CS undergrad discovers calling down an unconsidered path
Abhishek Shah thought he wanted to be a doctor. He didn’t intend to study computer science; the extent of his programming knowledge was limited to basic HTML.
Then he had an “ah-ha” moment, and when what started as an exploration turned into pursuit of a passion.
Leaving his home in the western Indian state of Gujarat just after high school, Shah had an idea of what he wanted to study in college. He liked math and science, and had studied bioinformatics in high school. After arriving at MU, he pursued biomedical engineering to break into bioinformatics, thinking he would become a doctor or something else in the medical field.
“I talked about that with a biomedical professor, and he said if I wanted to study bioinformatics, I should look into computer science,” Shah said.
Though Shah said he hadn’t considered that discipline, he took his professor’s advice and registered for the introductory computer science courses. The real turning point was during CMP SC 2050: Algorithm Design and Programming II in his sophomore year. Shah suddenly became fascinated with the efficiency of computational programming.
“That class was the biggest threshold,” he said. “When I crossed it — that was when I realized the real potential of computer science. Everyone else hated it, but I loved it.”
The class was his “blessing in disguise,” as it not only helped define his path of study, but also opened his eyes to the future possibilities in computer science. Throughout the first eight months of 2012, Shah completed a co-op and an internship with two companies. From January through May, Shah’s co-op with Anheuser-Busch as a program manager intern gave him the experience of working to fulfill customer and/or another department’s needs.
“Let’s say the brewery department wanted a whole new system. My duties would be to go to that customer and find out what they required. I would build the design of the system that I envisioned, create a requirements document and a test plan, go to programming team and ask, ‘Can you implement this?’”
Shah then had the chance to learn the next step in this process when he worked as a software-programming intern for Cerner Corporation over the summer. During his three months there, he built a system that went live by the end of his tenure.
Back at MU and working with Professor Wenjun Zeng and doctoral student Suman Roy, Shah began research on a project that looks at Twitter trending data, something he calls “social media computing.”
In this project, Shah’s team is working on classifying Twitter trends, words, phrases, memes or topics that are used more frequently in posts at any given time. This is the first step in developing a program that can track trends geographically and in real time as they grow or decrease in popularity.
“Abhi is very passionate about undergraduate research, and has made great progress in his project,” Zeng said.
Using a “decision tree” model to classify words or phrases, Shah and his research team will construct an algorithm that will track the fluctuating trend patterns.
“The idea is that once your have all these categories built out, you an look at which categories are rising in popularity and from where,” Shah said. “Networks could take this data and see where people are talking about certain categories and know which markets to broadcast to.”
Research on this project began in the fall, and Shah said the team can begin generating data once categories start making classifications. At the moment, they are working on 10 categories, including entertainment, sports and politics.
“We’re trying to predict where people will start talking and what they will talk about,” he said, adding that the aspect of the psychology behind the project has added to his interest in it.
“When I get started talking about computer science, I just can’t stop,” he said.