Neurons, specialized cells that transmit nerve impulses, have long been known to be a vital element for the functioning of the human brain. Over the past century, however, neuroscience research has given rise to the false belief that neurons are the only cells that...
Machine learning & AI
A system for swarm robotics applications inspired by pheromone communication in insects
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...
DIGIT: A high-resolution tactile sensor to enhance robot in-hand manipulation skills
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,...
An AI painter that creates portraits based on the traits of human subjects
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...
A hyperdimensional computing system that performs all core computations in-memory
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...
A scheme to enhance how swarm robots search for multiple targets
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...
FoolChecker: A platform to check how robust an image is against adversarial attacks
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...
A deep reinforcement learning framework to identify key players in complex networks
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...
A method to protect audio classifiers against adversarial attacks
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...
A statistical model of cognitive status for natural language generation
In order for robots to be used in a wide variety of settings, they need to be able to communicate seamlessly with humans. In recent years, researchers have thus been developing increasingly advanced computational models that could allow robots to process human...