PhD in Computer Engineering
Duke University, 2022
Data-Pattern-Based Predictive On-Chip Power Meter in DNN Accelerator
Article
Towards Fully Automated Machine Learning for Routability Estimator Development
Article
Transferable Pre-Synthesis PPA Estimation for RTL Designs With Data Augmentation Techniques
Article
APPLE: An Explainer of ML Predictions on Circuit Layout at the Circuit-Element Level
Conference paper
RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model
Conference paper
Unleashing Flexibility of ML-based Power Estimators Through Efficient Development Strategies
Conference paper
The Dark Side: Security and Reliability Concerns in Machine Learning for EDA
Article
Book chapter
Net-Based Machine Learning-Aided Approaches for Timing and Crosstalk Estimation
Book chapter
Efficient Runtime Power Modeling with On-Chip Power Meters
Conference paper
FADO: Floorplan-Aware Directive Optimization for High-Level Synthesis Designs on Multi-Die FPGAs
Conference paper
Fully Automated Machine Learning Model Development for Analog Placement Quality Prediction
Conference paper
MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design
Conference paper
PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions
Conference paper
PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search
Conference paper
PROPHET: Predictive On-Chip Power Meter in Hardware Accelerator for DNN
Conference paper
Rethink before Releasing Your Model: ML Model Extraction Attack in EDA
Conference paper
Security and Reliability Challenges in Machine Learning for EDA: Latest Advances
Conference paper
Pre-Placement Net Length and Timing Estimation by Customized Graph Neural Network
Article
DEEP: Developing Extremely Efficient Runtime On-Chip Power Meters
Conference paper
Robustify ML-based Lithography Hotspot Detectors
Conference paper
Towards Collaborative Intelligence: Routability Estimation based on Decentralized Private Data
Conference paper
Conference paper
Automatic Routability Predictor Development Using Neural Architecture Search
Conference paper
Net2: A Graph Attention Network Method Customized for Pre-Placement Net Length Estimation
Conference paper
Fast IR Drop Estimation with Machine Learning : Invited Paper
Conference paper
FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning
Conference paper
PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network
Conference paper
Routing-Free Crosstalk Prediction
Conference paper
Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model
Conference paper
RouteNet: Routability prediction for mixed-size designs using convolutional neural network
Conference paper
FADO: Floorplan-Aware Directive Optimization for High-Level Synthesis Designs on Multi-Die FPGAs
Fully Automated Machine Learning Model Development for Analog Placement Quality Prediction
MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design
PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions
PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search
PROPHET: Predictive On-Chip Power Meter in Hardware Accelerator for DNN
Rethink before Releasing Your Model: ML Model Extraction Attack in EDA
Security and Reliability Challenges in Machine Learning for EDA: Latest Advances
Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model
RouteNet: Routability prediction for mixed-size designs using convolutional neural network
Conference paper
ELEC2350 | Introduction to Computer Organization and Design |
ELEC3910 | Academic and Professional Development II |
ELEC4900 | Final Year Design Project |
ELEC6910D | Electronic Design Automation for VLSI Design |
ELEC2350 | Introduction to Computer Organization and Design |
ELEC3910 | Academic and Professional Development II |
No Teaching Assignments |
No Teaching Assignments |
No Teaching Assignments |
FANG, Wenji
Electronic and Computer Engineering
LI, Mengming
Electronic and Computer Engineering
LI, Wenkai
Electronic and Computer Engineering
MOK, Jay Zhe-an
Electronic and Computer Engineering
TSARAS, Dimitrios
(co-supervision)
Computer Science and Engineering
WANG, Jing
Electronic and Computer Engineering
LIU, Shang
Electronic and Computer Engineering
LU, Yao
Electronic and Computer Engineering
ZHANG, Qijun
Electronic and Computer Engineering
ZHU, Yugao
Electronic and Computer Engineering
HO, Kai Suet
Electronic and Computer Engineering
ZHANG, Tao
Electronic and Computer Engineering( Completed in 2024 )
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