Explores neural signal processing, MRI techniques, and imaging validation, emphasizing structural and functional connectivity and clinical applications.
Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.
Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
Explores phase transitions in physics and computational problems, highlighting challenges faced by algorithms and the application of physics principles in understanding neural networks.