We live in an increasingly computational world; one that, in the near term, may require everyone to be computationally literate. Computer science (CS) education has greatly increased its reach in the last two decades with an increasing number of students having access to formal computer science classroom experiences in the...
The dissertation builds on my current research to demonstrate the connection between affect and learning through machine learning and qualitative analysis of interactions where players use a complex systems game. The project is threefold: First, I developed a thinking and learning intervention, the agent-based modeling simulation Ant Adaptation. I showed...
Recent developments in deep learning have led to breakthroughs in rendering novel views from sparse input views of a scene.While the accuracy of these algorithms has improved dramatically, it has come at a huge computational cost.
While developments in graphics hardware have ameliorated some of the computational burdens, deep learning-based...
This thesis studies Bayesian-robustness of algorithm design. The main perspective requires for a single fixed algorithm that its performance is an approximation of the optimal performance when its inputs are independent and identical draws (i.i.d.) from every unknown distribution which is an element of a known, large class of distributions....
In this thesis, we aim to develop efficient algorithms with theoretical guarantees for noisy nonlinear optimization problems, with and without constraints, under various different assumptions. Apart from Chapter 1 which provides relevant backgrounds, the remaining of thesis is divided into four chapters. In Chapter 2, we establish the theoretical convergence...
Over the past decade as smartphones and wearable tracking devices have grown in popularity, more individuals have begun collecting their own health and behavioral data. Innovations in sensor technology now allow individuals to continuously collect data over long periods of time with minimal effort. As a result, more data has...
This research looks at the robotic shape formation problem, which is one of the fundamental problems in robotic swarm systems. Here, the task is to move a group of robots to form a user-specified shape. In this dissertation, the task of shape formation is divided to four problems: (i) using...
Manufacturing processes are known for their intricacies in changing material shapes and properties. New generations of manufacturing technologies, known as flexible manufacturing, are moving toward design freedom, which allows producing parts with optimized geometries and high customizations at an affordable cost even for low-volume productions. Two prominent flexible manufacturing processes...
Human language processing is incremental. In this dissertation, I explore how an incremental perspective can help us clarify our understanding of transformational syntax, which typically proceeds bottom-up. As part of our exploration, I develop an incremental head-driven parsing algorithm for Minimalist Grammars. The two main innovations of this parsing algorithm...
Security and robustness are two critical problems in modern computing system. In this disserta- tion, we study these two problems in both hardware system and learning system.Firstly, we discuss the robustness problem in hardware system. Modern microprocessors suffer from significant on-chip variation at the advanced technology nodes. The development of...
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...
Motivated by real-world problems in various fields, mechanism design governs the design of protocols for strategic agents and has applications both in computer science and economics. Due to the revelation principle – a seminal observation in mechanism design, a vast number of studies in mechanism design focus on revelation mechanisms...
Cardiovascular disease is the leading cause of death in US and non-invasive cardiac imaging has vital importance for early detection and diagnosis of heart disease. Cardiac Magnetic Resonance (CMR) is arguably the most versatile imaging modality and capable of a comprehensive evaluation of heart disease without ionization radiation. Despite the...
When first-year students begin college they are thrown into a new environment where they are expected to simultaneously perform academically, form new relationships, and become independent. Many students struggle with this transition; experiences of stress, anxiety, and depression are common. For the majority of residential college students this is their...
Location-aware technologies, such as personal navigation applications, location-based AR games, and artificial intelligence systems that learn from data about places, increasingly mediate our understanding of and interactions with the world. However, a number of risks associated with location-aware technologies have emerged, jeopardizing the welfare of its users. This dissertation seeks...
Data Science and related fields like Artificial Intelligence, Machine Learning, and Statistics provide indispensable research methods for understanding a wide variety of phenomena from large datasets. However, as methodical and empirical as these methods aim to be, there are many subjective and discretionary choices that the data scientist must make...
Our experience of the physical world is mediated by our senses, but while most people have five senses, interactions with computer systems are largely limited to the visual sense. When working with nonvisual artifacts, like sound, on computers, such artifacts are typically transformed, or re-encoded, into something visual. Determining how...
In conventional data federations, a set of data providers each possess an autonomous database and collectively make the union of these databases available for querying by a client from a unified SQL interface. This setting however, provides no guarantees on data privacy or security. With my work, I consider a...
This dissertation asks how researchers can create more equitable algorithmic systems. Ultimately, this thesis explores methods and implications of representing subjects of analysis in the design and evaluation of algorithmic systems. I also unpack how algorithmic tools measure and quantify human behavior, giving heed to the potential impacts of these...
Computational imaging (CI) is a class of imaging systems that optimize both the opto-electronic hardware and computing software to achieve task-specific improvements. Machine/deep learning models have proven effective in drawing statistical priors from adequate datasets. Yet when designing computational models for CI problems, physics-based models derived from the image formation...