Assistant Professor of Computer Sciences and Engineering,
Gildart Haase School of Computer Sciences and Engineering

Contact Information


  • PhD, Computer Engineering, University of Michigan, Ann Arbor
  • MS, Computer Engineering, University of Michigan, Ann Arbor
  • BTech, Electrical Engineering, Indian Institute of Technology, Kanpur


  • EENG 2286, Undergraduate course on Digital Systems Design
  • EENG 7709, Graduate course on Embedded Systems

Academic Profile

Dr. Ravi Rao obtained his Ph.D. in Computer Engineering from the University of Michigan, Ann Arbor, and bachelor’s degree in Electrical Engineering from the Indian Institute of Technology, Kanpur.

Formerly, he worked at the IBM T.J. Watson Research Center and IBM Global Business Services.

His research interests include analytics in education, machine learning, data mining, data science, big data analytics, healthcare, life sciences, neural simulation, brain science, pattern recognition, image processing, machine vision, practical applications of imaging science and technology, human perception and visualization.

He is an IEEE Fellow and a former IBM Master Inventor.

Please visit for further information.

Books Published

A. Ravishankar Rao, “A Taxonomy for Texture Description and Identification”, Springer Verlag, 1990

A. Ravishankar Rao and Guillermo Cecchi, editors, “High-Throughput Image Reconstruction and Analysis”, Artech House, 2009

A. Ravishankar Rao and Guillermo Cecchi, editors, “The relevance of the time domain to neural network models”, Springer Verlag, 2011

A. Ravishankar Rao, Guillermo Cecchi, Ehud Kaplan, editors, “Towards an Integrated Approach to Measurement, Analysis and Modeling of Cortical Networks”, eBook published by Frontiers Research Topics, 2016

Patents (27 issued, 6 filed and pending)

Three most recent patents :

US 9072496: Method and system for modeling and processing fMRI image data using a bag-of-words approach, R. Rao, S. Dey, M. Shah, B. Solmaz

US 8861815: Systems and methods for modeling and processing functional magnetic resonance image data using full-brain vector auto-regressive model, G.A. Cecchi, R. Garg, R. Rao

US 8464026: Method and apparatus for computing massive spatio-temporal correlations using a hybrid cpu-gpu approach, R. Bordawekar, R. Rao

Professional Activity and Service

Fellow, IEEE

Master Inventor, IBM

Associate Editorships for the following journals

  • Pattern Recognition
  • Machine Vision and Applications
  • Neural Networks

Member of National Resource Center Review panel at National Institutes of Health, USA

Selected participant, Keck Futures Initiative, National Academy of Sciences, USA

Principal Investigator of the Working Group “Multi-scale analysis of cortical networks “, funded by NIMBIOS (National Institute for Mathematical and Biological Synthesis, NSF Supported, 2010-2013

Program Co-Chair/Committee Member for multiple conferences, including

  • IEEE Joint Conference on Neural Networks
  • IEEE Conference on Cognitive Informatics and Cognitive Computing
  • SPIE Conference on Machine Vision and Applications

Founded the Computational Intelligence Society, IEEE New York Section, 2010

Artistic and Creative Activity

Classical Indian musician, sitar player, with performances at the Lincoln Center, Lotus Fine Arts Center, the Museum of Natural History, the Noguchi Museum, and the Rubin Museum, New York.

Also featured on WKCR Classical Radio, NYC, 2013.