This thesis presents the techniques we have developed in analyzing brain signals obtained from the most commonly used brain imaging methods, e.g., EEG/MEG and fMRI …
Information retrieval (IR) has become a ubiquitous technology for quickly and easily finding information on a given topic amidst the wealth of digital content available …
The premise of the emerging field of computational psychiatry is to use models from computational cognitive neuroscience to gain deeper insights into mental illness. In …
This thesis takes aim at two directions. The first direction involves setting the foundations for a new type of data-driven scientific computing, essentially creating a …
An essential step in the development of a cortical auditory neural prothesis (ANP) is the development of a reliable method for reconstructing acoustic stimuli from …
In addition to the public health crisis instigated by COVID-19, the pandemic generated a set of structural and conceptual problems for social researchers to unpack …
This thesis develops novel algorithms to automate video analysis for fixed monocular surveillance cameras. Specifically, change detection algorithms are proposed to identify spatio-temporal locations in …
Advancements in machine learning techniques have encouraged scholars to focus on convolutional neural network (CNN) based solutions for object detection and pose estimation tasks. Most …
When developing a new heuristic or complete algorithm for a constraint satisfaction or constrained optimization problem, we frequently face the problem of choice. There may …
We analyze the self-rated health (SRH) of women in Cebu, Philippines. In three surveys conducted between 2002 and 2007, each woman in the study cohort …
Magnetic resonance (MR) has expanded over the past few decades into exciting new applications that have advanced the diagnosis, evaluation and treatment of many diseases. …
The trapeziometacarpal (TMC) joint, responsible for much of the thumb’s mobility, is commonly affected by osteoarthritis (OA), especially in older female populations. This has extensive …
We worked to develop an analysis system that can process and classify large data sets of audio, specifically infant cries. This clinical project focuses on …
Many applications in Computer Vision and Machine Learning entail learning from partially annotated data. A popular family of models that can capture unobserved variables in …
Cancer results from an evolutionary process where somatic mutations occur and accumulate in a population of cells. There are many types of mutations that can …
Intracortical brain computer interfaces directly link the brain to external devices. When a person attempts to move, electrodes inserted into the motor cortex can record …
We develop new algorithms for training nonparametric clustering models based on the Dirichlet Process (DP), including DP mixture models, hierarchical Dirichlet process (HDP) topic models, …
In this paper, we introduce a novel framework for improving intent classification performance in domains with limited labeled data. We call our framework RIPPED: Recursive …
Statistical models of non-rigid deformable shape have wide application in many fields, including computer vision, computer graphics, and biometry. We show that shape deformations are …
The top quark is one of the most important Standard Model particles in probing new physics beyond the Standard Model. Experimentally, this exploration can be …
We consider autonomous robots as having associated control policies that determine their actions in response to perceptions of the environment. Often, these controllers are explicitly …