Maggie Zhang - Data Science & Machine Learning @ UCSD

Intro & Research Interests

Hey there, I'm Maggie Zhang, a senior at UC San Diego. I’m fascinated by the intersection of technology, human cognition, and language, and I’m currently double majoring in Data Science and Cognitive Science (Machine Learning specialization) with a minor in Linguistics.

My journey into data science actually started with mathematics. I loved the logic of equations and uncovering hidden patterns, and my perspective shifted when I realized that linguistics offered the exact same analytical challenge. To me, linguistics is simply the structure of math applied to language, using words and syntax instead of numbers and variables to represent those hidden patterns. After placing in the top 20 at the North American Computational Linguistics Open, I became enraptured by how we can take something as fluid and natural as language and break it down into structured, mathematical theories. In college, this passion expanded into the philosophy and neuroscience aspects of cognitive science: What makes an entity capable of free thought? Is it the physical flesh of the brain, the confines of a metal GPU, or the electrical currents passing between them? Can we teach machines to understand language the same way children do?

Today, my research interests sit right at this intersection of AI and computational linguistics. Whether I'm benchmarking automatic speech recognition models or investigating how top-down language models parse syntax compared to human phonetic processing, I am deeply driven to find the signal in the noise. I love exploring the gap between how humans and machines process the world, constantly looking for ways to bridge structured algorithms with unstructured human behavior.

Professional & Academic Background

My background spans AI engineering, finance, industry data science, and a sprinkling of bioinformatics. I thrive in environments where I can build end-to-end ML solutions, handling everything from data mining and pipeline modularization to predictive forecasting and high-level business strategy.

In professional settings, my goal is to translate complex, fragmented data into scalable models that drive actionable decisions. From architecting AI-driven financial forecast dashboards to engineering machine learning algorithms for renewable energy site selection, I enjoy tackling open-ended problems with real-world impact.

Currently: Working as a Data Science Intern in the Finance Department at AGCO! Loving the work on finance & retail forecasting and providing business insights from different angles for the goal of putting Farmers First.

Beyond the Data

In my free time, I'm a huge culinary enthusiast who treats cooking a lot like programming: I love expanding my collection of high-end cookware and optimizing time-consuming dishes. Beyond that, I'm also an avid speedreader, finishing around 100 million words (about 1000 average-length books) in 2025 and averaging 1200 wpm overall. Notably, I finished all of Great Expectations by Charles Dickens in a single afternoon after school in preparation for an exam.

Otherwise, you can find me working on a knitting project, hitting the gym, or playing poker and majiang—because there is no better way to apply statistics and probability theory than at the card table.

Blog posts, project gallery view, and more features coming soon!