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! .
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?
Check out this graduation speech I gave at the University of York 2021, discussing, privilege, luck, and compassion in science and life --- 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