My Education Journey

I am currently a first-year student at UC Berkeley, studying Data Science and Economics. Some of the relevant courses I am taking include: Foundations of Data Science, Structure and Interpretation of Computer Programs, Multivariable Calculus, Introduction to Economics.

I am also a member of DataGood @ Berkeley, a student-run organization that provides data science consulting services to nonprofits and social enterprises.

My Extended Essay investigates the efficiency of two non-cryptographic hash functions (NCHFs), FNV-1a and MurmurHash3, in the context of hash table implementations. My research question explores how these hash functions compare in terms of collision resistance and time complexity. Through systematic experimentation, the study evaluates collision rates across various datasets and measures execution times for hashing, searching, inserting, and deleting operations. Results indicate that both NCHFs exhibit similar collision resistance, with average collision rates around 0.37. However, MurmurHash3 demonstrates superior performance in terms of time complexity, executing operations more efficiently than FNV-1a. My findings challenge the common misconception that hash tables can achieve O(1) efficiency for all operations, revealing significant collision rates and time costs.

My essay received a score of A.

I worked with Professor Brittany Murray from Davidson College on a research paper in 2024's summer. In this paper, we examine the implications of ability tracking in Hong Kong's education system, particularly through the lens of the Secondary School Places Allocation (SSPA) System. We explore the contentious debate surrounding ability tracking, which categorizes students based on perceived academic abilities, often leading to entrenched social inequalities.

Drawing upon theories of categorical inequality and labelling, we investigate how these systems may perpetuate disparities in educational opportunities and outcomes, especially for students from lower socioeconomic backgrounds. Through a proposed study comparing tracked and untracked classrooms, we aim to assess the impact of ability grouping on students' self-efficacy, teacher perceptions, and academic performance.

Ultimately, we argue that while ability tracking is not the root cause of social inequalities, it exacerbates existing disparities and hinders social mobility. This research seeks to contribute to the ongoing discussion about the need for equitable educational practices and the potential benefits of detracking in Hong Kong and beyond.