ECE Alumna Rose Faghih Publishes Open Access Book

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Rose Faghih (ECE ‘08) is the senior author of an open access book titled "Bayesian Filter Design for Computational Medicine: A State-Space Estimation Framework", published by Springer.  The first author is Faghih’s former Ph.D. student, Dilranjan Wickramasuriya.

Physiological signals, such as skin conductance, heart rate and biochemicals in the blood, can be measured and observed in order to better understand numerous processes taking place in the human body. One modern challenge has been to create mathematical tools that will link these signals in order to provide concrete results to physical observances.

Current research uses physiological phenomena from a state-space control system perspective to apply to various applications such as brain-computer interfaces, behavioral learning and human emotion recognition. Until now, access to these studies have been through advanced journal papers and not been readily available to beginner graduate students, Faghih and Wickramasuriya have developed a tutorial-like publication intended to aid the beginner in statistical Bayesian methods for computational medicine, appropriate for the point process physiologicalphenomena.  

Their purpose in writing this book is to give readers an understanding of the processes and models needed to acquire tools for successfully developing physiological state-space estimators involving point process phenomena. In addition, the concepts examined in the book can be applied to other data sets, such as earthquakes, incidents of crime, and rainfall.  The book is available as an open access publication and the code described within the work is publically available.  It can be used as a free resource applicable to many research areas in biomedical research and other technologies.

Research used to write this book was supported by an NSF CAREER grant titled MINDWATCH: Multimodal Intelligent Noninvasive brain state Decoder for Wearable AdapTive Closed-loop arcHitectures

Faghih is an Associate Professor in the New York University (NYU) Department of Biomedical Engineering and Director of the Computational Medicine Laboratory.  After graduating from UMD with a BSc degree (summa cum laude) in electrical engineering (Honors Program Citation and first in her class), she earned her MS and PhD degrees in Electrical Engineering and Computer Science with a minor in Mathematics at MIT. Her research interests include Control, Estimation, and System Identification of Biomedical Systems, Data Science and Computational Methods for Biomedicine, Biomedical and Neural Signal Processing, Wearable Computing, Physiological Modeling & Cyber Physical Systems

In addition to her NSF CAREER Award, she is a recipient of NIH Maximizing Investigators’ Research Award for Early Stage Investigators, and has been named one of 35 Innovators Under 35by MIT Technology Review, an IEEE-USA New Face of Engineeringand an IEEE Women in Engineering Magazine “Woman to Watch.”In 2022, she was inducted into the A. James Clark School of Engineering Early Career Distinguished Alumni Society Class of 2022.  She is a senior member of IEEE and has been inducted into various honor societies, including Phi Kappa Phi, Tau Beta Pi, and Eta Kappa Nu.

Published May 28, 2024