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


Mar 09 PDP Seminar
Princeton, NJ
May 18-23 VSS 2018
St. Pete Beach, FL
June 17-21 OHBM 2018
Nov 3-7 SfN 2018
San Diego, CA


Mar 31 PDP Seminar
Princeton, NJ
May 19-24 VSS 2017
St. Pete Beach, FL
June 28-30 IASL 2017
Bilbao, Spain
Sep 20 CogSci Seminar
Princeton, NJ
Nov 11-15 SfN 2017
Washington, DC
poster | poster
Nov 28-Dec 1 rtFIN 2017
Nara, Japan
Dec 8 PDP Seminar
Princeton, NJ

marius cătălin iordan
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about me
I'm a Postdoctoral Researcher at the Princeton Neuroscience Institute, working with Jon Cohen, Ken Norman, and Nick Turk-Browne (Yale University). 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 visual and semantic concepts and categories are learned and represented in our brains and how they contribute to our building a coherent picture of the world.



May 2018: Presenting at the Vision Sciences Society (VSS) 2018 Annual Meeting:
talk: Inducing Neural Plasticity and Perceptual Similarity Using Real-Time fMRI Feedback.

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 and a Best Poster 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.
poster: The Importance of "Motherese": Early Drivers of Successful Communication.

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".