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

Travel and Presentations

2017


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


2016


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

marius cătălin iordan
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about me
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.
research interests
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.
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.

       

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.

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".