Ishita is a Research Scientist at DeepMind New York City (working remotely from San Francisco / Mountain View). Her research is at the intersection of computational cognitive science and machine learning. Ishita uses advances in machine learning to build new models of human reasoning, applies cognitive science approaches toward understanding black-box AI systems (with a recent focus on large-scale pre-trained models), and combines these insights to build better, more human-like artificial intelligence.
She was previously a postdoctoral researcher at Princeton University in the Departments of Psychology and Computer Science, working in the Computational Cognitive Science Lab with Prof. Tom Griffiths. She received her PhD from the Department of Physics at Harvard University in 2020, working in the Computational Cognitive Neuroscience Lab with Prof. Sam Gershman.
