MS-DAS Student Aims To Change the Face of Programmers

Cleft lips and palates are the most common facial malformation of newborns and affect more than an estimated 200,000 infants globally. Without reconstructive surgery, infants can be at risk for problems eating and breathing and have speech or language delays.

Carnegie Mellon University master’s student Gayatri Chabra wants to join the community of researchers studying cleft palates in utero.

“Data science can play a huge role in building interactive models to detect abnormalities, and make treatment more accessible,” she said.

Chabra, a master’s student in Carnegie Mellon’s Data Analytics for Science program, was born with a cleft lip and a cleft palate. She underwent a series of operations and medical challenges and has always longed to be part of a solution for families impacted by this birth anomaly.

“This work requires statistical means and decoding the DNA sequence. I believe my studies will prepare me to develop algorithms and build data science models. That’s why I need this program at CMU,” she said.

Chabra is trying to pack in all the learning and experience she can, aiming to work in industry and build her own skills in data analytics. A graduate of the University of Delhi’s Jesus and Mary College with a bachelor’s degree in mathematics, she is excited to combine her love of the discipline with her passion for biomedical research.

The college was an all-girls environment, Chabra said she was awed by the powerful woman all around her.

“It’s so motivating,” she said. “You feel like doing so much more.” One upper class student created a math newsletter for the whole college, breaking down concepts in articles that were interesting for the entire student body. Chabra was inspired by a project that made students interested in learning more about her favorite subject.

“I immediately got involved and was eventually promoted to editor-in-chief of the newsletter,” she said.

The extracurricular project grounded Chabra at a time when she was struggling with pure and abstract math. She said she craved something she could apply practically in the real world and began looking at other fields. She discovered data analytics and data science, built upon linear algebra, statistics and probability — math concepts she loved. As Chabra completed internships, she reached out to graduate programs around the world.

Carnegie Mellon’s MS-DAS program stood out to her because of the diverse backgrounds of the enrolled students. Degree candidates come to the one-year program with backgrounds in disciplines such as biology and other foundational sciences in addition to engineering and, in Chabra’s case, mathematics.

“Students come to the MS-DAS program with a broad range of talent,” said Manfred Paulini, the MCS associate dean for research, MS-DAS executive director and a professor of physics. “Gayatri is exactly the type of student we strive to enroll. She is not only academically strong but more importantly somebody who cares about others around her. She will use the data analytic tools and machine learning skills acquired in MS-DAS to keep solving societal problems.”

Before she even enrolled, Chabra said she learned that some of the master’s degree candidates volunteer with a Pittsburgh chapter of Girls Who Code. The combination of service, fostering a community of women in STEM, and the MS-DAS curriculum sealed the deal, she said.

“We need more women in STEM, and Girls Who Code aims to close the gender gap in technology. To essentially change the image of what a programmer looks like and does,” Chabra said.

Middle school girls enrolled in the program learn to code in Python over the course of a semester. Chabra helped teach loops and tables, emphasizing project management and presentation skills along the way. Teaching young girls the basics of programming benefitted Chabra’s own studies.

“They tend to ask questions from a fresh perspective and I hadn’t paid attention to those nitty gritty details before. It was a good learning experience for me as well,” she said.

Her professors in the MS-DAS program agree.

“Gayatri was an inquisitive, goal-oriented, and highly capable student in my Computational Linear Algebra course in the Fall of 2023,” said Jason Howell, a teaching professor in Carnegie Mellon’s Department of Mathematics. “I was very impressed with her commitment to learning, and she excelled at all aspects of the course.”