303 KD Building
The only way so many different people can agree about so much they experience in the world is if the fundamental substrate for those experiences is identical. This is clearly true at the level of gross physiology, but cognitive scientists believe that this is also true of more abstract categories of phenomena that underpin experience.
By abstract categories, I mean things like attention, memory, values, emotion, and motivation. These aren't physically observable phenomena, but seem to play important organizing roles in any meaningful analysis that tries to understand the lived experience. The hope of cognitive science is to clarify how and why these phenomena arise, interact, and dissipate.
I share this hope, and am trying to do my bit to help this project along, and to see how insights from this research can be used to improve the ways in which computing systems interact with humans.
*For a full list, see here.
Modelling metareasoning about decision thresholds in a perceptual learning task. Proceedings of ICCM 2018 (preprint)
A simple model of recognition and recall memory. Proceedings of NIPS 2017 (pdf)
A rational analysis of marketing strategies. Proceedings of CogSci 2017 (pdf)
Modeling sampling durations in decisions from experience. Proceedings of Cog Sci 2016 (pdf)
Attention modulates spatial precision in multiple object tracking. Topics in Cognitive Science, 2016 (pdf)
Learning what to want: context-sensitive preference learning. PLoS One 2015 (pdf)
Choosing fast and slow.Proceedings of Cog Sci 2015 (pdf)
Magnitude-sensitive preference formation. Proceedings of NIPS 2014 (pdf)
Frugal preference formation. Proceedings of Cog Sci 2014 (pdf)
Classical conditioning via inference over observable situation contexts. Proceedings of Cog Sci 2014 (pdf)
Rational inference of relative preferences. Proceedings of NIPS, 2012 (pdf)
Muhammad Aurangzeb Ahmed Visiting Research Scientist. Agent-based simulations of religious affiliation and conversions.
Anveshna Srivastava Visiting Research Scholar. Predicting individual differences in academic outcomes using cognitive variables.