I am an assistant professor in the School of Integrated Circuits at Peking University associated with the Center for Energy-efficient Computing and Applications (CECA). Previously, I worked as a postdoctoral researcher at the University of Texas at Austin from 2018 to 2019. I received the Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin in 2018 and the B.S. degree in Microelectronics from Shanghai Jiaotong University in 2013. My research interests include VLSI CAD, machine learning applications, heterogeneous computing. I am a recipient of the Best Paper Awards at DATE 2023, DATE 2022, TCAD 2021, DAC 2019, Integration, the VLSI Journal 2018, and SPIE Advanced Lithography Conference 2016.
I am always looking for motivated undergraduate and graduate students with background in computer science, microelectronics, electrical engineering, mathematics, statistics, or related areas, working on research fields of
machine learning assisted CAD;
Opening positions available: Ph.D., Post Doc, Engineer, Interns.
7/2023: We are pleased to release OpenPARF, an open-source placement and routing framework for large-scale heterogeneous FPGAs with deep learning toolkit. Please check it out!
3/2023: Our paper, SAGERoute: Synergistic Analog Routing Considering Geometric and Electrical Constraints with Manual Design Compatibility, received the Best Paper Award at DATE 2023. Please checkout the preprint and binary release. Cheers and thanks to all the co-authors!
8/2022: We are pleased to release an open-source dataset CircuitNet for machine learning tasks in EDA! You are very welcome to check it out and provide feedbacks.
6/2022: Congratulations to Zizheng Guo for winning the First Place at the 2022 ACM Student Research Competition Grand Finals (Undergraduate Category)!
10/2021: Our journal paper, DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement, received the Best Paper Award at TCAD 2021. Please checkout the preprint and source code release. Cheers and thanks to all the co-authors!
08/2021: DREAMPlace 3.0 has been released on Github. Please checkout the source code release. Cheers!
06/2020: Our co-authored paper, TEMPO: Fast Mask Topography Effect Modeling with Deep Learning, received the Best Paper Award at ISPD 2020. Please checkout the preprint. Cheers!
07/2019: Yibo co-taught the class with Prof. David Z. Pan on Machine Learning and Its Applications in IC Physical Design in the 3rd IEEE/ACM Physical Design Automation Summer School. Please checkout the slides. Thanks to the organizers!
06/2019: Our recent work, DREAMPlace: Deep Learning Toolkit-Enabled GPU Acceleration for Modern VLSI Placement, received the Best Paper Award at DAC 2019. Please checkout the preprint, slides, and source code release. Cheers and thanks to all the co-authors!
06/2018: Yibo attended PhD forum at the 55th Design Automation Conference (DAC), San Francisco, CA.
06/2018: Yibo presented his work at Lithography Workshop 2018, Sun Valley, Idaho.
04/2018: Yibo passed his PhD defense. Cheers!
03/2018: Yibo presented his work on transfer learning at ISPD 2018, Monterey, CA.
03/2018: Yibo visited Texas A&M University and presented his recent research at Computer Engineering & Systems Group (CESG). Thanks Dr. Alex Sprintson and Ms. Vickie Winston for hosting the event.
12/2017: One co-authored paper, UTPlaceF 2.0: A High-Performance Clock-Aware FPGA Placement Engine, is accepted by TODAES 2017. Cheers!
09/2017: A VLSI CAD library Limbo that contains various utilities for CAD developement is released!
05/2017: Yibo Lin starts his summer intern at Toshiba, Japan!
03/2017: Congratulations to Yibo Lin for winning the prestigious University Graduate Continuing Fellowship!