About me

Hello! I am Amir Khalilian, a machine learning and signal processing engineer with a deep commitment to advancing interpretable, scalable algorithms for real-world applications. My background bridges electrical engineering, computer vision, and computational neuroscience, with experience developing and applying advanced optimization, deep learning, graph-based signal processing methods. My research and engineering work have focused on designing innovative frameworks for neural signal analysis, video and image restoration, and speech decoding, resulting in multiple peer-reviewed publications, patents, and successful collaborations across academia and industry.

Currently as a postdoctoral researcher at NYU Langone Health, I leverage my expertise to investigate the neural mechanisms of speech production and perception using electrophysiological data, developing novel tools to map and decode brain activity. Beyond research, I am passionate about creating solutions that integrate rigorous mathematical foundations with machine learning to produce explainable deep-learning technologies. Whether building neuroprosthetic systems, enhancing image processing pipelines, or designing new brian connectivity analysis techniques, I aim to deliver engineering solutions that are both interpretable and transformative. Here, I post updates about my research and other topics of interest.