Kanwisher Lab


Pramod RT (pramodrt at mit dot edu)
The brain is an extraordinary machine -- it processes a lot of information at astonishing speeds to enable us to go about our everyday lives. What kind of information is represented where (and when) in the brain? What are the underlying computations? As a postdoctoral researcher with Nancy Kanwisher, I am working towards answering these questions using ECoG, Neuroimaging and computational modeling. Prior to this, I obtained my PhD from the Indian Institute of Science where I worked with SP Arun towards understanding the compositional nature of object representation in brains and machines.
Vivian Paulun (vpaulun at mit dot edu)
At a glance, we get a rich and deep understanding of the physical world around us. Not only can we recognize objects, we also get a sense of their internal (material) properties: We can see how an object would feel when touched, squeezed or lifted and, importantly, we can predict its possible futures. How does the human brain represent materials and their properties to achieve this? Fortunately, I have received a fellowship to work with Nancy Kanwisher and Josh Tenenbaum on this question using neuroimaging, machine learning and computational modelling. I got interested in materials during my PhD (with Roland Fleming, Mel Goodale, Karl Gegenfurtner), in which I investigated how material properties shape the way we grasp and interact with objects. Before joining MIT, I did a postdoc in Roland’s lab investigating the visual cues humans use to infer functional material properties (e.g. softness) by sight in the first place.
Thomas O'Connell (tpo at mit dot edu)
I am a postdoctoral researcher working with Nancy Kanwisher and Josh Tenenbaum. My research aims to answer how perceptual processes in the primate brain give rise to behavior and higher-order cognition using tools from neuroscience (fMRI, MEG, non-human primate electrophysiology) and cognitive computational modeling (deep learning, inverse graphics). Prior to MIT, I received my PhD with Marvin Chun at Yale University applying neural reconstruction techniques to study spatial attention in the human brain.
Kamila Jóźwik (kmjozwik at mit dot edu)
Broadly I'm interested in the following questions: How does the primate brain process visual information? More specifically - how does the primate brain recognise objects? What are the underlying computations of visual processing? I'm using fMRI, EEG, MEG, behavioural measures and single-cell recording data, together with computational modelling (including deep neural networks) to understand these processes better. I’m a Sir Henry Wellcome postdoctoral fellow working with Nancy Kanwisher and Jim DiCarlo at MIT, and Zoe Kourtzi at the University of Cambridge. I am interested in modelling the representations in the brain and behaviour, for human and monkey, using deep neural networks. For more information, please see my website and Cambridge Neuroscience page
Dana Boebinger (dlboebinger at gmail dot com)
I am a PhD student in the Harvard-MIT program in Speech and Hearing Bioscience and Technology , working both with Nancy Kanwisher and Josh McDermott. I use fMRI to examine the neural mechanisms that underlie human perception of complex sounds, such as speech and music. I am also interested in how perception of these complex sounds varies across people, as well as the extent to which experience shapes both auditory perceptual abilities and how sound is represented in the brain.
Kirsten Lydic (kolydic at mit dot edu)
As a lab tech, my project involvement is regularly in flux, and the work I do in the lab is fairly diverse. Presently, though, my main project involves a methods test of MEG source localization in the ventral visual pathway. In other words, using fMRI as a baseline for comparison, how viable is MEG as a methodology for obtaining both temporal and spatial resolution, namely in visual processing of specific domains like faces, words, objects, scenes, etc. Before starting as a lab tech here in 2019, I went to Hampshire College in western MA, where I studied cognitive neuroscience and worked as a research assistant/lab manager for an event-related potential/EEG lab. My main research interests are broadly in the realm of social cognition, and I am also very interested in the processes that underly informational abstraction in the brain.
Julio Martinez (juliom at mit dot edu)
As a lab tech I get to be involved in several difference projects. I have mostly focused on training deep neural networks for specific tasks, such as face identification and object categorization, to do comparitive analysis to human neural computations. I have been working closely with Katharina Dobs exploring lesion experiments on different deep net architectures to understand individual units and groups of units, and in particular, to discover units responsible for face processing. My future interests are in expanding this research to natural language processing tasks. For example, I am interested in understanding whether neural networks segregate the learning of syntax and semantics. Before coming to this lab I spent some time at Apple working on machine learning research in the Platform Architecture Org. I received my masters at Stanford University in Computational and Mathematical Engineering.
Freddy Kamps (fkamps at mit dot edu)
I am a postdoctoral research fellow working with Nancy Kanwisher and Rebecca Saxe. I’m interested in the functional organization and development of high-level visual systems for recognizing people, places, and things. My current work focuses on the developmental origins of cognitive and neural systems supporting scene recognition and navigation in infancy. Prior to MIT, I completed my PhD at Emory University with Daniel Dilks, where I studied the functional organization and development of human scene and face processing.
