ECE PhD Student Yubo Du Captures 3rd Place at ACM SIGDA
Yubo Du won the 3rd place at ACM Special Interest Group on Design Automation (SIGDA) University Demonstration at the 59th IEEE/ACM Design Automation Conference (DAC), for her outstanding demonstration by using multimodality neural network model deployed on embedded GPU to do real time human sentiment analysis. She has also been selected as a DAC Young Fellow.
Embedded GPU platform for real-time human sentiment analysis developed at Dr. Zhou’s lab
DAC is a premier conference devoted to the design and design automation of electronic systems and circuits. The conference was held July 10th to July 14th, 2022, in San Francisco, California. During the conference, Dr. Peipei Zhou gave an invited talk “Practice on Performance Autotuning in AI Compute Chip” at DAC-ROAD4NN 2022: International Workshop on Research Open Automatic Design for Neural Networks 2022. Dr. Peipei Zhou also served as session chair for System-on-Chip Design Methodology “Fantastic SoCs and Where to Find Them!”.
Yubo is a PhD student in the University of Pittsburgh Department of Electrical and Computer Engineering (ECE) under supervision by Prof. Peipei Zhou. Yubo received the B.S. degree in Physics from University of Science and Technology of China in 2018 and M.S. degree in Computer Science from Vanderbilt University in 2021. She has general research interests in deep neural network algorithms and applications, energy efficiency deep learning. To learn more about her work, visit Yubo’s webpage: https://peipeizhou-eecs.github.io/author/yubo-du/.
The work was supported by funds from the US Department of Energy, Office of Science, Basic Energy Sciences under grant number DE-FG02-90ER45438. The University of Pittsburgh Center for Research Computing provided computational facilities.