Deep learning is a new area of machine learning research that allows deep neural networks composed of multiple processing layers to learn representations of data with multiple levels of abstraction. Deep learning has helped in achieving the objective of pushing machine learning closer to one of its original goals of...
Polymer nanocomposites have attracted great interest in recent years because of their potential as tailored materials with enhanced properties. Recent experiments have shown that polymer nanocomposites are able to achieve significant improvement in dielectrical, thermal, mechanical and other physical properties compared with their parent polymer systems. More importantly, these outstanding...
Platelets are circulating anucleate discs derived from megakaryocytes, and play major roles in hemostasis, inflammation, thrombosis, and vascular biology. Multi-phase culture systems for inducing in vitro platelet production from mature megakaryocytes have been explored to allow progenitor expansion, megakaryocyte maturation, and promotion of platelet formation and shedding. In this thesis,...
Cells are complex, autonomous machines that integrate many environmental cues to execute a desired response. Though this property makes cells versatile, it presents significant design challenges when, to treat diseases, we must alter cellular responses. To understand changes to the complex regulatory pathways that cause diseases, studies often investigate the...
Each neuron in the primary motor cortex (M1) is like a musician in an orchestra, contributing to a larger harmony under the constraint of a “neural manifold”—a geometric score describing the correlated signals produced by the neural musicians that drive movement. Despite the widespread recognition of the importance of M1...
In the late 2000’s, scientific studies in cultural heritage saw a great advancement in macro X-ray fluorescence (XRF) imaging of paintings. These images are used to generate elemental distribution maps, which aid in identifying chemical elements and paint pig- ments as well as their locations throughout the layers of the...
In this document, I demonstrate that: 1) Linear basis functions cannot outperform nonlinear ones to represent hand kinematics 2) Nonlinear autoencoders outperform PCA on the dimensionality reduction of hand kinematics, 3) Nonlinear autoencoders outperform PCA in human gait representation and recurrent nonlinear autoencoders can seamlessly express the temporal dynamics, 4)...
In 2009, the Health Information Technology for Economic and Clinical Health Act (HITECH) promoted national use of electronic health records (EHR) in the US by giving incentives to providers who adopt ‘meaningful use’ of EHRs. As of 2017, nearly 86% of office-based physicians had adopted EHRs. EHRs have rich information...
In recent years, machine learning on graphs (or networks) has gone from a niche topic with only a few active researchers worldwide, to a heavily invested field with novel use cases for dealing with relationships and/or interactions within complex systems in the natural and social sciences. Traditionally, choosing the right...
Mixing by cutting-and-shuffling (like that for a deck of cards or a Rubik's cube) is a paradigm that has not been studied in detail even though it can be applied in a variety of situations including the mixing of granular materials. Mathematically, cutting- and-shuffling is described by piecewise isometries (PWIs),...