Apurva Ratan Murty (ratan at mit dot edu)
I am postdoctoral research fellow with Nancy Kanwisher and Jim Dicarlo. I received my PhD in Neuroscience from the Centre for Neuroscience, Indian Institute of Science, Bangalore - India, where I studied viewpoint invariant object representations in the macaque inferotemporal cortex. Broadly, I am interested in computational mechanisms during early brain development and investigate this using a combination of brain imaging, macaque electrophysiology, behavioural psychophysics and computational modelling.
Heather Kosakowski (hlk at mit dot edu)
At birth, the human infant brain weighs less than one pound. As infants become children and then adults, that tiny piece of tissue grows and expands to three times its birth size and is responsible for housing our entire experience as a human being. Every bit of knowledge, every cognitive capacity, and every thought humans have is a result of what is and isn’t stored by the billions of neurons in our brain. I think that is amazing! As a graduate student, I get to study the development of the functional specialization and organization of the human brain with Nancy Kanwisher and Rebecca Saxe as my advisors!
Meenakshi Khosla (mkhosla at mit dot edu)
We’re at a very special time in human history where on one hand, we are witnessing a data revolution in neuroscience collecting ever-larger neural datasets and on the other, computational models inspired from the brain (‘artificial neural networks’) are offering promising ways to understand neural computations. How can we use modern artificial neural networks to model and understand how the brain processes the natural world? How far can they get us in answering some critical why-questions about phenomena observed in the human brain? I am excited to tackle some of these questions as a postdoc with Nancy Kanwisher. Prior to joining the Kanwisher Lab, I completed my PhD in Electrical and Computer Engineering at Cornell University with Mert Sabuncu, where I first delved into the study of the human brain.
Elizabeth Mieczkowski (emiecz at mit dot edu)
As a lab tech, I get to work on several ongoing projects at a time. I am interested in applications of computational models and neural networks to cognitive science. I recently graduated from Cornell University with a degree in Computer Science and Psychology, where I worked on natural language processing projects, moral psychology research, and building AI navigation algorithms for autonomous robotic sailboats.
Willian De Faria (wdefaria at mit dot edu)
Currently, I am a post-baccalaureate researcher working in Dr. Nancy Kanwisher's Lab. I graduated from the University of Notre Dame with a degree in Neuroscience and Applied Mathematics and worked on investigating EEG signals of younger and older adults engaged in cognitive tasks. I am broadly interested in working memory and perception, particularly in how we form mental imagery that are counterfactual to online sensory input. I plan on pursuing an MD/PhD to work as a physician-scientist and I hope to develop novel computational tools that can be easily used in clinical settings for the treatment of neurological and psychiatric disorders.
Jessica Chomik (jchomik at mit dot edu)
During the Abnormal Psychology section of a course in high school, our class watched “Silence of the Lambs”, and I thought, “I want to be the person talking to that guy [Hannibal Lector].” Since then I have tasted the many flavors of Neuroscience, from manipulating Alzheimer’s genes in a Drosophila lab, to exploring science communication with a podcast (The Research Diaries), to working in a clinical setting with patients at risk of having Dementia and AD. Now, I am working from the computational side of Neuroscience, using machine learning and brain imaging to study causal relationships in the brain. I hope to use my acquired knowledge to facilitate science communication to the general public and pursue a PhD to better understand the biological basis of deviant social behavior in humans.
Gustavo X Santiago-Reyes (gustxsr at mit dot edu)
Reading the 110 pages of "Cognitive Neuroscience: A Very short introduction" during the Summer of 2020 was my first step into looking at the brain in a scientific lens. The following year, I was lucky to work with Thomas O'Connell in a project regarding how predictive the layers of a pool of neural networks are for eye movement data and how this correlates with the model's neural predictability and accuracy. The following Summer, I worked with O'Connell in a project that involved analyzing what features are encoded in the layers of 3D scene representation networks. I'm looking forward to continue exploring more about the computations of the brains using Artificial Intelligence and Computer Science techniques!
Nancy Kanwisher (ngk at mit dot edu)
Lucky me! I get to work with all the brilliant and wonderful people on this page, and to think about cool questions like these: How are objects, faces, and scenes represented in the brain, and (how) do the representations of each of these classes of stimuli differ from each other? How are visual representations affected by attention, awareness, and experience? Which mental processes get their own special patch of cortex, why is it these processes and (apparenly) not others, and how do special-purpose bits of brain arise in the first place?
If you want to know about my personal story, check out this graduation speech I gave at the University of York 2021, discussing privilege, luck, and compassion in science and life; listen to this interview about my twisted career path, or this one, or read about the quest for the FFA!
Hi, I’m Shiloh. I grew up in Alabama then got shipped up north to my new home with Mom and Dad on Cape Cod. I love running and leaping and snuggling. I can’t wait to have the whole Kanwisher Lab to play with!
Former Lab Members