Oral Presentations

• To be Updated ……

• Efficient Digital Design and Implementation with Machine Learning in EDA
  • ACCESS-CEDA Seminar Series, 2022
• DEEP: Developing Extremely Efficient Runtime On-Chip Power Meters slides poster
  • In International Conference on Computer Aided Design (ICCAD), 2022. (Pre-Recorded)
• Exploring Design Solutions through AI-assisted Prediction and Parameter Tuning
  • ACCESS Technology Symposium on Frontiers of AI Accelerators, 2022.
  • Departmental Seminar, 2022.
• APOLLO: An Automated Power Modeling Framework for Runtime Power Introspection in High-Volume Commercial Microprocessors. slides
  • Invited talk at “The best of EDA research” ACM/IEEE Design Automation WebiNar (DAWN), 2022.
  • Invited talk at Oak Ridge National Lab (ORNL), 2021.
  • Invited talk at Biren Technology, 2021.
  • In International Symposium on Microarchitecture (MICRO), 2021.
• Intelligent Circuit Design and Implementation with Machine Learning. slides
  • PhD Dissertation Defense at Duke University, 2022.
• Truly Intelligent Circuit Design and Implementation. slides
  • Invited talk at AMD, 2021.
  • Seminar at Hong Kong University of Science and Technology, 2021.
  • Invited talk at Alibaba, 2021.
  • Seminar at City University of Hong Kong, 2021.
• Intelligent Circuit Design and Implementation with Machine Learning in EDA. slides
  • ACM Student Research Competition at ICCAD, 2021.
• A Collaborative Machine Learning Approach to Fast and High-Fidelity Design Prediction. (Co-presenter) slides
  • In SRC CADT Annual Review Presentation, 2021.
• Net$^2$: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation. slides
  • In Asia and South Pacific Design Automation Conference (ASPDAC), 2021.
• Automatic Routability Predictor Development Using Neural Architecture Search. slides
  • In NSF IUCRC ASIC Center Annual Meeting, 2021.
• Fast IR Drop Estimation with Machine Learning. slides
  • In International Conference on Computer Aided Design (ICCAD), 2020.
• PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network. slides
  • In Asia and South Pacific Design Automation Conference (ASPDAC), 2020.
  • In Workshop on Machine Learning for CAD (MLCAD), 2019.
• FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning. slides
  • In Semiconductor Research Corporation (SRC) TECHCON, 2020.
  • In Asia and South Pacific Design Automation Conference (ASPDAC), 2020.
  • In Workshop on Machine Learning for CAD (MLCAD), 2019.
• A Collaborative Machine Learning Approach to Fast and High-Fidelity Design Prediction. (Co-presenter) slides
  • In Texas Analog Center of Excellence (TxACE) Symposium, 2019.
• Deep Learning and GPU Acceleration for VLSI Physical Design. (Co-presenter) slides
  • In Nvidia GPU Technology Conference (GTC), 2018.
• RouteNet: Routability Prediction for Mixed-Size Designs Using Convolutional Neural Network. slides
  • In International Conference on Computer Aided Design (ICCAD), 2018.

Poster

• Intelligent Circuit Design and Implementation with Machine Learning in Design Automation. poster
  • In Design, Automation and Test in Europe Conference (DATE) Ph.D. forum, 2022.
  • In ACM SIGDA Student Research Forum at ASP-DAC, 2022. (Best Research Poster Award)
  • In Design Automation Conference (DAC) Ph.D. forum, 2021.
• Machine Learning for High-Fidelity Design Prediction and Automatic Tuning. poster
  • In SRC CADT Annual Review Poster Session, 2019.