Rashmi Jha
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View article: Understanding ferroelectricity in sputtered aluminum nitride thin films on silicon
Understanding ferroelectricity in sputtered aluminum nitride thin films on silicon Open
We report ferroelectric switching at room temperature in sub-100 nm aluminum nitride thin films deposited using radio frequency magnetron sputtering in a metal–insulator–metal configuration. The film microstructures were investigated using…
View article: Impact of electrodes and interfaces on ferroelectric switching of Al1-xScxN
Impact of electrodes and interfaces on ferroelectric switching of Al1-xScxN Open
This work reports the role of different metal bottom electrodes such as Tungsten (W), Titanium/Ruthenium (Ti/Ru), and Scandium (Sc) on the Ferroelectric Switching of sub-100-nm Al 1-x Sc x N thin films deposited via reactive co-sputtering …
View article: A Survey of Electromagnetic Radiation Based Hardware Assurance and Reliability Monitoring Methods in Integrated Circuits
A Survey of Electromagnetic Radiation Based Hardware Assurance and Reliability Monitoring Methods in Integrated Circuits Open
Electromagnetic (EM) radiation-based hardware assurance methods are gaining prominence due to their non-invasive nature of monitoring the chip activity and the potential for continuous monitoring of integrated circuits (ICs) during operati…
View article: Studying Accuracy of Machine Learning Models Trained on Lab Lifting Data in Solving Real-World Problems Using Wearable Sensors for Workplace Safety
Studying Accuracy of Machine Learning Models Trained on Lab Lifting Data in Solving Real-World Problems Using Wearable Sensors for Workplace Safety Open
Porting ML models trained on lab data to real-world situations has long been a challenge. This paper discusses porting a lab-trained lifting identification model to the real-world. With performance much lower than on training data, we expl…
View article: Emerging Memory Devices Beyond Conventional Data Storage: Paving the Path for Energy-Efficient Brain-Inspired Computing
Emerging Memory Devices Beyond Conventional Data Storage: Paving the Path for Energy-Efficient Brain-Inspired Computing Open
The current state of neuromorphic computing broadly encompasses domain-specific computing architectures designed to accelerate machine learning (ML) and artificial intelligence (AI) algorithms. As is well known, AI/ML algorithms are limite…
View article: NeuroSOFM-Classifier: A Low Power Classifier Using Continuous Real-Time Unsupervised Clustering
NeuroSOFM-Classifier: A Low Power Classifier Using Continuous Real-Time Unsupervised Clustering Open
Supervised machine learning techniques are becoming subject of significant interest in data analysis. However, the high memory bandwidth requirement of current implementations and scarcity of labeled data in many applications prevents impl…
View article: Machine Learning for Detection and Risk Assessment of Lifting Action
Machine Learning for Detection and Risk Assessment of Lifting Action Open
Repetitive occupational lifting has been shown to create an increased risk for incidence of back pain. Ergonomic workstations that promote proper lifting technique can reduce risk, but it is difficult to assess the workstations without con…
View article: Exploring the associative learning capabilities of the segmented attractor network for lifelong learning
Exploring the associative learning capabilities of the segmented attractor network for lifelong learning Open
This work explores the process of adapting the segmented attractor network to a lifelong learning setting. Taking inspirations from Hopfield networks and content-addressable memory, the segmented attractor network is a powerful tool for as…
View article: Ultra-Low Power Schottky Barrier TFT-Based Neurotransmitter Detection and Regenerative Studies
Ultra-Low Power Schottky Barrier TFT-Based Neurotransmitter Detection and Regenerative Studies Open
There is limited work on understanding Schottky barrier (SB) field-effect transistor (FET) behavior, and subsequent evolution of sensitivity metrics under wet detection conditions for neurotransmitter sensing applications.In this work, we …
View article: Intrinsically Secure Non-Volatile Memory Using ReRAM Devices
Intrinsically Secure Non-Volatile Memory Using ReRAM Devices Open
The paper describes a device-level encryption approach for implementing intrinsically secure non-volatile memory (NVM) using resistive RAM (ReRAM). Data are encoded in the ReRAM filament morphology, making it robust to both electrical and …
View article: NeuroSOFM: A Neuromorphic Self-Organizing Feature Map Heterogeneously Integrating RRAM and FeFET
NeuroSOFM: A Neuromorphic Self-Organizing Feature Map Heterogeneously Integrating RRAM and FeFET Open
Many currently available hardware implementations of the unsupervised self-organizing feature map (SOFM) algorithm utilize complementary metal–oxide–semiconductor (CMOS)-only circuits that often compromise key behaviors of the SOFM algorit…
View article: Adversarial Attack Mitigation Approaches Using RRAM-Neuromorphic Architectures
Adversarial Attack Mitigation Approaches Using RRAM-Neuromorphic Architectures Open
