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Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

In the development of implantable bioelectronics, the establishment of efficient wireless RF links between implants and external nodes is crucial, providing substantial contributions to the advancement of medical diagnosis, therapies, and basic science. Im ...

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR bl ...

Deploying compute-intensive deep neural networks (DNNs) on resource-constrained end devices has become a prominent trend, enabling localized intelligence. However, efficiently deploying these DNNs at scale poses challenges. To address this, extensive resea ...

This thesis delves into the critical study of particle transport in matter, particularly emphasising its implications for machine protection at CERN's accelerator complex and facilities. To conduct studies of this nature, FLUKA and Geant4 stand out within ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

One challenge in designing RF wireless bioelectronic devices is the impact of the interaction between electromagnetic waves and host body tissues on far-field wireless performance. In this paper, we investigate a peculiar phenomenon of implantable RF wirel ...

2.5D Systems-on-Package (SoPs) are composed by several chiplets placed on an interposer. They are becoming increasingly popular as they enable easy integration of electronic components in the same package and high fabrication yields. Nevertheless, they int ...

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

Wireless data communication could improve the performance and reliability of biomedical implants used in fundamental neuroscience research by removing infection-prone transcutaneous cabling. The small size of common research animals like mice and rodents, ...

The wireless sensor nodes used for monitoring the condition of grid equipment always be powered by disposable batteries. However, it introduces disadvantages, such as inconvenient replacement, short lifespan, and envi-ronmental pollution, significantly imp ...

Low-Density Parity-Check (LDPC) decoder is among the power hungry building blocks of wireless communication systems. Voltage scaling down to Near-Threshold (NT) voltages substantially improves energy efficiency, in theory up 10x. However, tuning the voltag ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

Diversity Embedded Space-Time Codes

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Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Stability: a search for structure

Extensions of Peer Prediction Incentive Mechanisms

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Electromagnetic Radiation of Implantable Antennas

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

RAPNet: Resolution-Adaptive and Predictive Early Exit Network for Efficient Image Recognition

Bridging Monte Carlo worlds: a new framework for accelerator simulations applied on shielding and machine protection studies

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Radiation Patterns of RF Wireless Devices Implanted in Small Animals: Unexpected Deformations Due to Body Resonance

REMOTE: Re-thinking Task Mapping on Wireless 2.5D Systems-on-Package for Hotspot Removal

Deep Learning Generalization with Limited and Noisy Labels

Radiation Performance of Antennas Implanted in Small Animals for Neuroengineering

Self-powered transformer intelligent wireless temperature monitoring system based on an ultra-low acceleration piezoelectric vibration energy harvester

Low Power LDPC Decoding by Reliable Voltage Down-Scaling

Caching and Neutrality