Memory management and address translation need significant optimizations in order to not behindrances in the near future. Currently, plenty of work has started to address issues within the
current abstraction of the hardware-software codesign of paging. I argue that a new abstraction
is needed in order to properly address this...
Biological systems comprise diverse collections of cellular and non-cellular components with intricate relationships and dynamic interactions. To gain system-level understanding, we must be able to accurately model these systems, both experimentally and computationally. Agent-based models (ABMs) in particular are a uniquely intuitive, modular, and flexible framework capable of supporting multi-scale,...
The ever growing desire for accurate estimation and efficient learning necessitates the efforts to quantitatively characterize uncertainties for models. In this thesis, four problems pertaining to uncertainty quantification are discussed: A sequential stopping framework of constructing fixed-precision confidence regions is proposed for a class of multivariate simulation problems where variance...
The theory of how humans and machines control and communicate with each other is at the core of the scientific field known as Human-Robot Interaction (HRI). Researchers in this sub-discipline of robotics are therefore particularly interested in developing methods to chuppahreduce the inherent friction in this communication and control channel....
Asymmetric relationships between creators and consumers in peer-produced knowledge repositories produce inequitable knowledge representation--or knowledge gaps. These gaps result in unequal access to information, and downstream technologies that leverage peer-produced data perpetuate these inequities. Effective knowledge gap identification represents a necessary first step towards equitable knowledge representation. However, while prior...
From cyber theft of personal financial information to Advanced Persistent Threat (APT) attacks, nowadays endpoint devices suffer from various intrusions which cause inestimable property and privacy loss. To protect the security on endpoints, endpoint detection and response (EDR) systems have been developed to serve as the powerful solution against those...
Newcomers, or new members to organizations or professions, bring insights that are critical to the advancement of society. Yet newcomers often have low self-efficacy, or low beliefs in their abilities to achieve a task, which can impact performance and retention. Research suggests that self-efficacy can be developed through in-person social...
This dissertation combines perspectives from social networks and teams research to advance understanding of team self-assembly. Across three substantive chapters, I explore team member search behaviors and invitation patterns in contexts where individuals exercise agency to select team members. First, I consider the search for team members in a social...
Clustering is a fundamental task in unsupervised learning, which aims to partition the data set into several clusters. It is widely used for data mining, image segmentation, and natural language processing. One of the most popular clustering methods is centroid-based clustering, including k-medians and k-means clustering. k-medians and k-means clustering...
Responsiveness -- the time it takes for a message recipient to respond to a message -- has long been of interest to scholars in the fields of computer-mediated communication and human-computer interaction. It has been hypothesized that responsiveness is used to signal emotional information, and many empirical studies have demonstrated...