Three-dimensional (3D) imaging has been widely used in academic research and industrial applications. Compared to 2D representations, 3D imaging can yield more information about geometric structures of an object such as small surface variations that are difficult to perceive otherwise. 3D image contents provide additional information that is complementary to...
In this dissertation, I combine quasi-experiments and computational tools with large-scale data in new ways to address questions that revolve around the Matthew Effect of status. My dissertation is a collection of four empirical papers on status at both the organizational and the individual levels. I employ two distinct empirical...
Carbonates constitute Earth's largest carbon (C) reservoir, with most shallow marine deposition occurring on the low-latitude carbonate platforms covering ~800,000 km2. The Yucatán Platform situated between the Western Caribbean and Gulf of Mexico basins, is one of the largest present-day carbonate platforms. As with post-Paleozoic carbonates generally, it is readily...
Speech recognition in complex acoustic environments is dependent on myriad bottom-up (i.e., peripheral) and top-down (i.e., central) processes. While bottom-up processes remain fairly stable during childhood, the development of top-down processes persists into young adulthood. The immaturity of top-down processes places younger children at considerable risk for poorer speech recognition...
Optimization via simulation (OvS) is the practice of minimizing or maximizing the expected value of the output of a stochastic simulation model with respect to controllable decision variables. Stochastic simulation is a standard tool within operations research and is often required to model complex systems subject to uncertainty where it...
Proper partitioning of mitochondria and mtDNA is critical for cellular health. Investigations into mitochondrial inheritance, specifically how mtDNA inheritance is coupled with the inheritance mitochondrial compartment, are still in the early stages. We use budding yeast as a model polarized cell system to study a mitochondrial Myo2-adaptor protein, Mmr1, in...
The study and design of machines that are able to analyze the auditory scene and organize sound into parts that are perceptually meaningful to humans is referred to as machine hearing. Such machines are expected to distinguish between different sound categories (e.g., speech, music, background noise), focus on a sound...
Intelligence in humans is largely characterized by the ability to encode information into compressible representations to facilitate efficient communication for collaboration and learning. The goal of this thesis is to enable robots to both learn and act on compressible representations in real-time. I show how active exploration with respect to...
While optimization has received much attention in the machine learning community, most of them consider unconstrained supervised learning models such as neural networks and support vector machine. In this dissertation, we introduce a new class of optimization problems called scale invariant problems that include interesting unsupervised learning models such as...
This thesis focuses on applications of recurrent neural networks (RNNs) for three aspects of sequential classification. In the first chapter, a novel method to generate synthetic minority data generation to improve imbalanced classification is discussed. Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic...