Postdoctoral Researcher
Princeton Neuroscience Institute
Princeton University
Research Focus:
Cognitive Neuroscience
Computational Neuroscience
Machine Learning
Princeton Neuroscience Institute
Washington Road
Princeton, NJ 08544
mci (at) princeton (dot) edu
Google Scholar | Research Gate
| Mar 31 | PDP Seminar Princeton, NJ talk |
| May 19-24 | VSS 2017 St. Pete Beach, FL poster |
| June 28-30 | IASL 2017 Bilbao, Spain talk |
| Sep 20 | CogSci Seminar Princeton, NJ talk |
| Nov 11-15 | SfN 2017 Washington, DC poster |
| Nov 28-Dec 1 | RTFIN 2017 Nara, Japan poster |
| Dec 12 | PDP Seminar Princeton, NJ talk |
| Feb 1 | UC Berkeley Berkeley, CA talk |
| Apr 2-5 | CNS 2016 New York, NY poster |
| Apr 29 | Ph.D. Thesis Defense Stanford, CA talk |
| Sep 16 | PDP Seminar Princeton, NJ talk |
| Nov 3-6 | Williams College Williamstown, MA talk |
| Nov 12-16 | SfN 2016 San Diego, CA poster |
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I'm a Postdoctoral Researcher at the Princeton Neuroscience Institute, working with Jon Cohen and Dan Osherson. I earned my Ph.D. in Computer Science from the Vision Lab at Stanford University, co-advised by Fei-Fei Li and Diane Beck (University of Illinois). Before that, I received my B.A. from Williams College in Computer Science, Mathematics, and Cognitive Science.
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We rely on vision more than on any other sensory modality to
interact with and make sense of our environment. Our behavior and
culture, as well as the data we generate, all rely strongly on visual
information to index and capture salient relationships in the world.
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My work uses functional neuroimaging (fMRI), psycho-physics, and
computational approaches to explore how categories, concepts, and
the similarity between them are represented in our brains and how
they contribute to our building a coherent picture of the world.
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news
Dec. 2017: Presenting at the Real-Time Functional Imaging and Neurofeedback (RTFIN) 2017 Conference: poster: KL-Evidence: A Novel Multivariate Method for Differentiating Representations. Our work also received a Travel Award from the RTFIN Program Committee. 
Nov. 2017: Presenting at the Society for Neuroscience (SfN) 2017 Annual Meeting: poster: Inducing Neural Plasticity and Perceptual Similarity Using Real-Time fMRI Neurofeedback. 
Aug. 2017: Our work showing that vocal timbre is a discriminative feature between infant-directed and adult-directed speech was accepted for publication in Current Biology: "Mothers Consistently Alter Their Unique Vocal Fingerprints to Communicate With Infants". 
May 2017: Presenting at the Vision Sciences Society (VSS) 2017 Annual Meeting: poster: The Relative Contribution of Features and Dimensions to Semantic Similarity. 
Nov. 2016: Presenting at the Society for Neuroscience (SfN) 2016 Annual Meeting: poster: Sequential Warping of Neural Representations According to Cognitive Principles in Visual Cortex. 
Jul. 2016: Joined the Neuroscience of Cognitive Control Lab (NCCL) at the Princeton Neuroscience Institute (PNI) as a Postdoctoral Researcher, working with Jon Cohen and Dan Osherson. 
Jun. 2016: Graduated with M.S. and Ph.D. in Computer Science from Stanford University. Degree Focus: Cognitive and Computational Neuroscience, Machine Learning. 
Apr. 2016: Our work on how perceived typicality modulates the neural representation of real-world objects was accepted for publication in Neuroimage: "Typicality Sharpens Category Representations in Object-Selective Cortex". 
Jan. 2016: The Key Reporter, Phi Beta Kappa Society's magazine for news and alumni relations, published a story about Elise Ann Piazza and Marius Cătălin Iordan and their shared journey into science: "ΦBK Couple Combines Liberal Arts and Sciences in Career". |