Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
portfolio
publications
Exploring Target Function Approximation for Stochastic Circuit Minimization
Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2020
Chen Wang, Weihua Xiao, John P. Hayes, and Weikang Qian.
GOMIL: Global Optimization of Multiplier by Integer Linear Programming
Published in Design, Automation and Test in Europe Conference (DATE), 2021
Weihua Xiao, Weikang Qian, and Weiqiang Liu.
Quantified Satisfiability-based Simultaneous Selection of Multiple Local Approximate Changes
Published in IEEE International Symposium on Circuits and Systems (ISCAS), 2022
Chenfei Lou, Weihua Xiao, and Weikang Qian.
OPACT: Optimization of Approximate Compressor Tree for Approximate Multiplier
Published in Design, Automation and Test in Europe Conference (DATE), 2022
Weihua Xiao, Cheng Zhuo, and Weikang Qian.
ASPPLN: Accelerated Symbolic Probability Propagation in Logic Network
Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2022
Weihua Xiao and Weikang Qian.
A Survey on Approximate Multiplier Designs for Energy Efficiency: From Algorithms to Circuits
Published in ACM Transactions on Design Automation of Electronic Systems (TODAES), 2023
Yi Wu, Chuangtao Chen, Weihua Xiao, et al.
MiniTNtk: An Exact Synthesis-based Method for Minimizing Transistor Network
Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023
Weihua Xiao, Shanshan Han, Yue Yang, Shaoze Yang, Cheng Zheng, Jingsong Chen, Tingyuan Liang, Lei Li, and Weikang Qian.
Efficient Approximate Decomposition Solver using Ising Model
Published in ACM/IEEE Design Automation Conference (DAC), 2024
Weihua Xiao*, Tingting Zhang*, Xingyue Qian, Jie Han, and Weikang Qian. *Equal contribution.
Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA
Published in ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), 2025
Weihua Xiao, Derek Ekberg, et al.
VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification
Published in Conference on Neural Information Processing Systems (NeurIPS), 2025
Patrick Yubeaton, Andre Nakkab, Weihua Xiao, et al.
Focus Session: LLM4PQC — Accurate and Efficient Synthesis of PQC Cores by Feedback-Driven LLMs
Published in Design, Automation and Test in Europe Conference (DATE), 2026
Buddhi Perera*, Zeng Wang*, Weihua Xiao*, Mohammed Nabeel, Ozgur Sinanoglu, Johann Knechtel, and Ramesh Karri. *Equal contribution.
Special Day — GUIDE: GenAI Units In Digital Design Education Permalink
Published in Design, Automation and Test in Europe Conference (DATE), 2026
Weihua Xiao, Jason Blocklove, Johann Knechtel, et al.
TrojanGYM: A Detector-in-the-Loop LLM for Adaptive RTL Hardware Trojan Insertion
Published in ACM/IEEE Workshop on Machine Learning for CAD (MLCAD), 2026
Saideep Sreekumar, Zeng Wang, Akashdeep Saha, Weihua Xiao, Minghao Shao, Muhammad Shafique, Ozgur Sinanoglu, Ramesh Karri, and Johann Knechtel. Regular paper.
TrojanLoC: LLM-based Framework for RTL Trojan Localization and Classification
Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2026
Weihua Xiao, Zeng Wang, Minghao Shao, et al. Regular paper.
Gradient Estimation of Approximate Multipliers for High-Accuracy Deep Learning Model Retraining
Under review, 2026
Chang Meng, Weihua Xiao#, Wayne Burleson, and Giovanni De Micheli. #Corresponding author.
VeriDispatcher: Multi-Model Dispatching through Pre-Inference Difficulty Prediction for RTL Generation Optimization
Under review, 2026
Zeng Wang*, Weihua Xiao*, Minghao Shao*, Raghu Vamshi Hemadri, Ozgur Sinanoglu, Muhammad Shafique, and Ramesh Karri. *Equal contribution.
CoEvoP&R: Co-Evolving Placement Objectives with Routing Feedback via Large Language Models
Published in Asia and South Pacific Design Automation Conference (ASP-DAC), 2027
Ruogu Chen, Weihua Xiao#, Ramesh Karri, and Jie Han. #Corresponding author.
talks
teaching
Build Your ASIC
Co-instructor, New York University, 2024
Undergraduate course covering the practical workflow from RTL design through ASIC implementation.
Generative AI Based Chip Design I
Co-instructor, New York University, 2025
Undergraduate and master’s-level course introducing generative AI methods for chip design.
Generative AI Based Chip Design II
Co-instructor, New York University, 2026
Undergraduate and master’s-level course on advanced generative-AI methods for chip design.