Research
My research uses new computational tools to look into old questions about how we perceive and understand one another.
We’re able to look at another person - even a total stranger - and get a vivid impression of their emotions and mental state. But how do we actually do this?Whether or not our perceptions of others are accurate, the perceptual system can clearly extract and efficiently, flexibly represent incredibly complex information about what others are thinking and feeling. How is the brain accomplishing this high-level information processing from a computational perspective? How much of the richness of social cognition comes from raw perception vs. abstract, culturally-shaped ideas about what humans are like (or should be like)?
computational social vision
My research takes a computational approach to understanding how we communicate and understand one another's emotions (and how we perceive each other more generally).I'm very influenced by the social vision approach, which reframed our scientific understanding of social perception using insights about how perception fundamentally works drawn from vision science, neuroscience, and psychophysics.
This transdisciplinary approach opens up opportunities to consider major theoretical questions about the nature of perception, categories, intelligence, and representation. It's also been an exciting time to keep up with the methods and findings of vision science, which is rapidly being reshaped by deep computer vision models.
emotion perception
My first major line of research applied this approach to facial expressions - borrowing concepts from vision science, to what extent can we think of this process in terms of "bottom-up" and "top-down" processes (i.e., the relative influence of perceptual cues on the face vs. pre-existing perceptual heuristics and biases in the observer). This weighs in on debates about the role of conceptual knowledge in emotion, and the ability for cognitive processes to influence perception more generally. These papers investigate this question using computational methods applied to behavioral and brain imaging data, respectively:Brooks & Freeman (2018), *Nature Human Behaviour*
Brooks, Chikazoe, Sadato, & Freeman (2019), *PNAS*
computational approaches to brain and behavior
My research is also motivated by a desire to bring in new mathematical and statistical tools so that psychological science can capture and describe more of the nuance and complexity we're familiar with in our daily lives.Models and taxonomies in psychology tend to be very reductive - six basic emotions, two dimensions of social perception, dual-process models of learning, memory, morality. We have endured a massive gap between the obvious richness and complexity of human life and the ways we can describe and measure it scientifically.
In my work at Hume, I'm currently working on this problem in the domain of emotion - using machine learning in conjunction with massive experimentally controlled datasets to determine new ways to measure, represent, and model human emotion, and how these methods can remain sensitive to complex variability between individuals and cultures.
the future of explanatory models in psychology
Unprecedented amounts of data and advances in our capability to process and derive insights from huge amounts of data are opening a door on a completely new way to do science, and I'm fascinated about what this means for the future of psychology.Advances in data science and machine learning might enable psychological science to capture more of the truth of how we work, but in order to do this, it might have to use mathematical descriptions that abstract very far away from our daily experience of being human. What will this be like? How can we prepare for it? If today's psychology is classical mechanics, what is psychology's string theory?
etc.
Please feel free to reach out to me by email if you want to discuss any of these areas of research, or to just let me know you reached the bottom of this page.Aside from science I like yoga, cooking, guitar, video games, and exploring new york city, which gets bigger the longer I live here. I try to read as much as possible and you can feel free to check out the books I've been reading here.