Ensieh Iranmehr is a research engineer at INL. She joined INL Technology Engineering Group in November 2020. She focuses on using machine learning techniques to process sensor signals and images. She works on several projects focusing on analyzing the sensor signals including a TMR-based spintronic sensor, microphone, and Raman spectrum. She also works on some edge computing projects. During her work at INL, she has developed unsupervised algorithms for extracting signal patterns, including patterns based on shape and frequency, as well as supervised algorithms for Raman spectra analysis.

Ensieh has Ph.D. in Digital Systems from the electrical engineering department of the Sharif University of Technology, Tehran, Iran. Her works revolve around artificial neural networks, machine learning, neuromorphic engineering, and digital systems. For her Ph.D. project, she has proposed a new neuromorphic structure of a spiking neural network inspired by biological studies called the ILS-based Reservoir Network. She also has MSc in Digital Electronic Engineering from the electrical engineering department of the Amirkabir University of Technology, Tehran, Iran. Her MSc project revolved around artificial neural networks, image processing, and parallel processing.