Sudeep Bhatia studies the cognitive basis of human judgment and decision making with the use of mathematical and computational models. There are two interrelated components of his research program. The first involves understanding how people sample and aggregate information in order to form preferences and beliefs: He extends psychological research on perceptual decision making and memory retrieval to explain behavioral findings in domains such as multiattribute choice, risky choice, and probability judgment. The second component involves specifying the information that is sampled and aggregated in order to form preferences and beliefs. He applies methodological insights from semantic memory research and computational linguistics to uncover knowledge representations for objects, attributes, and events that are the focus of everyday judgment and decision tasks.
With progress in both these areas, he aims to build models of judgment and decision making that know what people know and use knowledge in the way people use knowledge. These models should be able to deliberate over and respond to a large variety of everyday decision problems, and moreover, mimic human responses to these problems.