Assistant Professor
Brain and Cognitive Sciences
Neuroscience
University of Rochester

Research Focus:
Cognitive Neuroscience
Computational Neuroscience
Machine Learning & Data Science

mci (at) rochester (dot) edu
Twitter: @MCatalinIordan
Google Scholar

 he/she/they

Travel and Presentations

2023


Jul 31 BCS Summer Seminar
Rochester, NY
Aug 28 BCS Retreat
Canandaigua, NY
Nov 16-19 Psychonomics 2023
San Francisco, CA


2022


Jan 24 Wesleyan College
Middletown, CT
Feb 7-8 Vanderbilt University
Nashville, TN
May 13-18 VSS 2022
St. Pete Beach, FL
Jun 1-2 V-VSS 2022
Virtual talk
Dec 12 Computer Science
Dept. Seminar
Rochester, NY

marius cătălin iordan
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about me
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.

research brief
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.
join us!
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
  • Our lab will always be a safe + inclusive + welcoming space for everyone, including trainees, collaborators, and participants.
  • We believe that diversity of backgrounds, identities, & perspectives greatly strengthens our ability to tackle research as a team.
  • We believe that respect, support, kindness, & work-life balance are prerequisites of a productive lab environment.
  • We believe in collaboration over competition.
  • We value individually-tailored mentorship highly and we always strive to learn from one another.

                             


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.