VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis. - Hadi Esmaeilzadeh; Soroush Ghodrati; Jie Gu 003; Shiyu Guo; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Rohan Mahapatra; Susmita Dey Manasi; Edwin Mascarenhas; Sachin S. Sapatnekar; Ravi Varadarajan; et al. (ICCAD, 2021)

SpecPart: A Supervised Spectral Framework for Hypergraph Partitioning Solution Improvement. - Ismail Bustany; Andrew B. Kahng; Ioannis Koutis; Bodhisatta Pramanik; Zhiang Wang (ICCAD, 2022)

IEEE CEDA DATC: Expanding Research Foundations for IC Physical Design and ML-Enabled EDA. - Jinwook Jung; Andrew B. Kahng; Ravi Varadarajan; Zhiang Wang (ICCAD, 2022)

RTL-MP: Toward Practical, Human-Quality Chip Planning and Macro Placement. - Andrew B. Kahng; Ravi Varadarajan; Zhiang Wang (ISPD, 2022)

Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (MLCAD, 2022)

An Open-Source Constraints-Driven General Partitioning Multi-Tool for VLSI Physical Design. - Ismail Bustany; Grigor Gasparyan; Andrew B. Kahng; Ioannis Koutis; Bodhisatta Pramanik; Zhiang Wang (ICCAD, 2023)

Invited Paper: IEEE CEDA DATC Emerging Foundations in IC Physical Design and MLCAD Research. - Jinwook Jung; Andrew B. Kahng; Sayak Kundu; Zhiang Wang; Dooseok Yoon (ICCAD, 2023)

Assessment of Reinforcement Learning for Macro Placement. - Chung-Kuan Cheng; Andrew B. Kahng; Sayak Kundu; Yucheng Wang; Zhiang Wang (ISPD, 2023)

K-SpecPart: A Supervised Spectral Framework for Multi-Way Hypergraph Partitioning Solution Improvement. - Ismail Bustany; Andrew B. Kahng; Ioannis Koutis; Bodhisatta Pramanik; Zhiang Wang (CoRR, 2023)

Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Sean Kinzer; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang (CoRR, 2023)

SPV-SSD: An Anchor-Free 3D Single-Stage Detector with Supervised-PointRendering and Visibility Representation. - Lingmei Yin; Wei Tian 001; Ling Wang; Zhiang Wang; Zhuoping Yu (Remote. Sens., 2023)

Strengthening the Foundations for IC Physical Design and ML EDA Research. - Vidya A. Chhabria; Vikram Gopalakrishnan; Andrew B. Kahng; Sayak Kundu; Zhiang Wang; Bing-Yue Wu; Dooseok Yoon (ICCAD, 2024)

Physically Aware Synthesis Revisited: Guiding Technology Mapping with Primitive Logic Gate Placement. - Hongyang Pan; Cunqing Lan; Yiting Liu; Zhiang Wang; Li Shang; Xuan Zeng 001; Fan Yang 001; Keren Zhu 001 (ICCAD, 2024)

An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Joon Kyung Kim; Sean Kinzer; Sayak Kundu; Rohan Mahapatra; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang; Ziqing Zeng (ACM Trans. Design Autom. Electr. Syst., 2024)

Physical Design Methods and Research Infrastructure for Machine Learning Accelerators - Zhiang Wang (2024)

K-SpecPart: Supervised Embedding Algorithms and Cut Overlay for Improved Hypergraph Partitioning. - Ismail Bustany; Andrew B. Kahng; Ioannis Koutis; Bodhisatta Pramanik; Zhiang Wang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Hier-RTLMP: A Hierarchical Automatic Macro Placer for Large-Scale Complex IP Blocks. - Andrew B. Kahng; Ravi Varadarajan; Zhiang Wang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Use Cases and Deployment of ML in IC Physical Design. - Amur Ghose; Andrew B. Kahng; Sayak Kundu; Yiting Liu; Bodhisatta Pramanik; Zhiang Wang; Dooseok Yoon (ASP-DAC, 2025)

Performance Analysis of CNN Inference/Training with Convolution and Non-Convolution Operations on ASIC Accelerators. - Hadi Esmaeilzadeh; Soroush Ghodrati; Andrew B. Kahng; Sean Kinzer; Susmita Dey Manasi; Sachin S. Sapatnekar; Zhiang Wang (ACM Trans. Design Autom. Electr. Syst., 2025)

DG-RePlAce: A Dataflow-Driven GPU-Accelerated Analytical Global Placement Framework for Machine Learning Accelerators. - Andrew B. Kahng; Zhiang Wang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

ORFS-agent: Tool-Using Agents for Chip Design Optimization. - Amur Ghose; Andrew B. Kahng; Sayak Kundu; Zhiang Wang (CoRR, 2025)

Recursive Learning-Based Virtual Buffering for Analytical Global Placement. - Andrew B. Kahng; Yiting Liu; Zhiang Wang (CoRR, 2025)

ChipletPart: Scalable Cost-Aware Partitioning for 2.5D Systems. - Alexander Graening; Puneet Gupta 001; Andrew B. Kahng; Bodhisatta Pramanik; Zhiang Wang (CoRR, 2025)