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A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits

IEEE transactions on microwave theory and techniques, 2022-01, Vol.70 (1), p.926-937

2022

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Accurate Reduced Dimensional Polynomial Chaos for Efficient Uncertainty Quantification of Microwave/RF Networks

IEEE transactions on microwave theory and techniques, 2017-10, Vol.65 (10), p.3697-3708

2017

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Sparse Linear Regression (SPLINER) Approach for Efficient Multidimensional Uncertainty Quantification of High-Speed Circuits

IEEE transactions on computer-aided design of integrated circuits and systems, 2016-10, Vol.35 (10), p.1640-1652

2016

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Two-Level Multifidelity Algorithm With Dimension Reduction for Efficient Uncertainty Quantification of MWCNT Interconnects

IEEE transactions on electromagnetic compatibility, 2021-12, Vol.63 (6), p.1941-1950

2021

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Machine Learning Augmented Compact Modeling for Simultaneous Improvement in Computational Speed and Accuracy

IEEE transactions on electron devices, 2024-01, Vol.71 (1), p.1-7

2024

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Multidimensional Uncertainty Quantification of Microwave/RF Networks Using Linear Regression and Optimal Design of Experiments

IEEE transactions on microwave theory and techniques, 2016-08, Vol.64 (8), p.2433-2446

2016

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A Space Mapping Augmented Compact Model for Uncertainty Quantification of GaN HEMT Devices and Circuits in the Presence of Trap Effects

IEEE transactions on electron devices, 2024-11, Vol.71 (11), p.6581-6587

2024

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Deep Learning-Based Fast BSIM-CMG Parameter Extraction for General Input Dataset

IEEE transactions on electron devices, 2023-07, Vol.70 (7), p.1-5

2023

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Analysis of a Polynomial Chaos-Kriging Metamodel for Uncertainty Quantification in Aerodynamics

AIAA journal, 2019-06, Vol.57 (6), p.2280-2296

2019

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Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks

IEEE transactions on components, packaging, and manufacturing technology (2011), 2019-06, Vol.9 (6), p.1119-1132

2019

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Machine Learning-Assisted Multiobjective Optimization of Advanced Node Gate-All-Around Transistor for Logic and RF Applications

IEEE transactions on electron devices, 2024-02, Vol.71 (2), p.1-7

2024

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On-Chip Learning of Neural Network Using Spin-Based Activation Function Nodes

IEEE transactions on electron devices, 2024-08, Vol.71 (8), p.5118-5124

2024

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Modified Knowledge-Based Neural Networks Using Control Variates for the Fast Uncertainty Quantification of On-Chip MWCNT Interconnects

IEEE transactions on electromagnetic compatibility, 2023-08, Vol.65 (4), p.1-15

2023

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Knowledge-Based Neural Networks for Fast Design Space Exploration of Hybrid Copper-Graphene On-Chip Interconnect Networks

IEEE transactions on electromagnetic compatibility, 2022-02, Vol.64 (1), p.182-195

2022

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Theoretical Insights of the Photocatalytic and Hydrogen Storage Ability of Two-Dimensional (2-D) MoSe (MX) and MoSSe (MXY) ( = Se, = S) ML Using DFT Study

IEEE sensors journal, 2024-01, Vol.24 (1), p.223-230

2024

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Comparative Analysis of Prior Knowledge-Based Machine Learning Metamodels for Modeling Hybrid Copper-Graphene On-Chip Interconnects

IEEE transactions on electromagnetic compatibility, 2022-12, Vol.64 (6), p.1-12

2022

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Artificial Neural Networks With Fast Transfer Learning for Statistical Signal Integrity Analysis of MWCNT and MLGNR Interconnect Networks

IEEE transactions on electromagnetic compatibility, 2024-06, Vol.66 (3), p.939-948

2024

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Fast Multi-ANN Composite Models for Repeater Optimization in Presence of Parametric Uncertainty for on-Chip Hybrid Copper-Graphene Interconnects

IEEE access, 2023, Vol.11, p.131191-131204

2023

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Advancements in memory technologies for artificial synapses

Journal of materials chemistry. C, Materials for optical and electronic devices, 2024-04, Vol.12 (15), p.5274-5298

2024

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A Predictor-Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects

IEEE transactions on components, packaging, and manufacturing technology (2011), 2019-10, Vol.9 (10), p.1963-1975

