1st Years

This project aims to enhance a research platform for creating and analyzing interactive, web-based data visualization studies by adding an eye-tracking analysis toolkit. Eye-tracking can help researchers understand where users focus, how they analyze problems, and how they make decisions while interacting with websites and data visualizations. However, analyzing gaze data often requires expensive commercial software. This project aims to address that challenge by developing an open and accessible toolkit for analyzing common gaze measures from recorded user studies. By simplifying gaze analysis, the toolkit could support the development of adaptive visualization systems that respond to users’ needs and difficulties.

Tags: Human Computer Interaction (HCI), Python, React, All Years

In this project, students will evaluate a recently proposed CDC algorithm and compare it against state-of-the-art techniques. Working in teams, students will use open-source implementations and real-world datasets to conduct benchmarking experiments and measure metrics such as chunking throughput, chunk-size distributions, and deduplication efficiency. Team members will focus on complementary tasks, including experiment design, dataset preparation, benchmarking, data analysis, and visualization. The primary goal during the program is to evaluate the algorithm and understand its strengths and limitations. Students who continue beyond the program may also explore integrating the algorithm into an open-source benchmarking framework and investigating further improvements to chunking techniques.

Tags: Systems, Algorithms, C/C++, Go, Python, All Years