Assistant Professor
Brain and Cognitive Sciences
Neuroscience
Goergen Institute for Data Science
University of Rochester


Research Interests
Visual and Naturalistic Cognition
Learning and Neural Plasticity
Computational Neuroscience

 mci(@)rochester.edu

 Google Scholar

 she/her

Travel and Presentations

2024


Jul 3 BCS REU Seminar
Rochester, NY
Aug 6-9 CCN                  
Boston, MA
Aug 15-17 CVS Symposium
Rochester, NY
Sep 13 BCS Retreat
Bristol, NY


2023


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

coraline rinn iordan
home      research      papers      teaching      outreach      travel      cv

instructor, university of rochester

An interdisciplinary introduction to cognitive science, focusing on behavioral, neuroscientific, and artificial intelligence approaches to understanding how information is encoded, represented, organized, and used by the human mind to interact with the world. Topics explored include concepts, categories, learning, attention, language, memory, and deep neural networks.

Cognition
University of Rochester. Brain and Cognitive Sciences & Psychology. BCSC 153 / PSYC 153
undergraduate   |   lecture
Spring 2024 (111 students), Spring 2025

An interdisciplinary tour of human cognition with a special focus on large-scale neural representations in the human brain. Topics include categorization, semantics, attention, memory, language, and cognitive control, with an emphasis on cutting-edge research that lies at the intersection of neuroscience, psychology, and computer science.

Advanced Topics in Cognitive Neuroscience
University of Rochester. Brain and Cognitive Sciences & Neuroscience. BCSC 280 / NSCI 280 / BCSC 580
graduate   |   lecture + seminar
Fall 2023 (12 students), Fall 2024 (18 students)


instructor, princeton university

Workshop that trained senior thesis students how to develop a strong rationale for performing effective empirical research. Also included professional development training (time management, effective writing and presentation style, designing compelling figures).

How to Effectively Design, Write, and Present a Neuroscience Honors Thesis
Princeton University. Neuroscience. Senior Thesis Workshop
undergraduate   |   seminar
Fall 2020 (11 students)

Discussion-based group tutorial that taught students how to analyze and interpret modern neuroscience literature. Topics focused on semantic and visual categorization in humans and non-human primates, covering multiple modalities (fMRI, ECoG, MEG, DNNs, modeling).

Cognitive and Computational Concerns in Cortical Concept Categorization
Princeton University. Neuroscience. Junior Tutorial
undergraduate   |   lecture + seminar
Fall 2017 (11 students)


guest lectures

Semantic Maps Across Human Cortex
University of Rochester. Neuroscience. NSCI 592. Critical Readings in Systems and Integrative Neuroscience.
Spring 2024

The Neuroscience of Categorization
University of Rochester. Brain and Cognitive Sciences. BCSC 502. Cognition.
Spring 2024

Multivariate Pattern Separation For Multiple Experimental Techniques
Princeton University. Neuroscience. Scientific Computing.
Summ 2020

Networks and Hierarchical Processing: Object Recognition in Human and Computer Vision
Stanford University. Computer Science. CS 131. Computer Vision and Applications.
Fall 2014

A Primer on Human Vision: Insights and Inspiration for Computer Vision
Stanford University. Computer Science. CS 131. Computer Vision and Applications.
Fall 2014


course assistant, stanford university

Taught discussion sections, held office hours, assisted students with problem sets and code, graded assignments. Work included Matlab programming and extensive theoretical proofs.

Computer Science. CS 131
Computer Vision and Applications
Instructor: Fei-Fei Li
Fall 2014, 50 students
Computer Science. CS 229
Machine Learning
Instructor: Andrew Ng
Fall 2011, 460 students


teaching assistant, williams college

Assisted students with coding assignments, held consulting hours, graded student work. Assignments included extensive theoretical proofs and programming in Java, C, C++, Lisp, Smalltalk, and Assembly language.

Computer Science. CS 334
Programming Languages
Instructor: Morgan McGuire
Spring 2009, 30 students
Computer Science. CS 334
Programming Languages
Instructor: Stephen Freund
Spring 2008, 30 students
Computer Science. CS 361
Theory of Computation
Instructor: Brent Heeringa
Fall 2007, 20 students
Computer Science. CS 237
Microarchitecture
Instructor: James D. Teresco
Fall 2006, 35 students
Computer Science. CS 361
Theory of Computation
Instructor: Brent Heeringa
Fall 2008, 25 students
Mathematics. MATH 211
Linear Algebra
Instructor: Cesar E. Silva
Spring 2008, 60 students
Mathematics. MATH 211
Linear Algebra
Instructor: Theron J. Hitchman
Spring 2007, 60 students
Mathematics. MATH 211
Linear Algebra
Instructor: Cesar E. Silva
Fall 2006, 120 students