Zheng Zhang - RankMe

119 papers A* 5A 10C 1Misc 1Journal 87Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression. EACL (Findings) Jiayi Tian, Ryan Solgi, Jinming Lu, Yifan Yang, Hai Li, Zheng Zhang
2026	J	`jnl`	Powering Up Zeroth-Order Training via Subspace Gradient Orthogonalization. CoRR Yicheng Lang, Changsheng Wang, Yihua Zhang, Mingyi Hong, Zheng Zhang, Wotao Yin, Sijia Liu
2026	J	`jnl`	TEON: Tensorized Orthonormalization Beyond Layer-Wise Muon for Large Language Model Pre-Training. CoRR Ruijie Zhang, Yequan Zhao, Ziyue Liu, Zhengyang Wang, Dongyang Li, Yupeng Su, Sijia Liu, Zheng Zhang
2026	J	`jnl`	Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Jiayi Tian, Jinming Lu, Hai Li, Xiangwei Wang, Cong Callie Hao, Ian A. Young, Zheng Zhang
2025	J	`jnl`	DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design. CoRR Xinling Yu, Ziyue Liu, Hai Li, Yixing Li, Xin Ai, Zhiyu Zeng, Ian A. Young, Zheng Zhang
2025	—	`conf`	Enhanced Operator Learning for Scalable and Ultra-fast Thermal Simulation in 3D-IC Design. ASP-DAC Xinling Yu, Ziyue Liu, Hai Li, Ian A. Young, Zheng Zhang
2025	—	`conf`	Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training. OFC Yequan Zhao, Xian Xiao, Antoine Descos, Yuan Yuan, Xinling Yu, Geza Kurczveil, Marco Fiorentino, Zheng Zhang, Raymond G. Beausoleil
2025	J	`jnl`	Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training. CoRR Yequan Zhao, Xian Xiao, Antoine Descos, Yuan Yuan, Xinling Yu, Geza Kurczveil, Marco Fiorentino, Zheng Zhang, Raymond G. Beausoleil
2025	J	`jnl`	FETTA: Flexible and Efficient Hardware Accelerator for Tensorized Neural Network Training. CoRR Jinming Lu, Jiayi Tian, Hai Li, Ian A. Young, Zheng Zhang
2025	J	`jnl`	FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression. CoRR Jiayi Tian, Ryan Solgi, Jinming Lu, Yifan Yang, Hai Li, Zheng Zhang
2025	J	`jnl`	KANO: Kolmogorov-Arnold Neural Operator. CoRR Jin Lee, Ziming Liu, Xinling Yu, Yixuan Wang, Haewon Jeong, Murphy Yuezhen Niu, Zheng Zhang
2025	J	`jnl`	Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach. ACM Trans. Design Autom. Electr. Syst. Yequan Zhao, Hai Li, Ian A. Young, Zheng Zhang
2025	A*	`conf`	QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models. EMNLP Jiajun Zhou, Yifan Yang, Kai Zhen, Ziyue Liu, Yequan Zhao, Ershad Banijamali, Athanasios Mouchtaris, Ngai Wong, Zheng Zhang
2025	J	`jnl`	QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models. CoRR Jiajun Zhou, Yifan Yang, Kai Zhen, Ziyue Liu, Yequan Zhao, Ershad Banijamali, Athanasios Mouchtaris, Ngai Wong, Zheng Zhang
2025	—	`conf`	Saten: Sparse Augmented Tensor Networks for Post-Training Compression of Large Language Models. EMNLP (Findings) Ryan Solgi, Kai Zhen, Rupak Vignesh Swaminathan, Nathan Susanj, Athanasios Mouchtaris, Siegfried Kunzmann, Zheng Zhang
2025	J	`jnl`	Saten: Sparse Augmented Tensor Networks for Post-Training Compression of Large Language Models. CoRR Ryan Solgi, Kai Zhen, Rupak Vignesh Swaminathan, Nathan Susanj, Athanasios Mouchtaris, Siegfried Kunzmann, Zheng Zhang
2025	J	`jnl`	Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks. CoRR Yequan Zhao, Xinling Yu, Xian Xiao, Zhixiong Chen, Ziyue Liu, Geza Kurczveil, Raymond G. Beausoleil, Sijia Liu, Zheng Zhang
2025	J	`jnl`	Tensor-Compressed and Fully-Quantized Training of Neural PDE Solvers. CoRR Jinming Lu, Jiayi Tian, Yequan Zhao, Hai Li, Zheng Zhang
2025	J	`jnl`	Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization. CoRR Jiayi Tian, Jinming Lu, Hai Li, Xiangwei Wang, Cong Hao, Ian A. Young, Zheng Zhang
2024	A*	`conf`	AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tuning. EMNLP Yifan Yang, Kai Zhen, Ershad Banijamali, Athanasios Mouchtaris, Zheng Zhang
2024	J	`jnl`	AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tuning. CoRR Yifan Yang, Kai Zhen, Ershad Banijamali, Athanasios Mouchtaris, Zheng Zhang
2024	A*	`conf`	DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. ICLR Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Konstantinos Parasyris, Jiancheng Liu, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2024	—	`conf`	LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models. NAACL-HLT Yifan Yang, Jiajun Zhou, Ngai Wong, Zheng Zhang
2024	J	`jnl`	LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models. CoRR Yifan Yang, Jiajun Zhou, Ngai Wong, Zheng Zhang
2024	J	`jnl`	Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach. CoRR Yequan Zhao, Hai Li, Ian Young, Zheng Zhang
2024	J	`jnl`	Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training. CoRR Yequan Zhao, Xian Xiao, Xinling Yu, Ziyue Liu, Zhixiong Chen, Geza Kurczveil, Raymond G. Beausoleil, Zheng Zhang
2024	J	`jnl`	Separable Operator Networks. CoRR Xinling Yu, Sean Hooten, Ziyue Liu, Yequan Zhao, Marco Fiorentino, Thomas Van Vaerenbergh, Zheng Zhang
2024	J	`jnl`	Separable Operator Networks. Trans. Mach. Learn. Res. Xinling Yu, Sean Hooten, Ziyue Liu, Yequan Zhao, Marco Fiorentino, Thomas Van Vaerenbergh, Zheng Zhang
2024	J	`jnl`	Tensor shape search for efficient compression of tensorized data and neural networks. Appl. Soft Comput. Ryan Solgi, Zichang He, William Jiahua Liang, Zheng Zhang, Hugo A. Loáiciga
2023	J	`jnl`	A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels. CoRR Yifan Yang, Alec Koppel, Zheng Zhang
2023	A*	`conf`	DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design. DAC Ziyue Liu, Yixing Li, Jing Hu, Xinling Yu, Shinyu Shiau, Xin Ai, Zhiyu Zeng, Zheng Zhang
2023	J	`jnl`	DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design. CoRR Ziyue Liu, Yixing Li, Jing Hu, Xinling Yu, Shinyu Shiau, Xin Ai, Zhiyu Zeng, Zheng Zhang
2023	J	`jnl`	DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training. CoRR Aochuan Chen, Yimeng Zhang, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu
2023	A	`conf`	Distributionally Robust Circuit Design Optimization under Variation Shifts. ICCAD Yifan Pan, Zichang He, Nanlin Guo, Zheng Zhang
2023	J	`jnl`	Distributionally Robust Circuit Design Optimization under Variation Shifts. CoRR Yifan Pan, Zichang He, Nanlin Guo, Zheng Zhang
2023	J	`jnl`	PIFON-EPT: MR-Based Electrical Property Tomography Using Physics-Informed Fourier Networks. CoRR Xinling Yu, José Enrique Cruz Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang
2023	J	`jnl`	Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks. CoRR Yequan Zhao, Xinling Yu, Zhixiong Chen, Ziyue Liu, Sijia Liu, Zheng Zhang
2023	J	`jnl`	Tensorized Optical Multimodal Fusion Network. CoRR Yequan Zhao, Xian Xiao, Geza Kurczveil, Raymond G. Beausoleil, Zheng Zhang
2022	—	`conf`	A Quantum-Inspired Hamiltonian Monte Carlo Method for Missing Data Imputation. MSML Didem Kochan, Zheng Zhang, Xiu Yang
2022	—	`conf`	Active Sampling for Accelerated MRI with Low-Rank Tensors. EMBC Zichang He, Bo Zhao, Zheng Zhang
2022	J	`jnl`	Efficient Processing of Sparse Tensor Decomposition via Unified Abstraction and PE-Interactive Architecture. IEEE Trans. Computers Bangyan Wang, Lei Deng, Zheng Qu, Shuangchen Li, Zheng Zhang, Yuan Xie
2022	C	`conf`	Evolutionary Tensor Train Decomposition for Hyper-Spectral Remote Sensing Images. IGARSS Ryan Solgi, Hugo A. Loáiciga, Zheng Zhang
2022	J	`jnl`	Hardware-Enabled Efficient Data Processing With Tensor-Train Decomposition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Qu, Lei Deng, Bangyan Wang, Hengnu Chen, Jilan Lin, Ling Liang, Guoqi Li, Zheng Zhang, Yuan Xie
2022	J	`jnl`	MR-Based Electrical Property Reconstruction Using Physics-Informed Neural Networks. CoRR Xinling Yu, José Enrique Cruz Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang
2022	J	`jnl`	Online, Informative MCMC Thinning with Kernelized Stein Discrepancy. CoRR Cole Hawkins, Alec Koppel, Zheng Zhang
2022	J	`jnl`	PoBO: A Polynomial Bounding Method for Chance-Constrained Yield-Aware Optimization of Photonic ICs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zichang He, Zheng Zhang
2022	J	`jnl`	TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing. CoRR Ziyue Liu, Xinling Yu, Zheng Zhang
2022	J	`jnl`	Tensor Shape Search for Optimum Data Compression. CoRR Ryan Solgi, Zichang He, William Jiahua Liang, Zheng Zhang
2022	J	`jnl`	Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination. SIAM J. Math. Data Sci. Cole Hawkins, Xing Liu, Zheng Zhang
2021	—	`conf`	3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration. ACM Great Lakes Symposium on VLSI Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
2021	J	`jnl`	3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration. CoRR Yao Chen, Cole Hawkins, Kaiqi Zhang, Zheng Zhang, Cong Hao
2021	J	`jnl`	Bayesian tensorized neural networks with automatic rank selection. Neurocomputing Cole Hawkins, Zheng Zhang
2021	J	`jnl`	Fast Search of the Optimal Contraction Sequence in Tensor Networks. IEEE J. Sel. Top. Signal Process. Ling Liang, Jianyu Xu, Lei Deng, Mingyu Yan, Xing Hu, Zheng Zhang, Guoqi Li, Yuan Xie
2021	J	`jnl`	General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification. Frontiers Artif. Intell. Kaiqi Zhang, Cole Hawkins, Zheng Zhang
2021	J	`jnl`	High-Dimensional Uncertainty Quantification via Rank- and Sample-Adaptive Tensor Regression. CoRR Zichang He, Zheng Zhang
2021	J	`jnl`	On-FPGA Training with Ultra Memory Reduction: A Low-Precision Tensor Method. CoRR Kaiqi Zhang, Cole Hawkins, Xiyuan Zhang, Cong Hao, Zheng Zhang
2021	J	`jnl`	Sparse Tucker Tensor Decomposition on a Hybrid FPGA-CPU Platform. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Weiyun Jiang, Kaiqi Zhang, Colin Yu Lin, Feng Xing, Zheng Zhang
2020	J	`jnl`	Active Sampling for Accelerated MRI with Low-Rank Tensors. CoRR Zichang He, Bo Zhao, Zheng Zhang
2020	J	`jnl`	Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. SIAM J. Math. Data Sci. Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang
2020	J	`jnl`	Chance-Constrained and Yield-Aware Optimization of Photonic ICs With Non-Gaussian Correlated Process Variations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Chunfeng Cui, Kaikai Liu, Zheng Zhang
2020	J	`jnl`	End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination. CoRR Cole Hawkins, Zheng Zhang
2020	J	`jnl`	High-Dimensional Uncertainty Quantification of Electronic and Photonic IC With Non-Gaussian Correlated Process Variations. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Chunfeng Cui, Zheng Zhang
2020	J	`jnl`	High-Dimensional Uncertainty Quantification via Active and Rank-Adaptive Tensor Regression. CoRR Zichang He, Zheng Zhang
2020	J	`jnl`	Prediction of Multidimensional Spatial Variation Data via Bayesian Tensor Completion. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Jiali Luan, Zheng Zhang
2020	J	`jnl`	Sparse Tucker Tensor Decomposition on a Hybrid FPGA-CPU Platform. CoRR Weiyun Jiang, Kaiqi Zhang, Colin Yu Lin, Feng Xing, Zheng Zhang
2019	J	`jnl`	Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. CoRR Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang
2019	J	`jnl`	Bayesian Tensorized Neural Networks with Automatic Rank Selection. CoRR Cole Hawkins, Zheng Zhang
2019	A	`conf`	Efficient Uncertainty Modeling for System Design via Mixed Integer Programming. ICCAD Zichang He, Weilong Cui, Chunfeng Cui, Timothy Sherwood, Zheng Zhang
2019	J	`jnl`	Efficient Uncertainty Modeling for System Design via Mixed Integer Programming. CoRR Zichang He, Weilong Cui, Chunfeng Cui, Timothy Sherwood, Zheng Zhang
2019	J	`jnl`	Prediction of multi-dimensional spatial variation data via Bayesian tensor completion. CoRR Jiali Luan, Zheng Zhang
2019	J	`jnl`	Quantum-Inspired Hamiltonian Monte Carlo for Bayesian Sampling. CoRR Ziming Liu, Zheng Zhang
2019	J	`jnl`	Stochastic Model Predictive Control of Autonomous Systems with Non-Gaussian Correlated Uncertainty. CoRR Huishan Chen, Zheng Zhang
2019	A	`conf`	Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models. ICCAD Chunfeng Cui, Cole Hawkins, Zheng Zhang
2019	A	`conf`	Tucker Tensor Decomposition on FPGA. ICCAD Kaiqi Zhang, Xiyuan Zhang, Zheng Zhang
2019	J	`jnl`	Tucker Tensor Decomposition on FPGA. CoRR Kaiqi Zhang, Xiyuan Zhang, Zheng Zhang
2019	J	`jnl`	Uncertainty-Aware Computational Tools for Power Distribution Networks Including Electrical Vehicle Charging and Load Profiles. IEEE Access Giambattista Gruosso, Giancarlo Storti Gajani, Zheng Zhang, Luca Daniel, Paolo Maffezzoni
2019	Misc	`conf`	Wafer Pattern Recognition Using Tucker Decomposition. VTS Ahmed Wahba, Li-C. Wang, Zheng Zhang, Nik Sumikawa
2018	—	`conf`	Low voltage electrical distribution network analysis under load variation. ICIT Giambattista Gruosso, Roberto Silva Netto, Paolo Maffezzoni, Zheng Zhang, Luca Daniel
2018	J	`jnl`	Stochastic Collocation with Non-Gaussian Correlated Parameters via a New Quadrature Rule. CoRR Chunfeng Cui, Zheng Zhang
2018	J	`jnl`	Uncertainty Quantification of Electronic and Photonic ICs with Non-Gaussian Correlated Process Variations. CoRR Chunfeng Cui, Zheng Zhang
2018	A	`conf`	Uncertainty quantification of electronic and photonic ICs with non-Gaussian correlated process variations. ICCAD Chunfeng Cui, Zheng Zhang
2018	J	`jnl`	Variation-Aware Modeling of Integrated Capacitors Based on Floating Random Walk Extraction. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Paolo Maffezzoni, Zheng Zhang, Salvatore Levantino, Luca Daniel
2018	A*	`conf`	Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion. ICDM Zheng Zhang, Cole Hawkins
2018	J	`jnl`	Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion. CoRR Cole Hawkins, Zheng Zhang
2017	J	`jnl`	Tensor Computation: A New Framework for High-Dimensional Problems in EDA. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Zhang, Kim Batselier, Haotian Liu, Luca Daniel, Ngai Wong
2016	J	`jnl`	A Big-Data Approach to Handle Many Process Variations: Tensor Recovery and Applications. CoRR Zheng Zhang, Tsui-Wei Weng, Luca Daniel
2016	J	`jnl`	A Big-Data Approach to Handle Process Variations: Uncertainty Quantification by Tensor Recovery. CoRR Zheng Zhang, Tsui-Wei Weng, Luca Daniel
2016	J	`jnl`	Analysis and Design of Boolean Associative Memories Made of Resonant Oscillator Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. Paolo Maffezzoni, Bichoy Bahr, Zheng Zhang, Luca Daniel
2016	J	`jnl`	Reducing Phase Noise in Multi-Phase Oscillators. IEEE Trans. Circuits Syst. I Regul. Pap. Paolo Maffezzoni, Bichoy Bahr, Zheng Zhang, Luca Daniel
2016	J	`jnl`	Tensor Computation: A New Framework for High-Dimensional Problems in EDA. CoRR Zheng Zhang, Kim Batselier, Haotian Liu, Luca Daniel, Ngai Wong
2015	J	`jnl`	Analysis and Design of Weakly Coupled LC Oscillator Arrays Based on Phase-Domain Macromodels. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Paolo Maffezzoni, Bichoy Bahr, Zheng Zhang, Luca Daniel
2015	J	`jnl`	Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Zhang, Xiu Yang, Ivan V. Oseledets, George E. Karniadakis, Luca Daniel
2015	J	`jnl`	Oscillator Array Models for Associative Memory and Pattern Recognition. IEEE Trans. Circuits Syst. I Regul. Pap. Paolo Maffezzoni, Bichoy Bahr, Zheng Zhang, Luca Daniel
2015	J	`jnl`	Probabilistic Power Flow Computation via Low-Rank and Sparse Tensor Recovery. CoRR Zheng Zhang, Hung D. Nguyen, Konstantin S. Turitsyn, Luca Daniel
2015	—	`—`	Uncertainty quantification for integrated circuits and microelectrornechanical systems. Zheng Zhang
2014	J	`jnl`	A Study of Deterministic Jitter in Crystal Oscillators. IEEE Trans. Circuits Syst. I Regul. Pap. Paolo Maffezzoni, Zheng Zhang, Luca Daniel
2014	J	`jnl`	Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification. CoRR Zheng Zhang, Tarek A. El-Moselhy, Ibrahim M. Elfadel, Luca Daniel
2014	J	`jnl`	Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Zhang, Tarek A. El-Moselhy, Ibrahim M. Elfadel, Luca Daniel
2014	J	`jnl`	Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits. CoRR Zheng Zhang, Tarek A. El-Moselhy, Paolo Maffezzoni, Ibrahim M. Elfadel, Luca Daniel
2014	J	`jnl`	Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition. CoRR Zheng Zhang, Xiu Yang, Ivan V. Oseledets, George E. Karniadakis, Luca Daniel
2014	J	`jnl`	Gramian-based model order reduction of parameterized time-delay systems. Int. J. Circuit Theory Appl. Xiang Wang, Zheng Zhang, Qing Wang, Ngai Wong
2014	J	`jnl`	Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos. CoRR Zheng Zhang, Tarek A. El-Moselhy, Ibrahim M. Elfadel, Luca Daniel
2014	J	`jnl`	Stochastic Testing Simulator for Integrated Circuits and MEMS: Hierarchical and Sparse Techniques. CoRR Zheng Zhang, Xiu Yang, Giovanni Marucci, Paolo Maffezzoni, Ibrahim M. Elfadel, George E. Karniadakis, Luca Daniel
2014	—	`conf`	Stochastic testing simulator for integrated circuits and MEMS: Hierarchical and sparse techniques. CICC Zheng Zhang, Xiu Yang, Giovanni Marucci, Paolo Maffezzoni, Ibrahim Abe M. Elfadel, George E. Karniadakis, Luca Daniel
2014	J	`jnl`	Uncertainty Quantification for Integrated Circuits: Stochastic Spectral Methods. CoRR Zheng Zhang, Ibrahim M. Elfadel, Luca Daniel
2013	J	`jnl`	Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits. IEEE Trans. Circuits Syst. II Express Briefs Zheng Zhang, Tarek A. El-Moselhy, Paolo Maffezzoni, Ibrahim M. Elfadel, Luca Daniel
2013	J	`jnl`	Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Zhang, Tarek A. El-Moselhy, Ibrahim M. Elfadel, Luca Daniel
2013	A	`conf`	Uncertainty quantification for integrated circuits: stochastic spectral methods. ICCAD Zheng Zhang, Ibrahim M. Elfadel, Luca Daniel
2012	J	`jnl`	Passivity Enforcement for Descriptor Systems Via Matrix Pencil Perturbation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Yuanzhe Wang, Zheng Zhang, Cheng-Kok Koh, Guoyong Shi, Grantham K. H. Pang, Ngai Wong
2011	A	`conf`	A block-diagonal structured model reduction scheme for power grid networks. DATE Zheng Zhang, Xiang Hu, Chung-Kuan Cheng, Ngai Wong
2011	—	`conf`	A moment-matching scheme for the passivity-preserving model order reduction of indefinite descriptor systems with possible polynomial parts. ASP-DAC Zheng Zhang, Qing Wang, Ngai Wong, Luca Daniel
2011	—	`conf`	Balanced truncation for time-delay systems via approximate Gramians. ASP-DAC Xiang Wang, Qing Wang, Zheng Zhang, Quan Chen, Ngai Wong
2011	A	`conf`	Model order reduction of fully parameterized systems by recursive least square optimization. ICCAD Zheng Zhang, Ibrahim M. Elfadel, Luca Daniel
2010	J	`jnl`	An Efficient Projector-Based Passivity Test for Descriptor Systems. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Zheng Zhang, Ngai Wong
2010	—	`conf`	An extension of the generalized Hamiltonian method to ASP-DAC Zheng Zhang, Ngai Wong
2010	—	`conf`	Design space exploration for sparse matrix-matrix multiplication on FPGAs. FPT Colin Yu Lin, Zheng Zhang, Ngai Wong, Hayden Kwok-Hay So
2010	A	`conf`	PEDS: Passivity enforcement for descriptor systems via Hamiltonian-symplectic matrix pencil perturbation. ICCAD Yuanzhe Wang, Zheng Zhang, Cheng-Kok Koh, Grantham K. H. Pang, Ngai Wong
2010	J	`jnl`	Passivity Test of Immittance Descriptor Systems Based on Generalized Hamiltonian Methods. IEEE Trans. Circuits Syst. II Express Briefs Zheng Zhang, Ngai Wong
2009	A	`conf`	GHM: A generalized Hamiltonian method for passivity test of impedance/admittance descriptor systems. ICCAD Zheng Zhang, Chi-Un Lei, Ngai Wong