CS Professor Jason Cong, together with his co-authors Dr. Chen Zhang (former visiting student, now at Microsoft Research Asia), Prof. Guangyu Sun (Peking University), Prof. Zhenman Fang (former postdoc, now faculty member at Simon Fraser Univ.), Peipei Zhou (current PhD student), and Peichen Pan (Falcon Computing), have received the 2019 Donald O. Pederson Best Paper Award from the IEEE Council for Design Automation (CEDA) for their paper “Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks” published in the IEEE Transactions on Computer-Aided Design (CAD) in Oct. 2018.
Donald O. Pederson Best Paper Award seeks to recognize the best paper published in the IEEE Transactions on CAD in the two calendar years preceding the award. The selection process starts with nomination of best paper candidates by the current Associate Editors of the IEEE TCAD.
Among the papers published over the preceding two years, papers receiving highest citations or highest downloads are automatically nominated for review and voting by the entire editorial board. This year the editorial board nominated five papers, and another nine papers are auto-nominated. After the voting, top five papers are reviewed by a confidential review committee before a final selection is made. The selection committee unanimously agreed to declare two papers to be co-winners. This award is recognized at the Design Automation Conference in Las Vegas on June 4, 2019.
Professor Jason Cong is a Distinguished Chancellor’s Professor of Computer Science. Dr. Cong’s research interests include energy-efficient computing, customized computing for big-data applications, electronic design automation, and highly scalable algorithms. He has over 400 publications in these areas, including 10 best paper awards, two 10-Year Most Influential Paper Awards, and the 2011 ACM/IEEE A. Richard Newton Technical Impact Award in Electric Design Automation.