Research by Jingtong Hu Earns IEEE TCAD Best Paper Award
A paper from senior author Jingtong Hu, associate professor of electrical and computer engineering at the University of Pittsburgh, has been selected by the IEEE Transactions on Computer-Aided Design for the 2021 Donald O. Pederson Best Paper Award. The paper, “Hardware/Software Co-Exploration of Neural Architectures,” (DOI: 10.1109/TCAD.2020.2986127) proposes a novel hardware and software framework for efficient neural architecture search (NAS), a technique to automate machine learning.
The IEEE TCAD Editorial Board and the IEEE Council on Electronic Design Automation selected the paper as one of two 2021 winners based on the overall quality, originality, level of contribution, subject matter, and timeliness of the research. The award will be presented at the 2021 Design Automation Conference in December.
“Machine learning is increasingly featured and invaluable across a broad range of engineering and science applications, and novel circuits and systems for machine learning are critically important” said Alan George, chair of the Department of Electrical and Computer Engineering.” Jingtong’s work in this area is outstanding, and I’m excited to see it getting the recognition that it deserves.”