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Ramakrishnan, S.
Dr.Mahalingam College Engg. and Technology, Pollachi
Coimbatore, India
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| | Dr. S. Ramakrishnan heads the Department of Information Technology at the Dr. Mahalingam College of Engineering and Technology (MCET) in Pollachi, India. He received his BE in electronics and communication engineering from Bharathidasan University, his ME in communication systems from Madurai Kamaraj University, and his PhD in information and communication engineering from Anna University. He has 22 years of teaching experience, one year of industry experience, and four years of research experience.
Ramakrishnan has published 198 papers in numerous conferences and journals, including IEEE Transactions on Image Processing, IEEE Transactions on Industrial Electronics, IET Image Processing, and Healthcare Technology Letters. He reviews for a number of international journals and serves on the editorial boards of six. He is an Associate Editor at IEEE Access and is acting as a guest editor for special issues of Telecommunication Systems, International Journal of Information and Computer Security, International Journal of Computer Science, and International Journal of Tomography and Statistics.
At Anna University, Ramakrishnan was Convener of the IT Board of Studies (BoS). He successfully guided nine PhD candidates in addition to several BE and ME projects. Ramakrishnan has also organized many national and international conferences, as well as training programs for both faculty members and students. He has delivered a number of guest lectures, including three keynote addresses at IEEE international conferences.
Ramakrishnan’s areas of interest include digital image processing, information security, and soft computing. He has authored 12 books on such topics as image processing, speech processing, pattern recognition, wireless sensor networks, and cryptography. His research has been sponsored by the Council of Scientific & Industrial Research (CSIR), the All India Council for Technical Education (AICTE), and the Defence Research and Development Organisation (DRDO).
Ramakrishnan has been a reviewer for Computing Reviews since 2010. |
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1 - 6 of 6
reviews
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Lie group machine learning
Fanzhang L., Li Z., Zhao Z., Walter de Gruyter & Co., Berlin, Germany, 2018. 533 pp. Type: Book (978-3-110500-68-4)
Machine learning, one of the evergreen fields of electrical engineering, has recently gained momentum and has a number of new and innovative applications. Related fields, such as artificial intelligence, deep learning, brain learning, ...
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Dec 4 2019 |
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 Algebra for cryptologists
Meijer A., Springer International Publishing, New York, NY, 2016. 301 pp. Type: Book (978-3-319303-95-6)
Cryptography is technically synonymous with information security. Providing security features for data and information is the most important concern in a business requirement. Most undergraduate students of electrical engineering and c...
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Mar 20 2017 |
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Three views of logic: mathematics, philosophy, and computer science
Loveland D., Hodel R., Sterrett S., Princeton University Press, Princeton, NJ, 2014. 344 pp. Type: Book (978-0-691160-44-3), Reviews: (2 of 2)
Mathematics is the base for engineering, and various mathematical courses are required for different branches of engineering. For computer science and engineering, mathematics courses such as discrete mathematics, number theory, theory...
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May 7 2014 |
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Data analytics: models and algorithms for intelligent data analysis
Runkler T., VIEWEG, Wiesbaden, Germany, 2012. 147 pp. Type: Book (978-3-834825-88-9)
Data mining and knowledge discovery has become an important field in computer science (CS) over the past few decades. As the amount of available information has been increasing rapidly, the mining of data from the web, in particular fr...
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May 3 2013 |
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A two-sample empirical likelihood ratio test based on samples entropy
Gurevich G., Vexler A. Statistics and Computing 21(4): 657-670, 2011. Type: Article
Statistical models can be either parametric or nonparametric. Identification of an appropriate model for the given data is an interesting research problem and is often used to reduce the dimensionality (for data classification, data cl...
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Mar 8 2012 |
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k-top scoring pair algorithm for feature selection in SVM with applications to microarray data classification
Yoon S., Kim S. Soft Computing 14(2): 151-159, 2009. Type: Article
The classification of gene data is one of the most interesting areas in biomedical signal processing. The efficiency of the classification algorithm depends mainly on feature extraction, feature selection, and the classification mechan...
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Mar 1 2010 |
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