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Jia Deng selected as recipient of PAMI Mark Everingham Prize

Prof. Deng and his collaborators received the award for their work on ImageNet.| Short Read
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IMAGE:  Prof. Jia Deng

Prof. Jia Deng has won the PAMI Everingham Prize for his work in developing ImageNet, a large-scale labeled image database that has powered many recent advances in computer vision.

This Prize is to commemorate Mark Everingham and to encourage others to follow in his footsteps by acting to further progress in the computer vision community as a whole. It is given to a researcher, or a team of researchers, who have made a selfless contribution of significant benefit to other members of the computer vision community. The award is given out by the IEEE Technical Committee on Pattern Analysis and Machine Intelligence (PAMI), and was presented at the ECCV Conference this year.

Prof. Deng and his collaborators received the award for their work on ImageNet, “for a series of datasets and challenges since 2010 that have had such impact on the computer vision field. ImageNet built on the Caltech101/256 datasets, increasing the number of images by orders of magnitude and enabling the development of new algorithms.”

Prof. Deng’s research focus is on computer vision and machine learning, in particular, achieving human-level visual understanding by integrating perception, cognition, and learning. He received his Ph.D. from Princeton University and his B.Eng. from Tsinghua University, both in computer science. He is a recipient of the Yahoo ACE Award, a Google Faculty Research Award, the ICCV Marr Prize, and the ECCV Best Paper Award. He directs the Michigan Vision & Learning Lab.

Jia Deng
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The electrons absorb laser light and set up “momentum combs” (the hills) spanning the energy valleys within the material (the red line). When the electrons have an energy allowed by the quantum mechanical structure of the material—and also touch the edge of the valley—they emit light. This is why some teeth of the combs are bright and some are dark. By measuring the emitted light and precisely locating its source, the research mapped out the energy valleys in a 2D crystal of tungsten diselenide. Credit: Markus Borsch, Quantum Science Theory Lab, University of Michigan.

Mapping quantum structures with light to unlock their capabilities

Rather than installing new “2D” semiconductors in devices to see what they can do, this new method puts them through their paces with lasers and light detectors. | Medium Read