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Yu-Hsin Chen receives 2015 ADI Outstanding Student Designer Award, NVIDIA Fellowship

August 28, 2015

yuhsin_chen.jpgIt's been a banner year for Yu-Hsin Chen, a fourth-year MIT Ph.D. candidate and a member of the Energy-Efficient Multimedia Systems Group led by Prof. Vivienne Sze, In February 2015, he was given the 2015 Analog Devices Outstanding Student Designer Award. In April 2015, he also received an NVIDIA Graduate fellowship.

The Analog Devices (ADI) Outstanding Student Designer Award is presented by Analog Devices annually for excellence in analog, mixed-signal, or digital integrated circuit (IC) design, or system-level IC architectures, as well as excellence in class work, project, or thesis work and the potential for outstanding industrial contribution.

Chen was nominated for the ADI award based on his design of "a high-throughput digital IC design for the CABAC entropy decoder for the latest video coding standard (HEVC)." This work was published at the IEEE International Conference on Image Processing (ICIP) in 2014 and IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) in 2015.

"We started the Outstanding Student Designer Award program in 1997 as a way to connect with students at key university programs and help bring awareness to the importance of the discipline of IC design, which fewer students are choosing to study," said Katsu Nakamura, ADI Fellow. "As an industry leader in this area, ADI has a responsibility to take on a leadership role in promoting and endorsing research activities in IC design."

Chen was also among five finalists selected for the NVIDIA Graduate Fellowship Program. This program demonstrates the company's commitment to academia in supporting research spanning areas of computing innovation. Recipients are selected based on their academic achievements, professor nomination, and area of research. The next year of his graduate studies will be supported by the NVIDIA graduate fellowship.

Chen's research in Prof. Vivienne Sze's lab at MIT focuses on the implementation of energy-efficient computer vision frameworks to meet the demand of modern mobile platforms. GPU is playing an important role as it greatly accelerates the processing of a large amount of image and video data. He is also looking into improving current GPU architectures with emphasis on providing machine learning capabilities in future multimedia systems. His research interests include VLSI design, energy-efficient system, computer vision and computer architecture. He holds a B.S. in electrical engineering from National Taiwan University, Taipei, Taiwan, and an M.S. in electrical engineering and computer science from MIT.

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