As our world is increasingly filled with data visualizations, having the skills to leverage data visualizations is essential for participation in society. Confident engagement with data visualizations is critical for being an educated member of society; however, research has shown that it is difficult for individuals to digest and gain...
Polymer nanocomposites are a class of advanced materials comprised of soft polymer matrix and nano-filler inclusions. While it has been found qualitatively that enhancements of material properties could be achieved by dispersing inorganic nano-particles into organic polymer matrix, the intrinsic governing principles of such composite has not been thoroughly studied...
Connecting structure and function in nanoscale engineered materials and devices relies on the analysis of the fundamental arrangement of matter, frequently under dynamic conditions. The demand to image structures at fundamental length scales has touched inorganic materials, biology, and frequently hybrid hard/soft materials with unique phenomena driven by heterogeneous components....
In this dissertation, we study different machine learning algorithms including probabilistic, sparse and deep learning based models applied to multi-sensory datasets. In many machine learning problems, samples are collected from more than one source or modality. Also, various feature extraction methods can be used to provide more than one set...
The current view in neuroscience holds that the brain, together with its sensory and motor structures and the environment, form a closed-loop system – a sensorimotor loop – in which the brain receives information from the environment and converts it into a motor response while simultaneously making predictions about future...
Data mining is multidisciplinary process involving computer science, artificial intelli- gence, and machine learning. The aim of data mining is discovering knowledge from a vast amount of data. This process consists of a set of stages forming a pipeline. This pipeline process consists of multiple steps: 1) Finding the right...
This thesis studies Bayesian-robustness of algorithm design. The main perspective requires for a single fixed algorithm that its performance is an approximation of the optimal performance when its inputs are independent and identical draws (i.i.d.) from every unknown distribution which is an element of a known, large class of distributions....
Blockchains are an exciting new type of Peer-to-Peer (P2P) distributed systems, which enable parties to transact directly, and maintain the record of said interactions in a distributed manner. A unique feature of blockchains is their ability to maintain a consensus without requiring knowledge on the number of participants, nor their...
Memory management and address translation need significant optimizations in order to not behindrances in the near future. Currently, plenty of work has started to address issues within the
current abstraction of the hardware-software codesign of paging. I argue that a new abstraction
is needed in order to properly address this...
Biological systems comprise diverse collections of cellular and non-cellular components with intricate relationships and dynamic interactions. To gain system-level understanding, we must be able to accurately model these systems, both experimentally and computationally. Agent-based models (ABMs) in particular are a uniquely intuitive, modular, and flexible framework capable of supporting multi-scale,...