lzhang

Hometown: Fullerton, CA

Domain Emphasis: Urban Science

Double Major: Computer Science & Data Science

Data Science in Six Words: transforming information's forms, use, and understanding

A fan of computers from an early age, Louis learned to code in high school and showed up at Berkeley ready to dig in to computer science. Which he did. He took lab assistant jobs in computer science and student IT jobs and completed two software engineering internships. His internship experiences, along with Data 8, inspired him to add data science to his quiver.

“After my internships, I realized I wanted something different. I really fell in love with data science and decided to add the new major,” he said. “I really enjoy the work that data scientists do, from machine learning to facial recognition—technologies that we use every day—to finding which areas are statistically most in need of clean water. I like the hands-on approach and practical nature of data science. You can see the impact of your work almost immediately.”

“The major also brings up really important topics like the Human Contexts and Ethics requirement. With the power of data science, you can do a lot of good, but also potentially bad things with all that information. Our job as data scientists and human beings is to figure out where to draw that line.”

I like the hands-on approach and practical nature of data science. You can see the impact of your work almost immediately.

His first software engineering internship at Spin, a scooter-sharing company (now a part of Ford), led to his interest in Urban Science as a domain emphasis. At the time, Spin's product was dockless bike sharing. “I immediately became fascinated with the idea of changing the way we think about transportation by increasing the mobility of people in congested urban areas and restructuring the transportation infrastructure of a city,” he said.

“Taking the Urban Experience course opened my eyes to understanding the deep-rooted social and cultural landscapes of cities as well as their histories that make each of them unique from one another. Each city is shaped by different factors and people along different timelines, requiring a complex level of understanding from data scientists, geographers, and planners.”

This summer, he has a data engineering internship at Atlassian that integrates his background in computer science and data science. He’ll return to campus in the fall to finish up some coursework.

After that, he says, “I wouldn’t mind working for a non-profit or an NGO, or a company reshaping the landscapes of urban infrastructure, transportation, global tourism, and things like that.”