Student Profile: Cathy Chen ‘18 uses machine learning to understand the brain

Thursday, Sep 20, 2018
by Sharon Adarlo

Cathy Chen, 22, Class of 2018:

Studies:

Chen earned her bachelor’s degree in computer science and earned three certificates: the Center for Statistics and Machine Learning’s Certificate in Statistics and Machine Learning, and certificates in applied and computational mathematics, and neuroscience. She graduated summa cum laude.

For the fall, Chen will be performing research on machine learning and neuroscience as a Fulbright Scholar in Germany, first at Ludwig Maximilian University of Munich and then at the Max Planck Institute for Intelligent Systems in Tübingen.

Next year, she is slated to start the doctoral program in the electrical engineering and computer sciences department at the University of California, Berkeley, where she hopes to continue her research from Princeton.

Research:

During her years at Princeton, Chen developed an interest in the interface between machine learning and neuroscience.

For her independent project for her CSML certificate, Chen looked at the fMRI scans of people who watched an episode of the tv show Sherlock. Working with other members of the Norman lab, she would split the episode into 25 different scenes, use data from scans of the neural activity of volunteers, and decode what they were watching by looking at the scans. She used machine learning techniques to examine neural data.

She specifically worked on a more interpretable model for combining what was happening in the brain at the present and what happened in the past in order to decode what the subject was watching.

“When you watch a movie, your thoughts about a movie at a certain time are also influenced by actions that happened previously in the movie, and we wanted to understand that in our model” she said.

Her thesis project involved training neural networks to learn schemata and apply them in specific situations. Schema is a concept in psychology that describes a framework for how things should work in the world or a structure of ideas. An example would be going into a restaurant and knowing to stand at the front desk to wait for a table from a schema governing how restaurants work.

In the future, Chen said she would like to apply her knowledge towards a potential academic career.

Extracurricular activities:

Chen played violin in Princeton’s Sinfonia, was a member of the Data Science Club, worked on the Princeton Internships in Civic Service program, and was a teaching assistant and grader.

For fun:

Chen likes to run, work on crossword puzzles, and play the violin.