M. Narasimha Murty (Professor)


PhD (1982, IISc)



SELECTED PUBLICATIONS (each has 20 or more number of citations as per Google Scholar on November 22, 2016)
  • M. N. Murty and G. Krishna, A computationally efficient technique for data clustering, Pattern Recognition, Vol. 12, pp. 153-158, 1980.(No. of citations: 43)
  • M. N. Murty and G. Krishna, A Hybrid clustering procedure for concentric and chain-like clusters, International Journal of Parallel Programming, Vol. 10, pp. 397-412, 1981.(No. of citations: 27)
  • G. P. Babu and M. N. Murty, A Near-optimal initial seed value selectionfor K-Means Algorithm using Genetic Algorithm, Pattern Recognition Letters, 14, pp. 763-769, 1993.(No. of citations: 200)
  • G. P. Babu and M. N. Murty, Simulated annealing for selecting optimal initial seeds in the K-means algorithm, Indian Journal of Pure and Applied Mathematics, Vol. 25, pp. 85-94, 1994. (No. of citations: 27)
  • G. P. Babu and M. N. Murty, Clustering with Evolution Strategies, Pattern Recognition, Vol. 27, No. 2, pp. 321-329, 1994.(No. of citations: 189)
  • M. Prakash and M. N. Murty, A Genetic Algorithm for Selection of (Near-) Optimal Subsets of Principal Components for Discrimination, Pattern Recognition Letters, Special Issue on Genetic Algorithms, Vol. 16, pp. 781-787, 1995.(No. of citations: 37)
  • M. N. Murty and A. K. Jain, Knowledge-Based Clustering Scheme for Collection Management and Retrieval of Library Books, Pattern Recognition, Vol. 28, No. 8, pp. 949-963, 1995.(No. of citations: 40)
  • M. Prakash and M. N. Murty, Growing Subspace Pattern Recognition Methods and their Neural-Network Models, IEEE Trans. on Neural Networks, Vol. 8, No. 1, pp. 161-168, 1997.(No. of citations: 28)
  • K. Krishna and M. N. Murty, Genetic K-Means Algorithm, IEEE Trans. on SMC, Vol. 29, No. 3, pp.433-439, June 1999.(No. of citations: 842)
  • V. E. Ramesh and M. N. Murty, Off-line Signature Verification Using Genetically Optimized Weighted Features, Pattern Recognition, Vol. 32, No. 2, pp. 217-233, 1999.(No. of citations: 96)
  • A. K. Jain, M. N. Murty, and P. J. Flynn, Pattern Clustering: A Review, ACM Computing Surveys, pp. 264-323, Sept. 1999.(no. of citations: 12008)
  • V. S. Ananthanarayana, M. N. Murty, and D. K. Subramanian, Scalable, Distributed and Dynamic Mining of Association Rules, In Proc. HIPC, Bangalore, 2000. (no. of citations: 37)
  • T. R. Babu and M. N. Murty, Comparison of Genetic Algorithm Based Prototype Selection Schemes, Pattern Recognition, Vol. 34, pp. 523-525, 2001.(No. of citations: 79)
