CIFAR Azrieli Global Scholar 2023-2025
Brain, Mind & Consciousness
Kanaka Rajan is a computational neuroscientist bridging the gap between biology and artificial intelligence. Her lab uses mathematical and computational models to understand how the brain learns and makes decisions. Her research seeks to understand how important cognitive functions — such as learning, remembering, and deciding — emerge from the cooperative activity of multi-scale neural processes. Using data from neuroscience experiments, Rajan applies computational frameworks derived from machine learning and statistical physics to uncover integrative theories about the brain that bridge neurobiology and artificial intelligence. Leveraging her unique expertise in the fields of engineering, biophysics, and neuroscience, Rajan has pioneered computational approaches for understanding how the brain processes information, and how these processes become disrupted by neuropsychiatric diseases.
- McKnight Scholar Award, McKnight Foundation, 2022
- Next Generation Leader, Allen Institute, 2021
- CAREER Award, National Science Foundation (NSF), 2021
- Harold and Golden Lamport Basic Science Research Award, Icahn School of Medicine at Mount Sinai, 2021
- Perich, M.G. & Rajan, K. (2020) Rethinking brain-wide interactions through multi-region “network of networks” models. Current Opinion in Neurobiology, 65:146–151. DOI: https://doi.org/10.1016/j.conb.2020.11.003
- Pinto, L., Rajan, K., DePasquale, B., Thiberge, S.Y., Tank, D.W. & Brody, C.D., (2019) Task-dependent changes in the large-scale dynamics and necessity of cortical regions. Neuron, 2019 Nov 20;104(4):810-824.e9. DOI: 10.1016/j.neuron.2019.08.025
- Rajan, K., Harvey, C.D. & Tank, D.W., (2016) Recurrent network models of sequence generation and memory. Neuron, 90(1): 128-142. DOI: 10.1016/j.neuron.2016.02.00900463
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