Bachelors in Science and Engineering with honors from the Electrical Engineering Department at Princeton University. Currently pursuing PhD in Machine Learning at CMU. Advisor: Tom Mitchell. Member of the Brain Image Analysis Group.
Broadly, I am interested in discovering how conceptual knowledge is represented and changed in the brain by using modeling, machine learning techniques and brain imaging data. Some more specific things I'm looking at this year: functional connectivity analysis using MEG data, combining fMRI and MEG data for better localization, and the role of memory in noun processing.
Nicole S. Rafidi, Konstantin S. Kravtsov, Yue Tian, Mable P. Fok, Mitchell A. Nahmias, Alexander N. Tait, Paul R. Prucnal. “Power Transfer Function Tailoring in a Highly Ge-Doped Nonlinear Interferometer-Based All-Optical Thresholder Using Offset-Spectral Filtering.” IEEE Photonics Journal. Vol 4, No 2, (2012).
Junda Chen, Abram Demski, Teawon Han, Louis-Philippe Morency, David Pynadath, Nicole Rafidi and Paul Rosenbloom, “Fusing Symbolic and Decision-Theoretic Problem Solving + Perception in a Graphical Cognitive Architecture,” Proceedings of the conference on Biologically Inspired Cognitive Architectures (BICA 2011), Arlington, VA, USA, 2011.
Nicole Rafidi. “High Performance All-Optical Thresholding for High-Speed Interconnects.” Presented in abstract and poster at IEEE High Speed Digital Interconnects Workshop in Santa Fe, NM, May 2011.
Mable P. Fok, Hannah Deming, Mitchell Nahmias, Nicole Rafidi, David Rosenbluth, Alexander Tait, Yue Tian, and Paul R. Prucnal, "Signal feature recognition based on lightwave neuromorphic signal processing," Opt. Lett. 36, 19-21 (2011).
nrafidi at cs dot cmu dot edu