Author's Latest Posts


A Novel Fundamental Frequency Switching Operation for Conventional VSI to Enable Single-Stage High-Gain Boost Inversion with ANN Tuned QWS Controller


Abstract "Single-stage high-gain inverters have recently gained much research focus as interfaces for inherent low voltage DC sources such as fuel cells, storage batteries, and solar panels. Many impedance-assisted inverters with different input stage configurations have been presented. To decrease passive component sizes, these inverters operate at high-frequency switching. The high-frequency... » read more

Adaptive NN-Based Root Cause Analysis in Volume Diagnosis for Yield Improvement


Abstract "Root Cause Analysis (RCA) is a critical technology for yield improvement in integrated circuit manufacture. Traditional RCA prefers unsupervised algorithms such as Expectation Maximization based on Bayesian models. However, these methods are severely limited by the weak predictive capability of statistical models and can’t effectively transfer the yield learning experience from old... » read more

Improving Volume Diagnosis and Debug with Test Failure Clustering and Reorganization


Abstract: "Volume diagnosis and debug play a key role in identifying systematic test failures caused by manufacturing defectivity, design marginalities, and test overkill. However, diagnosis tools often suffer from poor diagnosis resolution. In this paper, we propose techniques to improve diagnosis resolution by test failure clustering and reorganization. The effectiveness of our techniques ... » read more

The development of integrated circuits based on two-dimensional materials


Abstract Two-dimensional (2D) materials could potentially be used to develop advanced monolithic integrated circuits. However, despite impressive demonstrations of single devices and simple circuits—in some cases with performance superior to those of silicon-based circuits—reports on the fabrication of integrated circuits using 2D materials are limited and the creation of large-scale circu... » read more

DNS Cache Poisoning Attack: Resurrections with Side Channels


Abstract "DNS is one of the fundamental and ancient protocols on the Internet that supports many network applications and services. Unfortunately, DNS was designed without security in mind and is subject to a variety of serious attacks, one of which is the well-known DNS cache poisoning attack. Over the decades of evolution, it has proven extraordinarily challenging to retrofit strong security... » read more

International Roadmap for Devices and Systems lithography roadmap


Abstract: "Background: Planned improvements in semiconductor chip performance have historically driven improvements in lithography and this is expected to continue in the future. The International Roadmap for Devices and Systems roadmap helps the industry plan for the future. Aim: The 2021 lithography roadmap shows requirements, possible options, and challenges for the next 15 years. Resul... » read more

Absence of Barren Plateaus in Quantum Convolutional Neural Networks


Abstract:  Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exponentially vanishing gradients, known as barren plateau landscapes, for many QNN architectures. Recently, quantum convolutional neural networks (QCNNs) have been proposed, involving a sequence of convol... » read more

Factoring 2048-bit RSA Integers in 177 Days with 13 436 Qubits and a Multimode Memory


Abstract: "We analyze the performance of a quantum computer architecture combining a small processor and a storage unit. By focusing on integer factorization, we show a reduction by several orders of magnitude of the number of processing qubits compared with a standard architecture using a planar grid of qubits with nearest-neighbor connectivity. This is achieved by taking advantage of a tem... » read more

Considerations for Neuromorphic Supercomputing in Semiconducting and Superconducting Optoelectronic Hardware


Abstract: "Any large-scale spiking neuromorphic system striving for complexity at the level of the human brain and beyond will need to be co-optimized for communication and computation. Such reasoning leads to the proposal for optoelectronic neuromorphic platforms that leverage the complementary properties of optics and electronics. Starting from the conjecture that future large-scale neurom... » read more

Enabling Training of Neural Networks on Noisy Hardware


Abstract:  "Deep neural networks (DNNs) are typically trained using the conventional stochastic gradient descent (SGD) algorithm. However, SGD performs poorly when applied to train networks on non-ideal analog hardware composed of resistive device arrays with non-symmetric conductance modulation characteristics. Recently we proposed a new algorithm, the Tiki-Taka algorithm, that overcomes t... » read more

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