Increases in the quantity of available data have allowed all fields of science to generate
more accurate models of multivariate phenomena. Regression and interpolation become …

Performance variability is an important measure for a reliable high performance computing
(HPC) system. Performance variability is affected by complicated interactions between …

Time-driven and access-driven attacks are two dominant types of the timing-based cache
side-channel attacks. Despite access-driven attacks are popular in recent years …

Performance variability is an important factor of high-performance computing (HPC)
systems. HPC performance variability is often complex because its sources interact and are …

Typical cybersecurity solutions emphasize on achieving defense functionalities. However,
execution efficiency and scalability are equally important, especially for real-world …

Variability in the execution time of computing tasks can cause load imbalance in high-
performance computing (HPC) systems. When configuring system-and application-level …

This thesis presents machine-learning based malware detection and post-detection
rewriting techniques for mobile and web security problems. In mobile malware detection, we …

Function approximation is an important problem. This work presents applications of
interpolants to modeling random variables. Specifically, this work studies the prediction of …

Many fields of science rely on the collection of samples and estimation of true population
distributions from those samples. There are several effective nonparametric methods for …

In this thesis, two distinct problems in data-driven computational science are considered.
The main problem of interest is the multiobjective optimization problem, where the tradeoff …