  • V. Vijaya Saradhi and M. N. Murty, Bootstrapping for efficient handwritten digit recognition, Pattern Recognition, Vol. 34, pp. 1047-1056, 2001.(No. of citations: 21)
  • V. Susheela Devi and M. N. Murty, Incremental Prototype Building Technique, Pattern Recognition, Vol. 35, pp. 505-513, 2002.(No. of citations: 83)
  • S. V. N. Viswanathan and M. N. Murty, SSVM: a Simple SVM algorithm, In Proc. of IJCNN, 2002. (no. of citations: 51)
  • V. S. Ananthanarayana, M. N. Murty, and D. K. Subramanian, Tree Structure for Efficient Data Mining Using Rough Sets, Pattern Recognition Letters, Vol. 24, pp.833-849, 2003.(No. of citations: 86)
  • J. N. Manjunatha, K. R. Sivaramakrishnan, R. K. Pandey, and M. N. Murty, Citation Prediction Using Time Series Appraoch: KDD Cup 2003 (task 1), SIGKDD Explorations, Vol. 5, pp. 152-153, 2003.(winning entry)
  • S. Asharaf and M. N. Murty, An Adaptive Rough Fuzzy Single Pass Algorithm for Clustering Large Data Sets, Pattern Recognition, Vol. 36, pp. 3015-3018, 2003.(No. of citations: 65)
  • S. V. N. Vishwanathan, A. J. Smola, and M. N. Murty, Simple SVM, In Proceedings of Intl. Conf. on Machine Learning, pp. 760-767, 2003. (no. of citations: 135)
  • S. Asharaf and M. N. Murty, A rough fuzzy approach to Web usage Categorization, Fuzzy Sets and Systems, Vol. 16, pp. 119-129, 2004.(No. of citations: 35)
  • P. A. Vijaya, M. N. Murty, and D. K. Subramanian, Leaders-Subleaders: An Efficient Hierarchical Clustering Algorithm for Large Datasets, Pattern Recognition Letters, Vol 25, pp. 503 - 511, 2004.(No. of citations: 76)
  • S. Asharaf, S. K. Shevade and M. N. Murty, Rough support vector clustering, Pattern Recognition, Vol. 38, pp. 1779-1783, 2005.(No. of citations: 48)
  • J. Saketha Nath, Chiranjib Bhattacharyya, M. Narasimha Murty: Clustering based large margin classification: a scalable approach using SOCP formulation,In Proc. KDD 2006. (no. of citations: 22)
  • S. Asharaf, M. N. Murty, and S. K. Shevade, Rough set based incremental clustering of interval data, Pattern Recognition Letters, Vol. 27, pp. 515-519, 2006.(No. of citations: 76)
  • S. Asharaf, M. N. Murty, and S. K. Shevade, Multiclass core vector machine, Proceedings of the 24th international conference on Machine learning, 41-48, 2007. (No. of citations: 47)
  • S. Asharaf, M. N. Murty, and S. K. Shevade, Rough set based incremental clustering of interval data, Pattern Recognition Letters, Vol. 27, pp. 515-519, 2006.(No. of citations: 76)

