Emeritus ProfessorRamakrishn Mukundan

Ramakrishnan Mukundan’s primary research interests are in the areas of computer vision, biomedical image analysis, machine learning, and computer graphics.  His research work in the field of computer graphics spans several areas such as three-dimensional mesh modelling, 3D reconstructions, character animation and inverse kinematics algorithms, real-time rendering, shader based implementations, facial expression modelling, and crowd simulation. He is the author of the following 4 books:

• 3D Mesh Processing and Character Animation, Springer-Nature: Switzerland, Mar 2022, ISBN 978-3030813536.

        (https://link.springer.com/book/10.1007/978-3-030-81354-3)

• Advanced Methods in Computer Graphics, Springer: London, Apr 2012, ISBN 978-1447123392.

        (https://link.springer.com/book/10.1007/978-1-4471-2340-8)

• Computer Graphics Algorithms in Java, Pearson Higher Education (Malaysia), Sprint Print Edition, Apr 2000, ISBN 983-9236-42-3.

        (Out-of-print)

• Moment Functions in Image Analysis – Theory and Applications, World Scientific: Singapore, Sep 1998, ISBN 981-02-3524-0.

        (https://www.worldscientific.com/worldscibooks/10.1142/3838)

In addition to the above books, Mukundan has published 2 book chapters and around 150 technical papers in various journals and conference proceedings (https://dblp.org/pid/95/569.html).

NOTE:  Mukundan has not been actively involved in research supervision since he retired in Dec, 2024.

In the Department of Computer Science and Software Engineering at the University of Canterbury,  Mukundan led the CGMIA research group (Computer Graphics and Medical Image Analysis group) that was involved in the development and implementation of computational pathology algorithms for automated feature extraction and classification of whole slide images of histopathological slides. These projects on clinical applications of biomedical image analysis and machine learning algorithms were done in collaboration with clinical experts in relevant fields.
Mukundan's early research contributions in the area of pattern recognition and analysis include the development of novel feature descriptors called Tchebichef Moments, based on discrete orthogonal polynomials. Tchebichef moment functions have recently found applications in texture analysis, image compression and invariant pattern recognition.  Mukundan also served as the Principal/Senior Supervisor for 14 Ph.D thesis students and 12 Masters thesis students.