Abhiram Iyer

Abhiram Iyer is a graduate student in electrical engineering and computer science, exploring how principles from neuroscience can inform the next generation of AI. His research bridges theoretical neuroscience and AI, examining how biologically grounded models can both explain brain function and inspire more flexible and efficient machine learning systems. As a MathWorks Fellow, Abhiram will advance models that embed synaptic dynamics and microcircuit architectures into artificial networks, offering possible solutions to long-standing challenges such as catastrophic forgetting and inefficient scaling. MATLAB plays a pivotal role in Abhiram’s research, providing a robust framework for simulating neural circuits, mapping cortical connectivity, solving complex dynamical systems, and prototyping biologically inspired learning algorithms. Leveraging these capabilities, he has successfully modeled grid-cell-based cognitive maps and analyzed synapse-level plasticity mechanisms, contributing to advancements in lifelong learning and interpretable AI. Abhiram’s work could deepen our understanding of intelligence, both natural and artificial, and reshape the foundation of machine learning systems.