Jul 2018: Presenting at the Cognitive Science Society (CogSci) 2018 Annual Meeting:
talk: Feature Ratings and Dimension-Specific Similarity Explain Distinct Aspects of Semantic Similarity.
marius cătălin iordan
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about me
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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.
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research interests
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Our experiences often contain never before seen objects, scenes, and semantic concepts.
However, we easily navigate these new events because we interact with the world
not as a collection of unique novel items, but by first recognizing which
category these belong to; categories that are already familiar to us and that
we learned and honed over years of experience.
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My work uses functional neuroimaging (fMRI), real-time neurofeedback, and machine learning
to explore how the human brain builds and learns
categories from groups of items, how we use them to
generalize old experiences to novel situations, and how to control
and influence category representations to improve our interactions
with the world.
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news
Jul 2018: Presenting at the Cognitive Science Society (CogSci) 2018 Annual Meeting: talk: Feature Ratings and Dimension-Specific Similarity Explain Distinct Aspects of Semantic Similarity. 
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. 
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. |