    • M. N. Murty and V. Susheela Devi, Pattern Recognition: An Algorithmic Approach, Springer, 2011. (Co-published with Universities Press (India) Pvt. Ltd.),
    • M. N. Murty and V. Susheela devi, Pattern Recognition, Web course, NPTEL, 2012. (http://nptel.iitm.ac.in/courses.php)
    • Pradipta Maji, Ashish Ghosh, M. Narasimha Murty, Kuntal Ghosh, Sankar K. Pal (Eds.): Pattern Recognition and Machine Intelligence - 5th International Conference, PReMI 2013, Kolkata, India, December 10-14, 2013. Proceedings. Lecture Notes in Computer Science 8251, Springer 2013, ISBN 978-3-642-45061-7
    • T. R. babu, M. N. Murty nd S. V. Subrahmanya, Compresion Schemes for Mining Large Datasets: A Machine Learning Perspective, Springer, 2013.
    • M. N. Murty and V. Susheela Devi, Introduction to Pattern Recognition and Machine Learning, IISc Lecture Notes Series, World Scientific, 2015.
    • M. N. Murty and R. Raghava, Support Vector Machines and Perceptrons: Learning, Optimization and Application to Social Networks, Springer Briefs in Computer Science, 2016.


    • M. N. Murty and A. Negi, A Knowledge-Based Approach to Cluster Analysis, in Systems and Signal Processing, pp. 747-755, edited by R. N. Madan, N. Viswanadham, and R. L. Kashyap, Oxford and IBH Publishing Company, New Delhi, 1991.
    • V. Sridhar and M. N. Murty, Knowledge Processing Under Uncertainty, in Knowledge Based Systems, pp. 157-189, edited by S. G. Tzafestas, World Scientific, London, 1997.
    • V. Susheela Devi and M. N. Murty, Handwritten Digit Recognition Using Soft Computing, in Soft-Computing for Image Processing, pp. 506-524, edited by S. K. Pal, A. Ghosh and M. K. Kundu, Physica-Verlag, Heidelberg, 2000.
    • Andreas Moser and M. N. Murty, On the scalability of Genetic Algorithms to very large-scale feature selection, in Real-World Applications of Evoltionary Computing, pp. 309-31, edited by Stefano Cagnoni, Springer, LNCS: Vol. 1803, 2000.
    • M. N. Murty, Clustering Large Data Sets, in Soft Computing Approach to Pattern Recognition and Image Processing, pp. 41-63, edited by A. Ghosh and S. K. Pal, World-Scientific, New Jersey, 2002.
    • E. Diday and M. N. Murty, Symbolic Data Clustering, in Encyclopedia of Data Warehousing and Mining, pp. 1087-1092, Edited by J. Wang, Idea Group Inc., 2005.
    • P. Viswanath, M. N. Murty, and S. Bhatnagar, Pattern Synthesis for Large-Scale Pattern Classification, In Encyclopedia of Data Warehousing and Mining, pp. 902-906, Edited by. J. Wang, Idea Group Inc., 2005.
    • M. N. Murty, B. Rashmin and C. Bhattacharyya, Clustering based on Genetic Algorithms, In Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases, pp. 137-159, Edited by Ashish Ghosh, Satchidananda Dehuri, and Susmita Ghosh, Springer, 2008.
    • E. Thirumaran and M. N. Murty, Collaborative Filtering Based Recommendation Systems, in Text and Web Mining Technologies, Edited by M. Song and Y-F Brook Wu, 2009.
    • V. Suresh Babu, P. Viswanath and M. N. Murty, Non-Parametric Methods for Large Datasets, In Encyclopedia of Data Warehousing and Mining, pp. 1708-1713, Edited by. J. Wang, Idea Group Inc., 2009.
    • N. Ranga Suri, M. N. Murty and G. Athithan, Data Mining Techniques for Outlier Detection, in Visual Analytics and Interactive Technologies: Data, Text and Web Mining Applications, pp. 19-38, Edited by Q. Zhang, R. Segall, and M. Cao, IGI Global, 2011.
    • T. Ravindra Babu, M. N. Murty, and S. V. Subrahmanya, Quantization based Sequence Generation and Subsequence Pruning for Data Mining Applications, in Pattern Discovery Using Sequence Data Mining: Applications and Studies, pp. 94-110, Edited by Pradeep Kumar, P. Radha Krishna and S. Bapi Raju, 2012.


