Andrew Owens

Andrew Owens named 2025 Sloan Research Fellow

Owens will use the Sloan Research Fellowship to support his research on the development and utility of computer vision systems that learn from multisensory data.

Bridging gaps in rural health care with AI-powered mobile clinics

General practitioners with AI help could make diagnoses, run and interpret tests, and perform procedures like specialists.

Andrew Owens’ research group uses visual illusions to test the limits of diffusion models

Members of Andrew Owens's research group, Daniel Geng, Aaron Park, and Ziyang Chen, are using ambiguous image generation to understand diffusion models.

Fifteen papers by ECE researchers to be presented at the Conference on Neural Information Processing Systems

Topics of accepted ECE NeurIPS papers include diffusion models, large language models, multi-armed bandit models, and more.

Michigan AI Symposium showcases cutting-edge advances in embodied AI

The event brought together over 300 AI experts for a day of networking and discussions around this evolving field.

Andrew Owens receives NSF CAREER Award for research to improve machine perception systems

Prof. Owens’ research will help fully autonomous systems interact with their environments without human supervision.

Andrew Owens receives CoE 1938E Award

Prof. Owens brought a fresh approach to teaching the enormously popular field of computer vision, while caring deeply about the wellbeing of his students.

Michigan and ECE advancing computer vision at CVPR 2023

Look at some of the ways ECE and other University of Michigan researchers are using computer vision for real-world applications.

2022 EECS Outstanding Achievement Awards

The EECS Department has honored four faculty for their sustained excellence in instruction and curricular development, distinguished participation in service activities, or for their significant achievements in scholarly research.

ECE welcomes four new faculty for 2019

With research expertise in the areas of robotics, computer vision, control systems, and big data - these faculty are working to improve rehabilitation and autonomous systems, make systems safer, and process big data for a wide variety of applications.