2019

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Modified Small Signal Circuit of AlGaN/GaN MOS-HEMTs Using Rational Functions

IEEE transactions on electron devices, 2021-12, Vol.68 (12), p.6059-6064

2021

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A Temperature and Dielectric Roughness-Aware Matrix Rational Approximation Model for the Reliability Assessment of Copper- Graphene Hybrid On-Chip Interconnects

IEEE transactions on components, packaging, and manufacturing technology (2011), 2020-09, Vol.10 (9), p.1454-1465

2020

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Multi-Fidelity Approach for Polynomial Chaos Based Statistical Analysis of Microwave Networks

Applied Computational Electromagnetics Society journal, 2019, Vol.34 (2), p.358

2019

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A Deep Learning Space Mapping Based Enhancement of Compact Models for Accurate Prediction of Trapping in GaN HEMTs from DC to mm-Wave Frequency

2023 IEEE/MTT-S International Microwave Symposium - IMS 2023, 2023, p.89-92

2023

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A Bilevel Multi-Fidelity Polynomial Chaos Approach for the Uncertainty Quantification of MWCNT Interconnect Networks with Variable Imperfect Contact Resistances

IEEE access, 2022, Vol.10, p.1-1

2022

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A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits

Accurate Reduced Dimensional Polynomial Chaos for Efficient Uncertainty Quantification of Microwave/RF Networks

Sparse Linear Regression (SPLINER) Approach for Efficient Multidimensional Uncertainty Quantification of High-Speed Circuits

Two-Level Multifidelity Algorithm With Dimension Reduction for Efficient Uncertainty Quantification of MWCNT Interconnects

Machine Learning Augmented Compact Modeling for Simultaneous Improvement in Computational Speed and Accuracy

Multidimensional Uncertainty Quantification of Microwave/RF Networks Using Linear Regression and Optimal Design of Experiments

A Space Mapping Augmented Compact Model for Uncertainty Quantification of GaN HEMT Devices and Circuits in the Presence of Trap Effects

Deep Learning-Based Fast BSIM-CMG Parameter Extraction for General Input Dataset

Analysis of a Polynomial Chaos-Kriging Metamodel for Uncertainty Quantification in Aerodynamics

Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks

Machine Learning-Assisted Multiobjective Optimization of Advanced Node Gate-All-Around Transistor for Logic and RF Applications

On-Chip Learning of Neural Network Using Spin-Based Activation Function Nodes

Modified Knowledge-Based Neural Networks Using Control Variates for the Fast Uncertainty Quantification of On-Chip MWCNT Interconnects

Knowledge-Based Neural Networks for Fast Design Space Exploration of Hybrid Copper-Graphene On-Chip Interconnect Networks

Theoretical Insights of the Photocatalytic and Hydrogen Storage Ability of Two-Dimensional (2-D) MoSe (MX) and MoSSe (MXY) ( = Se, = S) ML Using DFT Study

Comparative Analysis of Prior Knowledge-Based Machine Learning Metamodels for Modeling Hybrid Copper-Graphene On-Chip Interconnects

Artificial Neural Networks With Fast Transfer Learning for Statistical Signal Integrity Analysis of MWCNT and MLGNR Interconnect Networks

Fast Multi-ANN Composite Models for Repeater Optimization in Presence of Parametric Uncertainty for on-Chip Hybrid Copper-Graphene Interconnects

Advancements in memory technologies for artificial synapses

A Predictor-Corrector Algorithm for Fast Polynomial Chaos-Based Uncertainty Quantification of Multi-Walled Carbon Nanotube Interconnects

Modified Small Signal Circuit of AlGaN/GaN MOS-HEMTs Using Rational Functions

A Temperature and Dielectric Roughness-Aware Matrix Rational Approximation Model for the Reliability Assessment of Copper- Graphene Hybrid On-Chip Interconnects

Multi-Fidelity Approach for Polynomial Chaos Based Statistical Analysis of Microwave Networks

A Deep Learning Space Mapping Based Enhancement of Compact Models for Accurate Prediction of Trapping in GaN HEMTs from DC to mm-Wave Frequency

A Bilevel Multi-Fidelity Polynomial Chaos Approach for the Uncertainty Quantification of MWCNT Interconnect Networks with Variable Imperfect Contact Resistances

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