Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
Research Objective: Nearly 60 million people in the United States reside in a rural area. Residents in rural areas have higher rates of chronic disease, risky health behaviors, disability, infant mortality, and age-adjusted mortality than their urban counterparts. Health insurance and access to care mitigate those risks, in part because...
Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
Converting energy from ocean waves is a challenging area for control theory application because of the nonlinear dynamics in various time scales. Generally, wave energy converter (WEC) control is applied in order to maximize power absorption, in the most common wave conditions, and subject to the devices’ physical constraints. Commonly,...
In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
Porous media are the materials containing void space or pores, where fluids and gases can pass through. Unsteady flows in porous media are encountered in many engineering applications and natural problems, such as CO₂ sequestration, high temperature nuclear reactor cooling, high efficiency combustion, chemical reactors, noise reduction on airplane trailing...
Transportation systems are facing safety and operational challenges with a cost of billions of dollars annually in lost production time and wasted fuel. Infrastructure expansion, previously held as a panacea to most transportation challenges has lost its appeal due to financial, land-use and environmental constraints. Interest is surging in intelligent...
Particle-laden turbulent flows, wherein a large number of small size particles are dispersed in a fluid, are widely encountered in environmental and industrial applications. Understanding their underlying physics, making predictions without performing expensive experiments, and ultimately optimizing the systems carrying such flows, require accurate and robust modelling tools. The Euler-Lagrange...
The rising global trend to reduce dependence on fossil fuels has provided significant motivation toward the development of alternative energy conversion methods and new technologies to improve their efficiency. Recently, oscillating energy harvesters have shown promise as highly efficient and scalable turbines, which can be implemented in areas where traditional...
It is desirable for complex engineered systems to perform missions efficiently and economically, even when these missions' complex, variable, long-term operational profiles make it likely for hazards to arise. It is thus important to design these systems to be resilient so that they will actively prevent and recover from hazards...