC to develop advanced real-time collision detection for use in autonomous road vehicles. In 2014, he joined Bosch RTC as a research engineer focusing on trajectory planning for autonomous road vehicles.

He has been a reviewer for Computing Reviews since 2013.