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Omid Dehzangi

Omid Dehzangi



Adjunct Assistant Professor

Dr. Omid Dehzangi received B.Sc. and M.Sc. Degrees in Computer Science and Engineering from the School of Electrical and Computer Engineering, Shiraz University in 2002 and 2006, respectively. Then, he received his Ph.D. degree from the School of Computer Engineering at Nanyang Technological University in 2012. In 2013 and 2014, he completed postdoctoral fellowships at the Center for Brain Health and the Department of Electrical Engineering at the University of Texas at Dallas, respectively. He became a tenure-track Assistant Professor at the University of Michigan from 2014 to 2018. He is currently the data analytic lead at the Rockefeller Neuroscience Institute, and Assistant professor in the department of Neuroscience and Adjunct professor at the department of computer science and electrical engineering. His research interests lie broadly in the area of wearable embedded systems, their signal processing and data analytic algorithm design using machine learning and deep learning with the emphasis on pervasive medical applications. His research has been funded by the NSF, NIH, SRC, Texas Instruments, Toyota, and Ford.


  • PhD, Computer Engineering, Nanyang Technological University
  • MSc, Computer Engineering, Shiraz University

Selected Publications

  • Dehzangi O, Rajendra V. (2018) Wearable Driver Distraction Identification On-The-Road via Continuous Decomposition of Galvanic Skin Responses. The MDPI Sensors
  • Dehzangi O, Farooq M. (2018) Portable Brain Computer Interface for the Intensive Care Unit Patient Communication using Subject-Dependent SSVEP Identification, The BioMed Research International Journal
  • Taherisadr M, Dehzangi O, Hossein P. (2017) Single Channel EEG Artifact Identification Using Two Dimensional Multi-Resolution Analysis, The MDPI Sensors journal, 17:12 2895
  • Dehzangi O, Taherisadr M, Changalvala R. (2017) IMU-based Gait Recognition using Convolutional Neural Networks and Multi-Sensor Fusion, The MDPI Sensors journal 17:12, 2735

Teaching Interests

  • Data Structures
  • Expert and Decision Support Systems
  • Introduction to Big Data
  • Advanced Data Mining
  • Advanced Artificial Intelligence

Research Interests

  • Learning from Data
  • Medical Embedded Systems
  • Wireless Health & Physiological Monitoring