While artificial intelligence (AI) has led to major breakthroughs in many domains, understanding machine learning models remains a fundamental challenge. How can we make AI more accessible and interpretable, or more broadly, ...

This dissertation explores embodied agents that can improvise with people in an object-based gestural proto-narrative domain. I study the improvisational action selection problem (the challenge of performing action selection ...

Statistical mechanics bridges the fields of physics and probability theory, providing critical insights into both disciplines. Statistical physics models capture key features of macroscopic phenomena and consist of a set ...

Inter-human interaction is a rich form of communication. Human interactions typically leverage a good theory of mind, involve pragmatics, story-telling, humor, sarcasm, empathy, sympathy, etc. Recently, we have seen a ...

Open-source software (OSS) has been widely adopted in all layers of the software stack, from operating systems to web servers and mobile apps. Despite their myriad benefits, careless use of OSS can introduce significant ...

There is a growing international movement to provide every child access to high-quality computing education. Despite the widespread effort, most children in the US do not take any computing classes in primary or secondary ...

In response to the growing need for securing user data in the cloud, recent Intel processors have supported a new feature, Intel Software Guard Extensions (SGX). SGX allows a program to execute in isolation from the rest ...

Recent advances in neuroimaging have enabled major progress in the field of brain connectomics, i.e., constructing maps of connections between brain regions at different scales. Diffusion MRI (dMRI) and probabilistic ...

As modern attacks become more stealthy and persistent, detecting or preventing them at their early stages becomes virtually impossible. Instead, an attack investigation or provenance system aims to continuously monitor and ...

In this work we propose a new approach to the object detection problem using Deep Neural Network, in the context of traffic sign detection. Our approach simplifies the detection head complexity by making the requirement ...