Computational
  Cognitive Science Group

I am interested in using cognitive models of human belief and causality reasoning to understand psychological phenomena such as base rate neglect. The ultimate goal of my research would be not just a computational model of human cognition, but also a method for developing AI systems that think like people. I got my PhD in BCS in 2006.

I did computational and cognitive neuroscience in the group of Josh Tenenbaum, BCS, MIT. (previously with Daniel Wolpert and Peter Konig). I specialize in modelling and movement psychophysics. I expect my theories to make experimental predictions, provide a compact description of data and lead to computationally strong algorithms. My experiments should falsify theories.

My research interests are developing computational models of higher level cognition. In particular, I'm interested in developing rational accounts of cognition using probabilistic generative models and Bayesian statistics. My current areas of interest are understanding people's everyday inductive leaps - difficult inductive problems we solve every day, like predicting the future, learning causal relationships, and noticing coincidences - and the interface between psychology and machine learning in developing statistical models of language.

My research interests span a diverse set of topics in cognitive science such as episodic and semantic memory, dynamic decision making, and causal reasoning. In each of these areas, I combine mathematical and computational modeling with behavioral experiments. The models and experiments are tightly coupled: I try to formulate empirical questions with the goals of constraining, developing, or testing between alternative computational models of how people learn, process, and represent information. My research interests also include some computer science topics in the domain of statistical machine learning and information retrieval. The adoption of recent machine learning methodology is useful in advancing cognitive science research, especially in the area of semantic memory.

I'm interested in some of the conceptual groundwork that might someday make psychology more coherent -- how we (or anything) can weave a web of concepts to explain experience. More technically, I'm interested in how to extend the range of probabilistic models of induction to richer descriptions of experience than those available to traditional probabilistic models. I'm also interested in the form of the associations of words with conceptual formulae, how we learn those associations, and how we use them to invoke thoughts in each other and ourselves.

I study the neural and psychological basis of social cognition. Do we have dedicated mechanisms for recognising and/or reasoning about other minds? How and why does the human brain succeed so easily where computers and logicians fail? Addressing these questions, my work spans the disciplines of cognitive neuroscience, developmental psychology, social psychology, computational modelling and philosophy.

My research in the Tenenbaum lab is focused on exploring computational models of how humans learn and generalize through inductive inference. My undergraduate honors thesis analyzed how a computer might construct a hypothesis space (i.e. candidate guesses about the concept to be learned) that could match human generalization performance. In that work, I examined several different unsupervised learning techniques to build a hypothesis space for a Bayesian concept learner. Recently, I have been looking at how humans seem to be using, on an abstract level, taxonomic, tree-based models of similarity to guide their generalization. In my other lab, I am working on understanding the dynamics underlying neural computations in small networks of neurons.

I graduated from the Brain and Cognitive Science Department at MIT doing a UROP with Professor Tenenbaum. My personal research interests for the future include modeling human social cognition.

I graduated from the Brain and Cognitive Science Department at MIT doing a UROP with Professor Tenenbaum. I am primarily interested in concept learning and conceptual change during learning and development.

I graduated from Brain and Cog Sci, only to stick around MIT in the Speech and Hearing Bioscience and Technology program. (I'm a cognitive scientist at heart, of course.) I'm interested in language -- both its evolution as a communication system and its purpose as an internal evoker of mental representations -- and how speech sounds might act as the elementary units of those representations.

I graduated MIT (majoring in BCS & minoring in music.) My research interest lies in searching for the fundamental ways humans generalize and understanding how they interpret novel ideas.