Computer Vision
Digital Image Processing
Medical Imaging

 

Research Assistantships: At this time, no paid Research Assistantship positions are available.

 

 COURSES

 

ESE 358 COMPUTER VISION

ESE 568 COMPUTER and ROBOT VISION
ESE457 Fundamentals of   DIGITAL  IMAGE  PROCESSING
ESE558  DIGITAL  IMAGE  PROCESSING

ESE 440 Senior Design I,  ESE 441 Senior Design II,
ESE 599 Graduate Research 

 

PUBLICATIONS  LIST: See Google Scholar webpage

‪Muralidhara Subbarao - ‪Google Scholar

 

 PATENTS ON 3D MEDICAL IMAGING :

       See USPTO database for full list of Patents, and Patent Applications

1. M. Subbarao, Method and Apparatus for High-Sensitivity Single-Photon Emission Computed Tomography, US Patent No. 8008625, Date 08/30/2011 [Download PDF format file].
2. M. Subbarao, Field Image Tomography for Magnetic Resonance Imaging, US Patent No. 8,378,682 B2, Date 02/19/2013  [Download PDF format file].
3. M. Subbarao, "Methods and Apparatuses for 3D Magnetic Density Imaging and Magnetic Resonance Imaging", US Patent No. 8,456,164 B2, Date 06/04/2013.  [Download PDF format file].

Ph.D. Dissertations Supervised

1. Dr. Lu, Ming-Chin         
2.  Dr. Choi, TaeSun             
3. Dr. Wei, Tse-Chung         
4. Dr. Surya, Gopal                  
5. Dr. Tyan, Jenn-Kwei    
6.  Dr. Liu, Yen-Fu            
7.  Dr. Yuan, Ta                      
8.  Dr. Lin, Huei-Yung       
9.  Dr. Soon-Yong Park     
10. Dr. Tao Xian                     
11. Dr. Xue Tu                   
12. Dr.  Youn-Sik Kang    
13. Dr. Shekhar Sastry     

Dr. Muralidhara (Murali) Subbarao  is a Professor of Electrical and Computer Engineering at Stony Brook University.

His research interests are Computer Vision, Digital Image/Signal/Video Processing, 3D Medical Imaging, Integral Equations, Partial Differential Equations, Artificial Intelligence, Machine Learning, Neural Networks, and related areas.

 

He is the inventor of several techniques in Computer Vision, Digital Image Processing, and 3D medical imaging. He invented the Depth-from-Defocus technique that uses arbitrarily defocused images (without requirement of any focused image) for three-dimensional shape recovery. He is also the inventor of Field-Image Tomography applied to MRI and SPECT imaging. In 1991, he invented the S-Transform for spatial-domain convolution and deconvolution of images and signals for shift-invariant kernels or point-spread functions. In 2005, he extended the S-Transform and invented the Rao Transform (renamed Ram Transform in 2026) for forward and inverse filtering of images and signals with shift-variant kernels. This Ram Transform (RT) provided closed-form analytic solutions in the spatial-domain to shift-variant kernels for forward and inverse filtering. This RT was also applicable to solving linear integral equations and partial differential equations. He extended this RT in 2005 to solve non-linear integral equations through General Rao Transform (renamed General Ram Transform or GRT in 2026). In the period Dec. 2025 to May 2026, assisted by AI tools, through intuition, insight, and thoughtfulness, he extended RT and GRT in numerous ways and invented dozens of mathematical tools and techniques for signal/image/video processing, solving integral and partial differential equations, Physics-Informed Neural Nets (PINN), etc. See integralresearch.net for more information on these inventions. In particular, Ram Partial Differential Operator (RPDO) and Ram Master Transform (RMT) together provide a unified framework that is a generalization of over a dozen other transforms like Fourier Transform, Laplace Transform, Mellin Transform, Wavelet Transforms, Ram Complex Spectral Transform, etc. These transforms were generalized to deal with N-dimensional complex, quaternionic, octonionic, and Adelean domains to make them useful in theoretical physics. Further extension of the Ram Transforms theory, algorithms, techniques, and tools, are in progress including topics on Kalman Filter, Particle Filter, Navier-Stokes Equation in fluid-dynamics, Ram Master Neural Nets, Graph Local Ram Neural Nets, Bayes Nets, Bayes Neural Nets, etc. See integralresearch.net for recent updates on these topics.

 

Prof. Subbarao obtained a B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Madras, and an M.S. and a Ph.D., both in Computer Science, from the University of Maryland at College Park. He has been a Principal Investigator of research grants from both industry and the National Science Foundation. He has authored one book, published over 50 papers in professional journals and conferences, and is the sole-inventor on 9 U.S. patents with 4 of them licensed to industry. Over a dozen students have completed their Ph.D. theses under his supervision. He was a principal member and the Chief Computer Scientist of a start-up company in 2000-2001 for online image management.

 

In 2026, assisted by AI tools, he has published over 100 technical reports and filed over 35 provisional patent applications related to the theory and applications of the Ram Transform family of transforms, techniques, tools, and their extensions. See integralresearch.net for details.