Kanaka Rajan

Kanaka Rajan is an Associate Professor of Neurobiology at Harvard Medical School, leading the Rajan Lab. Her research integrates computational neuroscience with artificial intelligence to uncover the brain's operational principles, focusing on how neural circuits bridge time scales between fast synaptic activity and slower cognitive processes like learning and decision-making. The lab develops biologically plausible neural network models constrained by experimental data to predict brain behavior and inform new experiments.

Education and affiliations include a PhD in neuroscience or related field (details not explicitly stated in text). The lab's interdisciplinary approach merges machine learning, systems neuroscience, and theory to address grand challenges such as social cognition dynamics and translational cross-species models. Major contributions include frameworks for recurrent neural networks and tools like the Minian analysis pipeline.

Research interests emphasize linking neural network theory with empirical data, particularly in how brain circuits manage temporal complexity. The lab explores mechanisms underlying information valuation, modular learning, and resilience through stress studies. Broader impacts include promoting ethical AI regulation and fostering open science practices.

Notable collaborations involve developing self-supervised learning models for medical applications and analyzing neural time-series data from epilepsy patients. The lab actively advocates for socially responsible AI development and hosts initiatives like the 'Learning Salon' for participatory science.