School of Computer Science Undergraduate Research Option Theses
The Research Option offers students majoring in computer science the opportunity for a substantial, in-depth research experience. Students are strongly encouraged at the end of their experience to work with their faculty mentor to develop a journal publication or conference presentation on the research in addition to the actual thesis.
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Recent Submissions
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Enumerating Acyclic Orientations
An acyclic orientation (AO) of an undirected graph is an assignment of direction to each of its edges without introducing a directed cycle. We study enumeration problems regarding AOs. Our results include: an explicit ... -
Automated Vulnerability Discovery in Botnet Command and Control Infrastructure
Systems infected with botnet malware often communicate with command and control (C&C) infrastructure, from which attackers can launch coordinated malicious attacks. Our research explores techniques for discovering ... -
Deterministic Volume Approximation of Polytopes
Computing the volume of a polytope is an important longstudied question, with applications ranging from combinatorics to machine learning. While there are numerous randomized algorithms that efficiently approximate the ... -
Penny – personal security assistant
This study presents Penny, a virtual assistant that monitors various parameters and conditions of the user’s machine and notifies them in case it senses a potential vulnerability. Penny also provides the user with ... -
CHORUS is Porous: Attacking Implementations of Differential Privacy
In this work I explore the vulnerability of CHORUS and FLEX, using a side- channel attack. CHORUS and FLEX are differentially private querying mecha- nisms jointly worked on by Uber and UC Berkeley. They aim to provide ... -
Single-Job Dynamic Parallelism Scaling through Lock Contention Monitoring
Harnessing available parallelism resources is an important but complicated task. Lock contention is one such factor that complicates this task and is of major concern, since locks and locking constructs are used heavily ... -
Snow Coverage Prediction using Machine Learning Techniques
Snow coverage is often predicted through analysis of satellite images. Two of the most common satellites used for predictions are MODIS and Landsat. Unfortunately, snow coverage predictions are limited either by MODIS ... -
Robot Calligraphy using Pseudospectral Optimal Control and a Simulated Brush Model
Chinese calligraphy is unique and has great artistic value but is difficult to master. In this paper, we make robots write calligraphy. Learning methods could teach robots to write, but may not be able to ... -
Quantifying Gerrymandering using Markov Chain Monte Carlo Algorithms
We look at the rules and regulations surrounding redistricting in the United State. We examine Markov Chain Monte Carlo algorithms that are able to sample redistricting plans adhering to these rules. We implement the ... -
Evaluating Off-Center Head-Worn Display
Several studies have highlighted the advantages of using mobile augmented reality systems to assist with various tasks over traditional paper-based methods. However, these interfaces are often located in users’ primary ... -
Stranger Danger: Educational Game for Cybersecurity Awareness
Cybersecurity is a concern for both organizations and individual users. Although there are a variety of security tools available, the number of cybersecurity incidents is still high. One cause of this phenomenon is that ... -
Semantic Mapping and Reasoning
Rich, yet efficient knowledge processing is one of the key problems in modern autonomous robotics. The Robot Autonomy and Interactive Learning (RAIL) Lab at the Georgia Institute of Technology has developed a new knowledge ... -
Improving Model-Predictive Control with Value Function Approximation
Existing Model Predictive Control methods rely on finite-horizon trajectories from the environment. Such methods are limited by the length of the samples because the robot cannot plan for scenarios beyond this time horizon. ... -
On Formula Embeddings in Neural-Guided SAT Solving
Branching heuristics determine the performance of search-based SAT solvers. We note that recently, Neural Machine Learning approaches have been proposed to learn such heuristics from data. The first step in learning a ... -
Review of Novel Communication Techniques for Autistic Individuals Using Eye-Gaze Tracking as an Indicator of Cognition
For the 1 in 68 individuals in the United States on the autism spectrum, the use of interactive tools and technologies has grown significantly over the past few years to augment daily living capabilities. For the subset ... -
Learning to Airbnb by Engaging in Online Communities of Practice
Technological advances, combined with sustained, minimalist consumerism, have raised the popularity of sharing economy platforms like Airbnb and Uber. These platforms are considered to have disrupted traditional industries ... -
Extracting information from gameplay videos using machine learning techniques and its varieties
The ability to extract sequences of game events for high-resolution e-sport games has traditionally required access to the game’s engine. This difficulty serves as a barrier to groups who don’t possess this access. It is ... -
The Impact of Lip and Jaw Movement in Virtual Reality Humanoid Avatars
Virtual reality (VR) developed as an immersive communication tool, where users are able to interact with each other through virtual avatars. Among the current VR applications with human avatars, most of them emphasize ... -
Material Classification with Active Thermography on Multiple Household Objects
Active thermography is a technique to inject heat into a target sample and observe the temperature change along time. Such a technique enables a robot to perform material classification with machine learning algorithms and ... -
FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or ...
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