Short Biography

I am a recent graduate of UC Irvine, holding a Bachelor's in Computer Science. I am currently preparing applications for fellowships and Ph.D. programs for Fall 2027 admission, with a focus on Computing Education Research, Human-AI Interaction, and Algorithm Design. In my free time, I periodically interact with the arts, humanities, and social sciences to widen my perspectives, understand the human condition, and express myself. My main goal in life is to progressively close the gap between the two cultures, advocating for institutions to mindfully incorporate perspectives from arts, humanities, and social sciences to inform scientific practices and innovations. But most of all, I want to foster a sense of self-determination and belonging in education not bound by rigid curriculums or careers, where students have the autonomy and agency to carve their own pathways in computing. Feel free to shoot me an email if you would like to collaborate/connect with respect to my research, ask questions about my work, or provide suggestions for future projects.

Research Interest Summary

Computing Education

For years, I struggled to reconcile cultural norms in computing with my personal goals — I quickly realized software engineering was not for me, but found a dearth of support systems for students who might want to pursue non-technical, perhaps interdisciplinary, careers. These experiences have motivated my interest in discovering and alleviating barriers to success, both individual and societal, in computing, especially for students considering divergent, non-normative pathways. How do psychological factors — such as sense of belonging, self-efficacy, and impostor syndrome — manifest in these computing students? My goals focus on uplifting and incorporating student perspectives through qualitative research to better serve students in ways tailored to their own interests within computing. What norms reinforce the software engineering career pipeline, and does this potentially discourage students from studying other areas that might be perceived as less relevant to a software engineering career, such as theoretical computer science, art, or literature? How can we promote sense of belonging among computing students who prefer non-technical or interdisciplinary careers? I intend for my research in this area to understand how we can foster curiosity, promote excitement, and broaden participation in computing to empower students with autonomy and agency.

Human-AI Interaction

In the first year of my undergraduate studies, I wrote a paper analyzing how in the world of Fahrenheit 451, an excessive dependence on technology stripped humans of their individuality, curiosity, and sociality, turning them into mindless cogs in a machine. I believe the rapid development of generative AI poses a similar threat if left unchecked — generative AI has emerged as an incredibly disruptive technology, one that has influenced how we communicate, learn, and work in many facets of life. I've observed online communities slowly dying, discussions about whether generative AI "belongs" in certain spaces, and fears about being obsolete. For that reason, it is important to understand how humans are adapting and responding to its integration, especially in educational and artistic spaces. Do artists, teachers, and writers see it as a productivity tool or as a threat to their continued livelihoods? How can we foster AI literacy among students to use generative AI in ways that support, rather than hinder, their learning? How do individuals and communities perceive and respond to the influx of AI-generated content online? To minimize harm, the design of generative AI must incorporate the perspectives of those personally affected by it to ensure responsible integration that preserves human capabilities and communication.

Algorithm Design

While I am broadly interested in computer science theory as a whole, I have taken a particular interest to designing algorithms made for specific input cases and computing paradigms. For example, if we know that our input array is nearly sorted, algorithms like Insertion Sort can achieve better performance than algorithms like Merge Sort. I am interested in designing algorithms that abide by similar principles — given these restrictions about our input or allowed resources, can we design an efficient algorithm that works better than a general, all-purpose algorithm and verify its performance experimentally? I am also interested in understanding how we can utilize alternative computing paradigms, such as parallel or quantum computing, to provide better performance beyond what a classical, single-processor algorithm is capable of. However, for me, it's not enough to simply design the algorithm and prove its runtime and correctness — I believe that it's important to describe the process and explain the mechanisms to other individuals in an easily digestible manner, to effectively communicate the insights that motivated to the discovery, in ways that elevate our understanding of the problem.

Education

University of California, Irvine

B.S. in Computer Science | Sep 2022 – Mar 2026
Campuswide Honors Collegium, ICS Honors Program
Thesis: Help-Seeking Behaviors in Algorithms Courses
Advisor: Michael Shindler