Nature is one of the most valuable sources of inspiration for researchers developing new robots and computational techniques. Over the past few decades, technological advances have enabled the creation of increasingly sophisticated systems replicating naturally...
To assist humans in completing manual chores or tasks, robots must efficiently grasp and manipulate objects in their surroundings. While in recent years robotics researchers have developed a growing number of techniques that allow robots to pick up and handle objects,...
URu2Si2 is a metal that belongs to the family of heavy-fermion compounds in which several quantum phases (e.g., magnetism and superconductivity) can compete or coexist. These metals exhibit small energy scales that are easy to tune, a characteristic that makes them...
Solar cells made of semi-transparent photovoltaic (PV) materials typically have a fixed optical transmission, which results in either high transparency or high efficiency, but rarely both. In order to perform optimally when integrated on buildings, however, they...
Over the past decade or so, researchers have been developing increasingly advanced artificial intelligence (AI) systems for a wide range of applications. This includes computational techniques that can interact with humans, analyze large quantities of data, identify...
Hyperdimensional computing (HDC) is an emerging computing approach inspired by patterns of neural activity in the human brain. This unique type of computing can allow artificial intelligence systems to retain memories and process new information based on data or...
Over the past decade or so, researchers have been trying to develop techniques that could enable effective collaborative strategies among teams of robots. One of the tasks that teams of robots could complete better than individual robots is simultaneously searching...
Deep neural networks (DNNs) have so far proved to be highly promising for a wide range of applications, including image and audio classification. Nonetheless, their performance heavily relies on the amount of data used to train them, and large datasets are not always...
Network science is an academic field that aims to unveil the structure and dynamics behind networks, such as telecommunication, computer, biological and social networks. One of the fundamental problems that network scientists have been trying to solve in recent years...
In recent years, machine learning algorithms have attained remarkable results in a variety of tasks, including the classification of both images and audio files. A class of algorithms that has proven to be particularly promising are deep neural networks (DNNs) that...