Ankit Parekh

Ankit Parekh, PhD

About Me

Ankit Parekh, PhD is an Assistant Professor with the Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine at Icahn School of Medicine at Mount Sinai. Dr. Parekh received his BS in Computer Engineering, MS and PhD degrees in Applied Mathematics from New York University in 2011, 2012 and 2016 respectively. During his PhD, he worked on the advancement of a theoretical framework termed convex non-convex optimization and its use in understanding sleep neurobiology. After completing a year of postdoctoral training in cardiac and brain imaging at the University of Iowa’s Institute of Biomedical Imaging, he joined the sleep research team at Icahn School of Medicine at Mount Sinai as a postdoctoral fellow in sleep medicine. During his fellowship, he developed a novel metric of EEG K-complex/slow-wave coupling that exhibits a dose-responsive relationship with performance on a psychomotor vigilance test, which is a common surrogate for daytime sleepiness, in sleep apnea patients before and after treatment. Dr. Parekh’s current work is geared towards developing predictive models for daytime sleepiness in sleep apnea using data from multiple modalities (e.g., EEG, structural and functional MRI).

Dr. Parekh heads the Sleep and Circadian Analysis (SCAN) Group. The SCAN group's efforts are dedicated toward quantifying patterns of sleep disorders using mathematical modelling and machine learning methods. The SCAN group also provides data analysis standards and specifications to investigators inside and outside the Mount Sinai Community. Additional services include: 

  • Basic training and certification in actigraphy, polysomnography, and circadian analyses
  • Assistance for investigators of all levels from junior to senior, in the interpretation and analysis of sleep and circadian data
  • Assistance in the development of grant proposals aimed at utilizing sleep and circadian data
ASSISTANT PROFESSOR | Medicine, Pulmonary, Critical Care and Sleep Medicine, ASSISTANT PROFESSOR | Artificial Intelligence and Human Health
Research Topics

Biomedical Sciences, Computational Neuroscience, Computer Simulation, Image Analysis, MRI, Personalized Medicine, Sleep Medicine

Multi-Disciplinary Training Areas

Artificial Intelligence and Emerging Technologies in Medicine [AIET], Neuroscience [NEU]