Ibrahim Venkat, Associate Professor Dr.

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  Associate Professor Dr

  Email : This email address is being protected from spambots. You need JavaScript enabled to view it.

  Tel : +604 653 ****
  Fax : +604 653 3335
  Room : 
  
  School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang

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  Research Interest

  Biometrics, Computer Vision, Computational, Intelligence

  Specialization

  Recognizing Complex Faces and Gaits using Novel Probabilistic Models

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Biography

PhD Heriot-Watt University, UK, 2007- 10
MSc (Artificial Intelligence) Universiti Malaysia Terengganu, Malaysia, 2005-06
BSc (Mathematics, First Class) Madurai Kamaraj University, India, 1986-89 

 

Interests

Biometrics
Computer Vision
Computational Intelligence

We have funding for a Ph.D. student to perform research on ''3D biometrics / Object recognition". Candidates with proven research record are welcome to contact me.

We are interested in developing computational models for the problem of recognizing objects under uncertainty. Even human vision has certain degree of uncertainty in recognizing complex objects. Our research involves studies from interrelated fields viz., Biometrics, Computer Vision, Computational Intelligence, Pattern Recognition, Machine Learning, Probabilistic Modelling and Image Processing. When 'Deep Blue', a machine, could beat reigning world chess champion, why not machine vision could surpass human vision? Specifically, we have been investigating the following research problems:

a) What is the key cognitive mechanism that governs humans to recognize complicated objects which are prone to uncertainty elements such as occlusion and noise?

b) If machines can learn this mechanism, can they advance ahead of humans?

This motivated us to invent award winning biometric products such as BORAHMAN...If you want to know more about our inventions and innovations, please go through our publications...Still if you are thrilled, don't hesitate to contact us...

We have strong links with the Intelligent Systems Lab of Heriot-Watt University as we use to colloborate with Prof. Philippe De Wilde http://www.macs.hw.ac.uk/~pdw/

Acknowledgements

We whole heartedly acknowledge (Syukur) the following organizations who offered considerable research funding for our research work

a) School of MACS, HWU, UK http://www.macs.hw.ac.uk/ (James Watt Scholarship)

b) TATiUC, Malaysia http://www.tatiuc.edu.my/

c) USM, Malaysia http://www.cs.usm.my

Projects

Membrane Computing Based Models For Image Analysis

Discovering and Expoiting Causal Relationships to Recognize Complex Biometric Signatures

Image Generation, Recognition and Reconstruction Based on Certain Theoretical Models

Publications

2017

Mohd Ibrahim A., Venkat I., Wilde P.D.,"Uncertainty in a spatial evacuation model Physica A: Statistical Mechanics and its Applications",Vol. 479, Pg.485-497

Isawasan P., Muniyandi R.C., Venkat I., Subramanian K.G. Array-rewriting P systems with basic puzzle grammar rules and permitting features Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and 10105 LNCS, pg. 272-285

2016

Azhar Mohd Ibrahim, Ibrahim Venkat, K.G. Subramanian, Ahamad Tajudin Khader, Philippe De Wilde, 2016. Intelligent Evacuation Management Systems: A Review, ACM Transactions on Intelligent Systems and Technology, Vol. 7, Issue 3, 1-27. [Citation Indexed Journal (SCOPUS/ISI/SCI/SSCI/AI)][Q2]

Badr Mohammed Lahasan, Mohammed Azmi Al-Betar, Ibrahim Venkat, Syaheerah Lebai Lutfi, Philippe De Wilde, 2016. Recognizing Faces Prone to Ccclusions and Common Variations using Optimal Face Subgraphs, Applied Mathematics and Computation, Vol. 283, 316-332. [Citation Indexed Journal (SCOPUS/ISI/SCI/SSCI/AI) ][Q1]

Tan Joi San, Ibrahim Venkat, Paul T. Jayaprakash, 2016. Computer-aided Craniofacial Superimposition using a Quasi-Newton Iterative Closest Point Approach, ScienceAsia, Vol. 42, Issue 2, 136-145. [Citation Indexed Journal (SCOPUS/ISI/SCI/SSCI/AI)][Q3]

Bharati Rajan, Ibrahim Venkat, K.G. Subramanian, 2016. Foreword to the Special Focus on Graph Theory and Applications, Mathematics Computer Science, Vol. 10, Issue 2, 207-208. [Citation Indexed Journal (SCOPUS/ISI/SCI/SSCI/AI)]

2015

K.G. Subramanian, Pradeep Isawasan, Rahmat Budiarto, Ibrahim Venkat, 2015. Binary Image Reconstruction Based on Prescribed Numerical Information, Acta Mathematicae Applicatae Sinica, English Series , Vol. 31, No. 2 (2015) DOI: 10.1007/s10255-015-0482-4. ISSN: 0168-9673, 519–528. [Citation Indexed Journal (SCOPUS/ISI/SCI/SSCI/AI)]

Ashraf Y. A. Maghari, Iman Yi Liao, Ibrahim Venkat, Bahari Belaton, 2015. Distance-based 3D Face Reconstruction using Regularization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4th International Visual Informatics Conference, IVIC 2015; 1. Bangi; Malaysia, Volume 9429, Pages 476-493. [Citation Indexed Proceedings (SCOPUS/ISI/SCI/SSCI/AI)]

Tan Joi San, Ibrahim Venkat, Bahari Belaton, 2015. An Analytical Curvature B-Spline Algorithm for Effective Curve Modeling. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4th International Visual Informatics Conference, IVIC 2015; 17. Bangi; Malaysia, Volume 9429, Pages 283-295. [Citation Indexed Proceedings (SCOPUS/ISI/SCI/SSCI/AI)]

Pradeep Isawasan, Ibrahim Venkat, R.C. Muniyandi, K.G. Subramanian, 2015. A Membrane Computing Model for Generation of Picture Arrays. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4th International Visual Informatics Conference, IVIC 2015; Bangi. Bangi; Malaysia, Volume 9429, Pages 155-165 . [Citation Indexed Proceedings (SCOPUS/ISI/SCI/SSCI/AI)]

Yap Fa Toh, Ibrahim Venkat, 2015. Classification of Speech Signals as Voiced-unvoiced-silence classes based on Quasi-period Characteristics. Proceedings (eBook) International Workshop on Graph Algorithms (IWGA2015). Penang, Malaysia, 13 May, 2015, pp. 203-206. eISBN 978-967-394-214-5, pp 249-253.