Keren Zhu

Keren Zhu

PhD Student at The University of Texas at Austin

Publications

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