t DAC 2023, Prof. Yngyan (Celine) Lin, along with her students, organized the tutorial titled “AutoDL: Automated Tools for Fast Development of Deep Learning Networks and Accelerators”, which included keynotes and invited talks from both industry and academic researchers, attracting over 200 attendees.
The EIC team, led by Prof. Yingyan (Celine) Lin and her students Yonggan Fu and Yongan Zhang, both of whom are currently supported by the CoCoSys center funding, won second place in the 33rd ACM SIGDA/IEEE CEDA University Demonstration at DAC’23 in July 2023.
Ph.D. students Haoran You and Yonggan Fu, currently supported by the CoCoSys center funding under the guidance of Professor Yingyan (Celine) Lin, presented their work, Castling-ViT and Auto-CARD, respectively, at CVPR 2023 in Vancouver, Canada, in June 2023. Furthermore, they shared their insights into the evolving field of computer vision, which was covered by Georgia […]
At DAC 2023, Prof. Yngyan (Celine) Lin, along with her students, organized the tutorial titled “AutoDL: Automated Tools for Fast Development of Deep Learning Networks and Accelerators”, which included keynotes and invited talks from both industry and academic researchers, attracting over 200 attendees.
PI Kaushik Roy spoke to ML@Purdue about the world of brain-like architectures, touching on SNNs, ANNs, and hybrid networks and delved into the importance of specialized hardware.
The EyeCoD work recently developed by PI Yingyan (Celine) Lin’s group at Georgia Tech was selected for the IEEE Micro Top Picks of 2023 in January 2023, which is a recognition of “the most significant research papers in computer architecture based on novelty and potential for long-term impact, published in the top computer architecture conferences […]
PI Tushar Krishna (GT), his Ph.D. student Raveesh Garg, and research collaborators from University of Murcia co-organized a tutorial on simulating sparse DNNs and GNNs on March 26 at ASPLOS 2023 on March 26, 2023, in Vancouver. He was also a co-author on two research papers presented at ASPLOS on accelerating sparse DNNs and Transformer […]
PI Michael Carbin (MIT) was invited to serve as Program Co-Chair MLSys23, the Sixth Conference on Machine Learning and Systems. The conference targets research at the intersection of machine learning and systems. The conference aims to elicit new connections amongst these fields, including identifying best practices and design principles for learning systems, as well as […]
Jonathan Frankle, supervised by PI Michael Carbin (MIT), graduated from MIT EECS with a PhD. The subject of his dissertation was his notable work on the Lottery Ticket Hypothesis, which received a Best Paper Award from ICLR in 2019. The work was the first to show that within large neural networks, there exist subnetworks that […]
At DAC 2023, Yu (Kevin) Cao organized the first Workshop on Chiplet-based Heterogeneous Integration and CO-design (CHICO), including 12 invited talks by academic and industry leaders.