Michigan Engineering | University of Michigan Transparent optical sensor arrays combine with a specialized neural network in new University of Michigan prototype
3D motion tracking system could streamline vision for autonomous tech
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Prof. Pei Zhang solemnly swears that he’s up to some good
In a project he calls the “Marauder’s Map,” Prof. Zhang uses machine learning-based data models, physics models, and heuristic models to turn physical structures into sensing devices.
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Artificial photosynthesis devices that improve themselves with use
“Our discovery is a real game-changer. I’ve never seen such stability.”
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U-Michigan, Ford open world-class robotics complex
The facility will accelerate the future of advanced and more equitable robotics and mobility
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A MiTEE student and her quest to shape the future of space satellites
Maya Pandya, an Electrical Engineering senior, is a key member of the student team working to design a new generation of CubeSats that may revolutionize how we monitor space environments and provide a new method for interplanetary communication.
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$6.25 million to develop new semiconductors for artificial photosynthesis
An interdisciplinary team from four universities are developing a new class of semiconductors for novel artificial photosynthesis and the production of clean chemicals and fuels using sunlight, as part of a DoD MURI
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Research to advance low-power speech recognition highlighted by Intel
Michael Flynn and his group are applying their groundbreaking work in beamforming to the challenge of low-power on-chip speech recognition.
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“Egg carton” quantum dot array could lead to ultralow power devices
By putting a twist on new “2D” semiconductors, researchers have demonstrated their potential for using single photons to transmit information.
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Fairer AI for long-term equity
Prof. Mingyan Liu is a key member of a project to mitigate bias in Artificial Intelligence and Machine Learning systems for long-term equitable outcomes.
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First IFIP Workshop on Intelligent Vehicle Dependability and Security
The workshop, co-organized by a team including two EECS faculty, focused on ensuring the safety of Level 3 autonomous vehicles, where humans must be ready to take over control.