Jeffrey Uhlmann
Also known as J. Uhlmann, J.K. Uhlmann, Jeff Uhlmann, Jeffrey K. Uhlmann
Jeffrey Uhlmann is a robotics researcher whose estimation work supports object tracking and SLAM. He began at the Naval Research Laboratory in 1987, earned a robotics doctorate at Oxford, and joined the University of Missouri in 2000. His research includes the Unscented Transform, Covariance Intersection, stable robotic control, and consistency methods for AI recommender systems. As of October 2026, he is an associate professor in electrical engineering and computer science at Missouri.
- Now at
- University of Missouri
- Works
- 169
- Citations
- 22,747
- h-index
- 27
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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1987
Tracking research at NRL
He begins research at the Naval Research Laboratory in 1987, working on tracking multiple objects. His education includes a robotics doctorate from Oxford, an MSc in computer science, and a BA in philosophy from Mizzou.
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1995
A nonlinear-filtering paper
In 1995, he publishes “A New Approach for Filtering Nonlinear Systems” for the American Control Conference.
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1999
Testing covariance intersection on Mars
In 1999, he coauthors “NASA Mars Rover: A Testbed for Evaluating Applications of Covariance Intersection.”
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2000
Joining the University of Missouri
He joins the University of Missouri in Fall 2000.
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2004
The Unscented Transform
In March 2004, he and Simon Julier publish “Unscented Filtering and Nonlinear Estimation” in Proceedings of the IEEE. The Unscented Transform applies nonlinear equations to sigma points to estimate a system’s transformed mean and covariance.
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2007
Covariance intersection for SLAM
In 2007, he and Simon Julier publish “Using Covariance Intersection for SLAM” in Robotics and Autonomous Systems.
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2019–2023
Robotic control and AI recommendations
In 2019, he and Bo Zhang publish “Applying a Unit-Consistent Generalized Matrix Inverse for Stable Control of Robotic Systems.” In 2023, he and Tung Nguyen describe consistency methods for AI-based SVD recommender systems, with experiments reporting improved RMSE and MAE and properties related to fairness and robustness.
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As of October 2026
Associate professor at Missouri
He is an associate professor in the David L. Payne Department of Electrical Engineering and Computer Science at the University of Missouri.
Sources and credits
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