Research Topics

Topic 1: Deep Neural Network Design Automation

In this project we will explore 1) DNN compression / acceleration and 2) DNN design space exploration.


Selected recent publications:

  • Yuzhe Ma, Ran Chen, Wei Li, Fanghua Shan, Wenjian Yu, Minsik Cho, Bei Yu, “A Unified Approximation Framework for Deep Neural Networks”. (arXiv)

Topic 2: Deep Mask Learning


Selected recent publications:

  • [C57] Hang Zhang, Fengyuan Zhu, Haocheng Li, Evangeline F. Y. Young, Bei Yu, “Bilinear Lithography Hotspot Detection”, ACM International Symposium on Physical Design (ISPD), pp. 7–14, Portland, OR, Mar. 19–22, 2017. (paper) (Best Paper Award)

Topic 3: Learning on Chips

Machine learning is a powerful computer science technique which can derive knowledge from big data, and provides prediction and matching. Since nanometer VLSI CAD problems have extremely high complexity and gigantic data, there has been a surge recently in applying and adapting machine learning techniques in VLSI CAD.


Selected recent publications:

  • [C85] Yuzhe Ma, Haoxing Ren, Brucek Khailany, Harbinder Sikka, Lijuan Luo, Karthikeyan Natarajan, Bei Yu, “High Performance Graph Convolutional Networks with Applications in Testability Analysis”, ACM/IEEE Design Automation Conference (DAC), Las Vegas, NV, June 2–6, 2019.

  • [J] Yuzhe Ma, Subhendu Roy, Jin Miao, Jiamin Chen, Bei Yu, “Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach”, accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD). (arXiv)

Topic 4: Hardware Friendly Computer Vision

Coming soon…

Topic 5: Combinatorial Algorithms in VLSI CAD

Many classical VLSI CAD problems can be extracted and formulated into challenging combinatorial optimization problems. We are heavily working to improve the state-of-the-art.


Selected recent publications are listed as follows:

Topic 6: Emerging Challenges

Cyber-physical system (CPS) addresses the close interactions and feedback loop between the cyber components such as sensing systems and the physical components such as varying environment and energy systems. Currently we are working on data regression and calibration in smart building environment. On ther other hand, we are also working on improving the security for hardware systems.

emerging topics 

Selected recent publications: