GHM: A generalized Hamiltonian method for passivity test of impedance/admittance descriptor systems. - Zheng Zhang 005; Chi-Un Lei; Ngai Wong 001 (ICCAD, 2009)

An extension of the generalized Hamiltonian method to S-parameter descriptor systems. - Zheng Zhang 005; Ngai Wong 001 (ASP-DAC, 2010)

Design space exploration for sparse matrix-matrix multiplication on FPGAs. - Colin Yu Lin; Zheng Zhang 005; Ngai Wong 001; Hayden Kwok-Hay So (FPT, 2010)

PEDS: Passivity enforcement for descriptor systems via Hamiltonian-symplectic matrix pencil perturbation. - Yuanzhe Wang; Zheng Zhang 005; Cheng-Kok Koh; Grantham K. H. Pang; Ngai Wong 001 (ICCAD, 2010)

An Efficient Projector-Based Passivity Test for Descriptor Systems. - Zheng Zhang 005; Ngai Wong 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2010)

Passivity Test of Immittance Descriptor Systems Based on Generalized Hamiltonian Methods. - Zheng Zhang 005; Ngai Wong 001 (IEEE Trans. Circuits Syst. II Express Briefs, 2010)

Balanced truncation for time-delay systems via approximate Gramians. - Xiang Wang; Qing Wang 051; Zheng Zhang 005; Quan Chen 007; Ngai Wong 001 (ASP-DAC, 2011)

A moment-matching scheme for the passivity-preserving model order reduction of indefinite descriptor systems with possible polynomial parts. - Zheng Zhang 005; Qing Wang 051; Ngai Wong 001; Luca Daniel (ASP-DAC, 2011)

A block-diagonal structured model reduction scheme for power grid networks. - Zheng Zhang 005; Xiang Hu; Chung-Kuan Cheng; Ngai Wong 001 (DATE, 2011)

Model order reduction of fully parameterized systems by recursive least square optimization. - Zheng Zhang 005; Ibrahim M. Elfadel; Luca Daniel (ICCAD, 2011)

Passivity Enforcement for Descriptor Systems Via Matrix Pencil Perturbation. - Yuanzhe Wang; Zheng Zhang 005; Cheng-Kok Koh; Guoyong Shi; Grantham K. H. Pang; Ngai Wong 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2012)

Uncertainty quantification for integrated circuits: stochastic spectral methods. - Zheng Zhang 005; Ibrahim M. Elfadel; Luca Daniel (ICCAD, 2013)

Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos. - Zheng Zhang 005; Tarek A. El-Moselhy; Ibrahim M. Elfadel; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2013)

Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits. - Zheng Zhang 005; Tarek A. El-Moselhy; Paolo Maffezzoni; Ibrahim M. Elfadel; Luca Daniel (IEEE Trans. Circuits Syst. II Express Briefs, 2013)

Stochastic testing simulator for integrated circuits and MEMS: Hierarchical and sparse techniques. - Zheng Zhang 005; Xiu Yang; Giovanni Marucci; Paolo Maffezzoni; Ibrahim Abe M. Elfadel; George E. Karniadakis; Luca Daniel (CICC, 2014)

Gramian-based model order reduction of parameterized time-delay systems. - Xiang Wang; Zheng Zhang 005; Qing Wang 051; Ngai Wong 001 (Int. J. Circuit Theory Appl., 2014)

Calculation of Generalized Polynomial-Chaos Basis Functions and Gauss Quadrature Rules in Hierarchical Uncertainty Quantification. - Zheng Zhang 005; Tarek A. El-Moselhy; Ibrahim M. Elfadel; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2014)

A Study of Deterministic Jitter in Crystal Oscillators. - Paolo Maffezzoni; Zheng Zhang 005; Luca Daniel (IEEE Trans. Circuits Syst. I Regul. Pap., 2014)

Probabilistic Power Flow Computation via Low-Rank and Sparse Tensor Recovery. - Zheng Zhang 005; Hung D. Nguyen 001; Konstantin S. Turitsyn; Luca Daniel (CoRR, 2015)

Analysis and Design of Weakly Coupled LC Oscillator Arrays Based on Phase-Domain Macromodels. - Paolo Maffezzoni; Bichoy Bahr; Zheng Zhang 005; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2015)

Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition. - Zheng Zhang 005; Xiu Yang; Ivan V. Oseledets; George E. Karniadakis; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2015)

Oscillator Array Models for Associative Memory and Pattern Recognition. - Paolo Maffezzoni; Bichoy Bahr; Zheng Zhang 005; Luca Daniel (IEEE Trans. Circuits Syst. I Regul. Pap., 2015)

Uncertainty quantification for integrated circuits and microelectrornechanical systems. - Zheng Zhang 005 (2015)

A Big-Data Approach to Handle Process Variations: Uncertainty Quantification by Tensor Recovery. - Zheng Zhang 005; Tsui-Wei Weng; Luca Daniel (CoRR, 2016)

A Big-Data Approach to Handle Many Process Variations: Tensor Recovery and Applications. - Zheng Zhang 005; Tsui-Wei Weng; Luca Daniel (CoRR, 2016)

Reducing Phase Noise in Multi-Phase Oscillators. - Paolo Maffezzoni; Bichoy Bahr; Zheng Zhang 005; Luca Daniel (IEEE Trans. Circuits Syst. I Regul. Pap., 2016)

Analysis and Design of Boolean Associative Memories Made of Resonant Oscillator Arrays. - Paolo Maffezzoni; Bichoy Bahr; Zheng Zhang 005; Luca Daniel (IEEE Trans. Circuits Syst. I Regul. Pap., 2016)

Tensor Computation: A New Framework for High-Dimensional Problems in EDA. - Zheng Zhang 005; Kim Batselier; Haotian Liu; Luca Daniel; Ngai Wong 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

Uncertainty quantification of electronic and photonic ICs with non-Gaussian correlated process variations. - Chunfeng Cui; Zheng Zhang 005 (ICCAD, 2018)

Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion. - Zheng Zhang 005; Cole Hawkins (ICDM, 2018)

Low voltage electrical distribution network analysis under load variation. - Giambattista Gruosso; Roberto Silva Netto; Paolo Maffezzoni; Zheng Zhang 005; Luca Daniel (ICIT, 2018)

Stochastic Collocation with Non-Gaussian Correlated Parameters via a New Quadrature Rule. - Chunfeng Cui; Zheng Zhang 005 (CoRR, 2018)

Variation-Aware Modeling of Integrated Capacitors Based on Floating Random Walk Extraction. - Paolo Maffezzoni; Zheng Zhang 005; Salvatore Levantino; Luca Daniel (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018)

Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models. - Chunfeng Cui; Cole Hawkins; Zheng Zhang 005 (ICCAD, 2019)

Efficient Uncertainty Modeling for System Design via Mixed Integer Programming. - Zichang He; Weilong Cui; Chunfeng Cui; Timothy Sherwood; Zheng Zhang 005 (ICCAD, 2019)

Tucker Tensor Decomposition on FPGA. - Kaiqi Zhang 002; Xiyuan Zhang 003; Zheng Zhang 005 (ICCAD, 2019)

Wafer Pattern Recognition Using Tucker Decomposition. - Ahmed Wahba; Li-C. Wang; Zheng Zhang 005; Nik Sumikawa (VTS, 2019)

Uncertainty-Aware Computational Tools for Power Distribution Networks Including Electrical Vehicle Charging and Load Profiles. - Giambattista Gruosso; Giancarlo Storti Gajani; Zheng Zhang 005; Luca Daniel; Paolo Maffezzoni (IEEE Access, 2019)

Prediction of multi-dimensional spatial variation data via Bayesian tensor completion. - Jiali Luan; Zheng Zhang 005 (CoRR, 2019)

Stochastic Model Predictive Control of Autonomous Systems with Non-Gaussian Correlated Uncertainty. - Huishan Chen; Zheng Zhang 005 (CoRR, 2019)

Quantum-Inspired Hamiltonian Monte Carlo for Bayesian Sampling. - Ziming Liu; Zheng Zhang 005 (CoRR, 2019)

High-Dimensional Uncertainty Quantification via Active and Rank-Adaptive Tensor Regression. - Zichang He; Zheng Zhang 005 (CoRR, 2020)

End-to-End Variational Bayesian Training of Tensorized Neural Networks with Automatic Rank Determination. - Cole Hawkins; Zheng Zhang 005 (CoRR, 2020)

Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. - Chunfeng Cui; Kaiqi Zhang 002; Talgat Daulbaev; Julia Gusak; Ivan V. Oseledets; Zheng Zhang 005 (SIAM J. Math. Data Sci., 2020)

High-Dimensional Uncertainty Quantification of Electronic and Photonic IC With Non-Gaussian Correlated Process Variations. - Chunfeng Cui; Zheng Zhang 005 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Chance-Constrained and Yield-Aware Optimization of Photonic ICs With Non-Gaussian Correlated Process Variations. - Chunfeng Cui; Kaikai Liu; Zheng Zhang 005 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

Prediction of Multidimensional Spatial Variation Data via Bayesian Tensor Completion. - Jiali Luan; Zheng Zhang 005 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020)

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low Bitwidth Quantization, and Ultra-Low Latency Acceleration. - Yao Chen 008; Cole Hawkins; Kaiqi Zhang 002; Zheng Zhang 005; Cong Hao (ACM Great Lakes Symposium on VLSI, 2021)

High-Dimensional Uncertainty Quantification via Rank- and Sample-Adaptive Tensor Regression. - Zichang He; Zheng Zhang 005 (CoRR, 2021)

On-FPGA Training with Ultra Memory Reduction: A Low-Precision Tensor Method. - Kaiqi Zhang 002; Cole Hawkins; Xiyuan Zhang 003; Cong Hao; Zheng Zhang 005 (CoRR, 2021)

3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration. - Yao Chen 008; Cole Hawkins; Kaiqi Zhang 002; Zheng Zhang 005; Cong Hao (CoRR, 2021)

General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification. - Kaiqi Zhang 002; Cole Hawkins; Zheng Zhang 005 (Frontiers Artif. Intell., 2021)

Bayesian tensorized neural networks with automatic rank selection. - Cole Hawkins; Zheng Zhang 005 (Neurocomputing, 2021)

Fast Search of the Optimal Contraction Sequence in Tensor Networks. - Ling Liang; Jianyu Xu; Lei Deng 003; Mingyu Yan; Xing Hu 001; Zheng Zhang 005; Guoqi Li; Yuan Xie 001 (IEEE J. Sel. Top. Signal Process., 2021)

Sparse Tucker Tensor Decomposition on a Hybrid FPGA-CPU Platform. - Weiyun Jiang; Kaiqi Zhang 002; Colin Yu Lin; Feng Xing; Zheng Zhang 005 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

Active Sampling for Accelerated MRI with Low-Rank Tensors. - Zichang He; Bo Zhao 002; Zheng Zhang 005 (EMBC, 2022)

Evolutionary Tensor Train Decomposition for Hyper-Spectral Remote Sensing Images. - Ryan Solgi; Hugo A. Loáiciga; Zheng Zhang 005 (IGARSS, 2022)

A Quantum-Inspired Hamiltonian Monte Carlo Method for Missing Data Imputation. - Didem Kochan; Zheng Zhang 005; Xiu Yang (MSML, 2022)

Online, Informative MCMC Thinning with Kernelized Stein Discrepancy. - Cole Hawkins; Alec Koppel; Zheng Zhang 005 (CoRR, 2022)

Tensor Shape Search for Optimum Data Compression. - Ryan Solgi; Zichang He; William Jiahua Liang; Zheng Zhang 005 (CoRR, 2022)

TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing. - Ziyue Liu 003; Xinling Yu; Zheng Zhang 005 (CoRR, 2022)

MR-Based Electrical Property Reconstruction Using Physics-Informed Neural Networks. - Xinling Yu; José Enrique Cruz Serrallés; Ilias I. Giannakopoulos; Ziyue Liu 003; Luca Daniel; Riccardo Lattanzi; Zheng Zhang 005 (CoRR, 2022)

Towards Compact Neural Networks via End-to-End Training: A Bayesian Tensor Approach with Automatic Rank Determination. - Cole Hawkins; Xing Liu; Zheng Zhang 005 (SIAM J. Math. Data Sci., 2022)

Efficient Processing of Sparse Tensor Decomposition via Unified Abstraction and PE-Interactive Architecture. - Bangyan Wang; Lei Deng 003; Zheng Qu; Shuangchen Li; Zheng Zhang 005; Yuan Xie 001 (IEEE Trans. Computers, 2022)

PoBO: A Polynomial Bounding Method for Chance-Constrained Yield-Aware Optimization of Photonic ICs. - Zichang He; Zheng Zhang 005 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Hardware-Enabled Efficient Data Processing With Tensor-Train Decomposition. - Zheng Qu; Lei Deng 003; Bangyan Wang; Hengnu Chen; Jilan Lin; Ling Liang; Guoqi Li; Zheng Zhang 005; Yuan Xie 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design. - Ziyue Liu 003; Yixing Li; Jing Hu; Xinling Yu; Shinyu Shiau; Xin Ai 007; Zhiyu Zeng; Zheng Zhang 005 (DAC, 2023)

Distributionally Robust Circuit Design Optimization under Variation Shifts. - Yifan Pan; Zichang He; Nanlin Guo; Zheng Zhang 005 (ICCAD, 2023)

Tensorized Optical Multimodal Fusion Network. - Yequan Zhao; Xian Xiao; Geza Kurczveil; Raymond G. Beausoleil; Zheng Zhang 005 (CoRR, 2023)

PIFON-EPT: MR-Based Electrical Property Tomography Using Physics-Informed Fourier Networks. - Xinling Yu; José Enrique Cruz Serrallés; Ilias I. Giannakopoulos; Ziyue Liu 003; Luca Daniel; Riccardo Lattanzi; Zheng Zhang 005 (CoRR, 2023)

A Gradient-based Approach for Online Robust Deep Neural Network Training with Noisy Labels. - Yifan Yang; Alec Koppel; Zheng Zhang 005 (CoRR, 2023)

Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks. - Yequan Zhao; Xinling Yu; Zhixiong Chen 004; Ziyue Liu 003; Sijia Liu 001; Zheng Zhang 005 (CoRR, 2023)

AdaZeta: Adaptive Zeroth-Order Tensor-Train Adaption for Memory-Efficient Large Language Models Fine-Tuning. - Yifan Yang; Kai Zhen; Ershad Banijamali; Athanasios Mouchtaris; Zheng Zhang 005 (EMNLP, 2024)

DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training. - Aochuan Chen; Yimeng Zhang; Jinghan Jia; James Diffenderfer; Konstantinos Parasyris; Jiancheng Liu; Yihua Zhang; Zheng Zhang 005; Bhavya Kailkhura; Sijia Liu 001 (ICLR, 2024)

LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models. - Yifan Yang; Jiajun Zhou; Ngai Wong 001; Zheng Zhang 005 (NAACL-HLT, 2024)

Real-Time FJ/MAC PDE Solvers via Tensorized, Back-Propagation-Free Optical PINN Training. - Yequan Zhao; Xian Xiao; Xinling Yu; Ziyue Liu 003; Zhixiong Chen 004; Geza Kurczveil; Raymond G. Beausoleil; Zheng Zhang 005 (CoRR, 2024)

Poor Man's Training on MCUs: A Memory-Efficient Quantized Back-Propagation-Free Approach. - Yequan Zhao; Hai Li 008; Ian Young 001; Zheng Zhang 005 (CoRR, 2024)

Separable Operator Networks. - Xinling Yu; Sean Hooten; Ziyue Liu 003; Yequan Zhao; Marco Fiorentino; Thomas Van Vaerenbergh; Zheng Zhang 005 (Trans. Mach. Learn. Res., 2024)

Tensor shape search for efficient compression of tensorized data and neural networks. - Ryan Solgi; Zichang He; William Jiahua Liang; Zheng Zhang 005; Hugo A. Loáiciga (Appl. Soft Comput., 2024)

Enhanced Operator Learning for Scalable and Ultra-fast Thermal Simulation in 3D-IC Design. - Xinling Yu; Ziyue Liu 003; Hai Li 008; Ian A. Young; Zheng Zhang 005 (ASP-DAC, 2025)

Experimental Demonstration of an Optical Neural PDE Solver via On-Chip PINN Training. - Yequan Zhao; Xian Xiao; Antoine Descos; Yuan Yuan 033; Xinling Yu; Geza Kurczveil; Marco Fiorentino; Zheng Zhang 005; Raymond G. Beausoleil (OFC, 2025)

Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization. - Jiayi Tian; Jinming Lu; Hai Li 008; Xiangwei Wang; Cong Hao; Ian A. Young; Zheng Zhang 005 (CoRR, 2025)

QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models. - Jiajun Zhou; Yifan Yang; Kai Zhen; Ziyue Liu 003; Yequan Zhao; Ershad Banijamali; Athanasios Mouchtaris; Ngai Wong 001; Zheng Zhang 005 (CoRR, 2025)

Scalable Back-Propagation-Free Training of Optical Physics-Informed Neural Networks. - Yequan Zhao; Xinling Yu; Xian Xiao; Zhixiong Chen 004; Ziyue Liu 003; Geza Kurczveil; Raymond G. Beausoleil; Sijia Liu 001; Zheng Zhang 005 (CoRR, 2025)

DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design. - Xinling Yu; Ziyue Liu 003; Hai Li 008; Yixing Li; Xin Ai 007; Zhiyu Zeng; Ian A. Young; Zheng Zhang 005 (CoRR, 2025)

FETTA: Flexible and Efficient Hardware Accelerator for Tensorized Neural Network Training. - Jinming Lu; Jiayi Tian; Hai Li 008; Ian A. Young; Zheng Zhang 005 (CoRR, 2025)

Saten: Sparse Augmented Tensor Networks for Post-Training Compression of Large Language Models. - Ryan Solgi; Kai Zhen; Rupak Vignesh Swaminathan; Nathan Susanj; Athanasios Mouchtaris; Siegfried Kunzmann; Zheng Zhang 005 (CoRR, 2025)

FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model Compression. - Jiayi Tian; Ryan Solgi; Jinming Lu; Yifan Yang; Hai Li 008; Zheng Zhang 005 (CoRR, 2025)