You can also find my articles on my Google Scholar profile.

Journal Papers

J2. Challenges and Opportunities Toward Fully Automated Analog Layout Design

J1. MAGICAL: An Open-Source Fully Automated Analog IC Layout System from Netlist to GDSII

Conference Papers

C17. Automating Analog Constraint Extraction: From Heuristics to Learning

C16. Reinforcement Learning for Electronic Design Automation: Case Studies and Perspectives

C15. Generative-Adversarial-Network-Guided Well-Aware Placement for Analog Circuits

C14. OpenSAR: An OpenSource Automated End-to-end SARADC Compiler

C13. Universal Symmetry Constraint Extraction for Analog and Mixed-Signal Circuits with Graph Neural Networks

C12. Optimizer Fusion: Efficient Training with Better Locality and Parallelism

C11. An In-Memory-Computing Charge-Domain Ternary CNN Classifier

C10. MAGICAL 1.0: An Open-Source Fully-Automated AMS Layout Synthesis Framework Verified With a 40-nm 1GS/s Δ∑ ADC

C9. Exploring Logic Optimizations with Reinforcement Learning and Graph Convolutional Network

C8. Toward Silicon-Proven Detailed Routing for Analog and Mixed-Signal Circuits

C7. Effective Analog/Mixed-Signal Circuit Placement Considering System Signal Flow

C6. An Efficient Training Framework for Reversible Neural Architectures

C5. Closing the Design Loop: Bayesian Optimization Assisted Hierarchical Analog Layout Synthesis

C4. Towards Decrypting the Art of Analog Layout: Placement Quality Prediction via Transfer Learning

C3. S3DET: Detecting System Symmetry Constraints for Analog Circuits with Graph Similarity

C2. MAGICAL: Toward Fully Automated Analog IC Layout Leveraging Human and Machine Intelligence

C1. GeniusRoute: A New Routing Paradigm Using Generative Neural Network Guidance for Analog Circuits