Hi! I'm a Computer Science graduate student at the University of Wisconsin-Madison with experience in algorithm design, data engineering, and human-centered research. I am eager to develop my skills further and contribute to innovative projects in these exciting fields!
HRI Research Project
Non-Linguistic Utterances (NLUs) are crucial in both human-human and human-robot interactions. We explored how specific audio qualities affect the perception of emotional arousal and pleasure. A novel generative algorithm was designed to express various emotions using musical and prosodic parameters. An end-user evaluation had participants interpret NLUs representing excitement, contentment, sadness, and anger. The study revealed that participants consistently associated excited, sad and angry NLUs with significantly different emotional states but not for content NLUs. Results are published in the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI '24).
★Features:
★Skills: Python, C++; Numpy, Matplotlib, Pandas, Scikit-learn, nltk, statsmodels, seaborn.
AI and ML Research Project
What is the maximum number of edges u(n) that a unit distance graph (UDG) of n vertices can have, as asked by an unsolved problem of Paul Erdős? We address the problem of determining the maximum number of edges in a UDG of n vertices using computer search. We seek to demonstrate a computer algorithm to generate dense UDGs for vertex counts up to at least 100. Via beam search with an added visitation metric, our algorithm finds all known maximally dense UDGs up to isomorphism at the push of a button. In addition, for 15 < n, where u(n) is unknown, i) the algorithm finds all previously published densest UDGs up to isomorphism for 15 < n ≤ 30, ii) the rate of growth of u(n)/n remains similar for 30 < n. iii) we build a database of over 60 million UDGs found by our algorithm. The preprint of the paper is available on arXiv.
★Features:
★Skills: Python; Numpy, Matplotlib, Pandas, Scikit-learn, Multiprocessing.
Computational Mathematics Research Project
Eigenmaps are important in analysis, geometry, and machine learning, particularly in nonlinear dimension reduction. This project investigates the relationship between eigen-coordinates of graph Laplacians and Chebyshev polynomials. We will consider constructing graph Laplacian operators on $[-1,1]$, $[-1,1]^2$, the sphere $S^2$, and the Sierpinski gasket. We also have explored these operators when the points are selected randomly with various distributions, such as uniform and Gaussian. We have developed algorithms capable of generating eigenmap plots for the aforementioned sample spaces. In our next step, we would also like to compare the eigen-coordinates of graph Laplacian operators constructed from those intervals with families of orthogonal polynomials, such as the Hermite polynomials and possibly exceptional orthogonal polynomials. The paper is available on the UConn REU website.
★Features:
★Skills: Python, MATLAB; NumPy.
This project involved building computer visualizations to showcase surfaces and geodesics in the disk model of the hyperbolic plane, using the Hyperbolic Canvas JavaScript library. It enhanced my understanding of hyperbolic geometry and allowed me to design extensions to improve existing programs.
This project explores the decomposition of a composite number into smaller integers. It discusses several algorithms like trial division, wheel factorization, and Pollard's p-1 factorization, comparing their efficiencies and discussing the theoretical limits of these methods.
Hole-in-One is a 2D simulation game where players compete to launch their ball into a hole. The game features a variety of obstacles and interactable terrains, challenging players to think strategically to succeed.