Hello! My name is Cathy Chen. I’m a PhD student in EECS at UC Berkeley, advised by Dan Klein and Jack Gallant. I am affiliated with BAIR and supported by an NSF Graduate Research Fellowship. I am broadly interested in the intersection of language, cognitive neuroscience, and machine learning.
Before coming to Berkeley, I received a Fulbright Student Grant to work on causal inference and neuroscience at LMU Munich and MPI Tuebingen, advised by Moritz Grosse-Wentrup. I graduated with a BSE in Computer Science from Princeton with minors in Neuroscience, Statistics and Machine Learning, and Applied Math. There, I had to privilege of working with Ken Norman, Elad Hazan, and Zahra Aminzare.
Outside of research, I run, play tennis and guitar, and work on improving my German and Spanish.
- Causal Inference in fMRI Data (in preparation).
- Showed prevalence of false positives when applying statistical causal inference methods to noisy data, even with simple model assumptions.
- Learning to Perform Dynamic Role-Filler Binding with Schematic Knowledge (CCN 2018). preprint poster abstract
- Tested whether/how neural networks learn to perform dynamic role-filler binding, the ability to associate specific “fillers” with abstract “roles” by learning structural relationships underlying specific experiences.
- A Temporal Decay Model for Mapping between fMRI and Natural Language Annotations (CCN 2017). abstract
- Studied the influence on exponential decay parameters to integrate information in models that predict between fMRI brain scans of subjects watching a movie and external text annotations of the same movie.
- Decision Making in Heterogeneous Drift Diffusion Networks slides report (PACM Undergraduate Certificate Colloquium 2018)
- Characterized decision dynamics in groups of hetereogeneous individuals that accumulate information according to the drift-diffusion model.