Combinatorial optimization problems are fundamental in many real-world applications, where the goal is to find the optimal or near-optimal solution to a problem subject to …
Autism is a developmental disability with variability in phenotypic features and genetic characteristics and affects 1% of children worldwide. Genetic and environmental factors are considered …
Inland waters (lakes, rivers, reservoirs, wetlands) are the largest natural source of the greenhouse gas methane, representing 40-50% of total emissions. Emission sources are characterized …
Electronic-structure calculations have provided us with in-depth understanding of chemical and physical phenomena in atomic and molecular scales. In particular, density functional theory has been …
In eukaryotes, DNA is first transcribed into precursor-messenger RNA (pre-mRNA) which is then followed by extensive RNA processing events. One such event is RNA splicing, …
In both supervised and reinforcement settings, there exist learning problems that are hard due to having high computational or sample complexity. Researchers have shown, using …
This dissertation is composed around the subject of multiscale modeling of soft matter and biophysical systems with applications using large-scale computations. Specifically, it is expanded …
Abstract of Neural Biomarker Based Parameter Optimization Using Deep Brain Stimulation for Parkinson’s Disease, by Pranav Akella, ScM., Brown University, May 2022. Introduction: Parkinson’s Disease …
Progress in deep feedforward neural networks has spawned great successes in many practical applications, but these models struggle to reproduce human-level generalization in tasks that …
This thesis presents the applications of phase field modeling in fracture analysis. In this method, a diffusive crack zone controlled by a scalar auxiliary variable …
Children with high-needs, including those with Autism Spectrum Disorder (ASD), require extensive medical, behavioral, and educational support due to their complex conditions. These challenges necessitate …
Prediction of Acute Kidney Injury in Hospitalized COVID-19 Patients Using Machine Learning, by David Carbonello, ScM., Brown University, May 2021 Many studies provide evidence that …
Objective: The overall goal of the study is to contribute to the development and use of artificial intelligence (AI) and machine learning (ML) for mental …
Advances in sequencing technologies in the last decade have enabled us to profile various genomic features at the single-cell resolution, such as gene expression and …
We propose a general-purpose probabilistic framework for scene understanding tasks. We show that several classical scene understanding tasks can be modeled and addressed under a …
In the age of big data, uncertainty in data constantly grows with its volume, variety and velocity. Data is noisy, biased and error-prone. Compounding the …
Educational assessments are crucial for both instructors and education researchers to measure learning, troubleshoot student problems, evaluate pedagogy, and improve education. Unfortunately, creating and administering …
We develop Bayesian nonparametric statistical models of document collections and social networks. Extending classic parametric topic models of documents, and stochastic block models of networks, …
