05/2023. I am grateful to have been awarded the University of Rochester College Course Development Fellowship for the course I will be teaching in Fall 2023: Advanced Topics in Cognitive Neuroscience.
marius cătălin iordan
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about me
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I'm an Assistant Professor in the Brain and Cognitive Sciences &
Neuroscience Departments at the University of Rochester.
Previously, I was a Postdoctoral Fellow at the Princeton Neuroscience Institute, working with
Jon Cohen, Ken Norman, and Nick Turk-Browne.
I earned my Ph.D. in Computer Science from the Vision Lab at Stanford University, co-advised by
Fei-Fei Li and Diane Beck.
My academic journey started at Williams College with a B.A. in Computer Science, Mathematics, and Cognitive Science.
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research brief
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I'm a computational cognitive neuroscientist studying the elusive link between how the human brain learns & organizes conceptual information into categories, stories, and events, and
how we use that information to understand & interact with our complex, noisy world.
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join us!
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WE ARE ACTIVELY RECRUITING:
1-2 PhD students | Application deadline: Dec 5, 2023 | Start date: Sept 2024 | Position Ad (no application fee, no GRE required) 1 Postdoc | Applications accepted until position is filled | Start date: flexible | Position Ad |
lab culture
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news
05/2023. I am grateful to have been awarded the University of Rochester College Course Development Fellowship for the course I will be teaching in Fall 2023: Advanced Topics in Cognitive Neuroscience. 
08/2022. I am incredibly happy and grateful to announce that I'll be starting a new adventure in January 2023 as an Assistant Professor at the University of Rochester, with joint appointments in the Brain and Cognitive Sciences & Neuroscience Departments. 
05/2022. Presenting a Talk at the Vision Sciences Society (VSS) 2022 Annual Meeting: Sculpting New Visual Concepts into the Human Brain. 
02/2022. New Publication in Cognitive Science:
Context Matters: Recovering Human Semantic Structure from Machine-Learning Analysis of Large-Scale Text Corpora.
We show that incorporating semantic context into the training procedure of word embedding models improves prediction of empirical similarity judgments and feature ratings. 
11/2021. Presenting a Poster at the Society for Neuroscience (SfN) 2021 Annual Meeting: Sculpting New Visual Concepts into the Human Brain. 
05/2021. Presenting a Poster at the Vision Sciences Society (VSS) 2021 Annual Meeting: Context Matters: Recovering Human Visual and Semantic Structure from Machine-Learning Analysis of Large-Scale Text Corpora. 
10/2020. New Preprint on bioRXiv:
Sculpting New Visual Concepts into the Human Brain.
We decribe a new way to provide humans with visual and conceptual knowledge by directly sculpting activity patterns in their brains using fMRI, real-time neurofeedback, and machine learning! 
10/2020. Presenting a Talk at the NeuroMatch 3.0 Conference: Creating Visual Categories Using Closed-Loop Real-Time fMRI Neurofeedback. 
06/2020. Our team was awarded a Research Grant from the GRAMMY Museum Foundation
to investigate the neural hierarchy of audio-motor integration during natural music performance.
Co-PI, $19,758 (33% share). PI: Elise Piazza, Princeton University, co-PI: Uri Hasson, Princeton University. |