The rising trend and advancements in machine learning has resulted into its numerous applications in the field of computer vision, pattern recognition to providing security to hardware devices. Eventhough the proven achievements showcased …
View article: A deep learning approach for lower back-pain risk prediction during manual lifting
A deep learning approach for lower back-pain risk prediction during manual lifting Open
Occupationally-induced back pain is a leading cause of reduced productivity in industry. Detecting when a worker is lifting incorrectly and at increased risk of back injury presents significant possible benefits. These include increased qu…
View article: Deep-subthreshold Schottky barrier IGZO TFT for ultra low-power applications
Deep-subthreshold Schottky barrier IGZO TFT for ultra low-power applications Open
View article: A Compact Gated-Synapse Model for Neuromorphic Circuits
A Compact Gated-Synapse Model for Neuromorphic Circuits Open
This work reports a compact behavioral model for gated-synaptic memory. The model is developed in Verilog-A for easy integration into computer-aided design of neuromorphic circuits using emerging memory. The model encompasses various forms…
View article: Unsupervised Clustering of COVID-19 Chest X-Ray Images with a Self-Organizing Feature Map
Unsupervised Clustering of COVID-19 Chest X-Ray Images with a Self-Organizing Feature Map Open
Machine learning approaches are gaining popularity in the medical field for diagnostics, predictive analytics and general research. With data often being unlabeled or sparse to collect, there is a need for unsupervised learning networks in…
View article: A CRISPR-Cas-Inspired Mechanism for Detecting Hardware Trojans in FPGA Devices
A CRISPR-Cas-Inspired Mechanism for Detecting Hardware Trojans in FPGA Devices Open
Hardware security has risen in prominence in recent years with concerns stemming from a globalizing semiconductor supply chain and increased third-party IP (intellectual property) usage. Trojan detection is of paramount importance for ensu…
View article: A CRISPR-Cas-Inspired Mechanism for Detecting Hardware Trojans in FPGA\n Devices
A CRISPR-Cas-Inspired Mechanism for Detecting Hardware Trojans in FPGA\n Devices Open
Hardware security has risen in prominence in recent years with concerns\nstemming from a globalizing semiconductor supply chain and increased\nthird-party IP (intellectual property) usage. Trojan detection is of paramount\nimportance for e…
View article: Detecting Malware Code as Video With Compressed, Time-Distributed Neural Networks
Detecting Malware Code as Video With Compressed, Time-Distributed Neural Networks Open
Malware is an ever-present problem in the modern era and while detecting malware with AI has grown as a new field of exploration, current methods are not yet mature enough for widespread adoption in terms of speed and performance. Current …
View article: Guest Editorial Nature-Inspired Approaches for IoT and Big Data
Guest Editorial Nature-Inspired Approaches for IoT and Big Data Open
Nature-inspired approaches have been widely used for different purposes over the last two decades and are still extensively researched, especially for complex real-world problems. Biological systems, or nature in general, serve as the sour…
View article: ARIA: Additive ReRAM-Based Integrity and Aging Monitoring for ICs
ARIA: Additive ReRAM-Based Integrity and Aging Monitoring for ICs Open
This paper reports an approach for monitoring aging and integrity of CMOS circuits through additively manufactured Resistive Random-Access Memory (ReRAM) based test structures. MgO-based ReRAM devices demonstrated excellent temperature sen…
View article: A Segmented Attractor Network for Neuromorphic Associative Learning
A Segmented Attractor Network for Neuromorphic Associative Learning Open
This work describes a segmented attractor network that records memories across different sets of information. Unlike typical attractor networks that can associate any given inputs with one another, the attractor network presented here trac…
View article: Effect of aluminum interfacial layer in a niobium oxide based resistive RAM
Effect of aluminum interfacial layer in a niobium oxide based resistive RAM Open
View article: Detecting Malicious Assembly using Convolutional, Recurrent Neural Networks
Detecting Malicious Assembly using Convolutional, Recurrent Neural Networks Open
View article: Gate-Controlled Memristors and their Applications in Neuromorphic Architectures
Gate-Controlled Memristors and their Applications in Neuromorphic Architectures Open
We discuss the theory of gated memristive devices, which exhibit continuous states over three orders of magnitude and can be programmed independently of reading. A model is generated by using knowledge of the device physics and fitting the…
View article: Multi-Bit Read and Write Methodologies for Diode-STTRAM Crossbar Array
Multi-Bit Read and Write Methodologies for Diode-STTRAM Crossbar Array Open
Crossbar arrays using emerging non-volatile memory technologies such as Resistive RAM (ReRAM) offer high density, fast access speed and low-power. However the bandwidth of the crossbar is limited to single-bit read/write per access to avoi…