A. Ravishankar (Ravi) Rao

Assistant Professor of Computer Sciences and Engineering

Gildart Haase School of Computer Sciences and Engineering

Education

PhD, Computer Engineering, University of Michigan, Ann Arbor

M.S., Computer Engineering, University of Michigan, Ann Arbor

B.Tech, Electrical Engineering, Indian Institute of Technology, Kanpur

Courses Taught

EENG 2286, Undergraduate course on Digital Systems Design

EENG 7709, Graduate course on Embedded Systems

Books Published

Ravi Rao Book 1

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

Ravi Rao High Throughput book

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

Ravi Rao Time Domain book

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

Ravi Rao Frontiers book

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

Selected Publications

Recent Journal Papers

“Editorial: Integrated Approaches to the Measurement, Analysis and Modeling of Cortical Networks “, A.R. Rao, G.A. Cecchi and E. Kaplan, Editorial for the journal Frontiers in Neural Circuits, October 2015, doi: 10.3389/fncir.2015.00061

“Attributed graph distance measure for automatic detection of Attention Deficit Hyperactive Disordered subjects “, S. Dey, A.R. Rao, M. Shah, Frontiers in Neural Circuits, Vol 8, article 64, 2014.

“Exploiting the brain’s network structure in identifying ADHD subjects “, S. Dey , A.R. Rao, M. Shah, Frontiers in Systems Neuroscience, Vol. 6, No, 75, 2012.

“Full-brain sparse auto-regressive functional modeling “, R.Garg, G.A.Cecchi, A.R.Rao, NeuroImage 58 (2011) 416 - 44.

“Statistics of natural scenes and cortical color processing “, G.A. Cecchi, A. R. Rao, Y. Xiao, and E. Kaplan, Journal of Vision, 10(11): 21, 2010.

“An objective function utilizing complex sparsity for efficient segmentation, “ A.R. Rao, G.A. Cecchi, Intl. J. on Intell. Comp. and Cybernetics, 2010, pp. Vol. 3, No. 2, pp. 173 - 206.


Recent Conference Papers

“A framework for analyzing publicly available healthcare data “, A.R. Rao, A. Chhabra, R. Das and V. Ruhil, IEEE Healthcom Conference, 2015, pp. 648-651.

“Augmented Human: Human OS for Improved Mental Function (Position Paper) “, S. Heisig, G. Cecchi, A.R. Rao, I. Rish, AAAI Workshop, 2014.

“Capacity limits in oscillatory networks: implications for sensory coding “, A. R. Rao, G. A. Cecchi, International Joint Conference on Neural Networks, IJCNN, IEEE, 2013.

“Multisensory integration using sparse spatio-temporal encoding “, A. R. Rao, G. A. Cecchi, International Joint Conference on Neural Networks, IJCNN, IEEE, 2013.

“A computational model of early visual cortex using konio-cellular pathway projections “, A. R. Rao, Y. Xiao, IEEE International Joint Conference on Neural Networks, doi: 10.1109/IJCNN.2012.6252425, pp. 1-8, 2012.

“ADHD Classification Using Bag of Words Approach on Network Features “, B. Solmaz, S. Dey , A.R. Rao, M. Shah , Medical Imaging 2012: Image Processing, Proc. of SPIE Vol. 8314, 83144T, doi: 10.1117/12.911598, 2012.

“The effects of feedback and lateral connections on perceptual processing: a study using oscillatory networks “, A.R. Rao, G.A. Cecchi, International Joint Conference on Neural Networks, 2011, pp. 1177-1184.

“A spatio-temporal support vector machine searchlight for fMRI analysis “, A.R. Rao, R.Garg, G.A. Cecchi, IEEE Symposium on Biomedical Imaging, ISBI 2011, pp. 1023-1026.

“Brain as a self-predictor: sparse full-brain autoregressive modeling in fMRI “, R. Garg. G.A. Cecchi, A.R. Rao, IEEE Symposium on Biomedical Imaging, ISBI 2011, pp. 1581-1584.

“Characteristics of Voxel Prediction Power in Full-brain Granger Causality Analysis of fMRI Data “, R. Garg, G.A. Cecchi, A.R. Rao, SPIE Medical Imaging, Proc. of SPIE Vol. 7965, pp. 796502-1:7, 2011.

"Fast computation of functional networks from fMRI activity: a multi-platform comparison", A.R. Rao, R.Bordawekar, G.Cecchi, SPIE Conference on Medical Imaging, Feb. 2011, Proc. SPIE 7962, 79624L (2011); doi:10.1117/12.878368.

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. http://www.nycradiolive.org/?p=694


Short Abstract

Dr. Ravi Rao obtained his PhD in Computer Engineering from the University of Michigan, Ann Arbor, and Bachelors Degree in Electrical Engineering from 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 linkedin.com/in/drravirao for further information.

 

University College

Gildart Haase School of Computer Sciences and Engineering
1000 River Road, (T-MU1-01)
Teaneck, NJ 07666-1914, USA
 201-692-2352