activity
20202025
most citedAdaptive Extreme Edge Computing for Wearable Devices

175 citations · 213 across the 10 of their papers we have counts for

collaborators

10 papers

eess.SP2025

An Asynchronous Mixed-Signal Resonate-and-Fire Neuron

Giuseppe Leo, Paolo Gibertini, Irem Ilter +3

Analog computing at the edge is an emerging strategy to limit data storage and transmission requirements, as well as energy consumption, and its practical implementation is in its…

cs.ET2025

Defect-Aware Physics-Based Compact Model for Ferroelectric nvCap: From TCAD Calibration to Circuit Co-Design

Luca Fehlings, Nihal Raut, Md. Hanif Ali +4

Ferroelectric non-volatile capacitance-based memories enable non-destructive readout and low-power in-memory computing with 3D stacking potential. However, their limited memory win…

cs.ET2025

Millisecond-scale Volatile Memory in HZO Ferroelectric Capacitors for Bio-inspired Temporal Computing

Luca Fehlings, Thomas Mikolajick, Beatriz Noheda +1

With the broad recent research on ferroelectric hafnium oxide for non-volatile memory technology, depolarization effects in HfO2-based ferroelectric devices gained a lot of interes…

cs.ET2025★ 1 cited

Reliability of Capacitive Read in Arrays of Ferroelectric Capacitors

Luca Fehlings, Muhtasim Alam Chowdhury, Banafsheh Saber Latibari +2

The non-destructive capacitance read-out of ferroelectric capacitors (FeCaps) based on doped HfO metal-ferroelectric-metal (MFM) structures offers the potential for low-power a…

cs.NE2025

Bruno: Backpropagation Running Undersampled for Novel device Optimization

Luca Fehlings, Bojian Zhang, Paolo Gibertini +3

Recent efforts to improve the efficiency of neuromorphic and machine learning systems have centred on developing of specialised hardware for neural networks. These systems typicall…

cs.ET2022★ 9 cited

A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron

Paolo Gibertini, Luca Fehlings, Suzanne Lancaster +6

Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Ju…

physics.app-ph2022★ 10 cited

Improvement of FTJ on-current by work function engineering for massive parallel neuromorphic computing

Suzanne Lancaster, Quang T. Duong, Erika Covi +2

HfO2-based ferroelectric tunnel junctions (FTJs) exhibit attractive properties for adoption in neuromorphic applications. The combination of ultra-low-power multi-level switching c…

cs.ET2022★ 2 cited

A 120dB Programmable-Range On-Chip Pulse Generator for Characterizing Ferroelectric Devices

Shyam Narayanan, Erika Covi, Viktor Havel +7

Novel non-volatile memory devices based on ferroelectric thin films represent a promising emerging technology that is ideally suited for neuromorphic applications. The physical swi…

cs.ET2021★ 16 cited

Ferroelectric Tunneling Junctions for Edge Computing

Erika Covi, Quang T. Duong, Suzanne Lancaster +10

Ferroelectric tunneling junctions (FTJ) are considered to be the intrinsically most energy efficient memristors. In this work, specific electrical features of ferroelectric hafnium…

cs.ET2020★ 175 cited

Adaptive Extreme Edge Computing for Wearable Devices

Erika Covi, Elisa Donati, Hadi Heidari +4

Wearable devices are a fast-growing technology with impact on personal healthcare for both society and economy. Due to the widespread of sensors in pervasive and distributed networ…