    • B. Shekar, M. N. Murty, and G. Krishna, Pattern clustering: an artificial intelligence approach, Proceedings of the 10th International Joint Conference on Artificial Intelligence, Milano, Italy, Aug. 1987.
    • V. Sridhar, M. N. Murty, and G. Krishna, A logical model for decision-making, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Dec. 1989.
    • S. H. Srinivasan and M. N. Murty, Validation in distributed representation, in International Joint Conference on Neural Networks, Singapore, pp. 36-42, November 1991.
    • G. P. Babu and M. N. Murty, Probabilistic connectionist approaches for the design of good communication codes, In the Proc. of the IJCNN, Japan, 1993.
    • G. P. Babu and M. N. Murty, Controlled offspring generation in evolutionary programming, in Proc. of the Third Annual Conf. on Evolutionary Programming, San Diego, 1994.
    • S. V. N. Vishwanathan and M. N. Murty, Geometric SVM: a fast and intuitive SVM algorithm. In Proc. Intl. Conf. Pattern Recognition, Vol. 2, pp. 56-59, 2002.
    • D. Ambedkar, M. N. Murty, and S. Bhatnagar, Quotient evolutionary space: abstraction of evolutionary process w.r.t macroscopic properties, In Proceedings of IEEE Congress on Evolutionary Computation, 2003.
    • D. Ambedkar, M. N. Murty, and S. Bhatnagar, Cauchy annealing schedule: an annealing schedule for Boltzmann selection scheme in evolutionary algorithms, In Proceedings of IEEE Congress on Evolutionary Computation (CEC'2004), 2004.
    • P. A. Vijaya, M. N. Murty, and D. K. Subramanian, An efficient technique for protein sequence clustering and classification, In Proc. of 17th ICPR (Int. Conf. in Pattern Recognition), Vol. 2, pp. 447-450, 2004.
    • P. Viswanath, M. N. Murty, and S. Bhatnagar, A pattern synthesis technique with an efficient nearest neighbor classifier for binary pattern recognition, In Proceedings of International Conference on Pattern Recognition (ICPR), Vol. 4, pp. 416-419, 2004.
    • D. Dipti, M. Vidyasagar, and M. N. Murty, Bimodal projection-based features for pattern classification, In Proceedings of the IJCNN at the IEEE world Congress on Computational Intelligence, 2006.
    • S. Asharaf, S. K. Shevade, and M. N. Murty, Scalable non-linear support vector machine using hierarchical clustering, ICPR Vol. 1, pp. 908-911, 2006.
    • S. Asharaf, M. N. Murty, and S. K. Shevade, Cluster based core vector machine, In Proceedings of Intl. Conf. on Data Mining, 2006.
    • S. Asharaf, M. N. Murty, and S. K. Shevade, Multiclass Core Vector Machine, in the Proceedings of the 24th ICML, June 2007.
    • B. Rashmin, J. Saketha Nath, K. Suresh Kumar, K. Sivaramakrishnan, C. Bhattacharyya, and M. N. Murty, Focussed Crawling with Scalable Ordinal regression solvers, in the Proceedings of the 24th ICML, June 2007.
    • A. P. Yogananda, M. N. Murty, and Lakshmi Gopal, A fast linear separability test by projection of positive points on subspaces, in the Proceedings of the 24th ICML, June 2007.
    • R. Arun, V. Suresh, R. Saradha, M. N. Murty, and C. E. Veni Madhavan, Stopwords and Stylometry : A Latent Dirichlet Allocation Approach, In NIPS Workshop on Applications for Topic Models: Text and Beyond, 2009.
    • Ambedkar Dukkipati, Abhay Kumar Yadav, and M. N. Murty, Maximum entropy model based classification with feature selection, ICPR 2010.
    • Geetha Manjunath, M. N. Murty, and Dinkar Sitaram, A Practical Heterogeneous Classifier for Relational Databases, ICPR 2010.
    • R. Arun, V. Suresh, C. E. Veni Madhavan, M. N. Murty: On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations, PAKDD 2010.
    • Govind Sharma and M. Narasimha Murty, Mining Sentiments from Songs Using Latent Dirichlet Allocation, IDA 2011.
    • Arghya Roy Chaudhuri and M. Narasimha Murty, On the relation between K-means and PLSA, ICPR 2012.
    • Deepak Gujraniya, M. Narsimha Murty: Efficient classification using phrases generated by topic models. ICPR 2012.



Data Mining
Topics in Pattern Recognition
Data Structures and Algorithms
Artificial Intelligence
Information Retrieval


PhD Students.
  • B. Shekar: A Knowledge-Based Approach to Pattern Clustering, 1988 (with Prof. G. Krishna).
  • S.H. Srinivasan: Studies in Learning and Representation in connectionist Networks, 1993.
  • V. Sridhar: Labelled clustering and its Applications, 1993.
  • G. Phanendra Babu: Evolutionary and Connectionist Approaches to Pattern Clustering, 1994 (with Prof. S. Sathiya Keerthi).
  • M. Prakash: Learning in Subspace Methods Using weighted and Multi-Subspace Representations, 1996.
  • S. Bhattacharya: A Novel Scheme for Speech Synthesis, 1997.
  • V. Susheela Devi: Optimal Prototype Selection for Efficient Pattern Classification, 2001 (with Prof. Indraneel Sen).
  • K. R. K. Murthy: Sharable Instructable Agent for Information Filtering, 2001 (with Prof. S. Sathiya Keerthi).
  • C. Bhattacharyya: Plefka's Mean-Field Theory and Belief Networks, 2002 (with Prof. Sathiya Keerthi).
  • S. K. Shevade: Some Efficient Algorithms for Support Vector Machines, 2001 (with Prof. S. Sathiya Keerthi).
  • Dipti Deodhare: Bimodal Projections Based Features for High Dimensional Pattern Classification, 2001 (with Dr. M. Vidyasagar).
  • V. S. Ananthanarayana: Knowledge-Based Mining of Multi-Databases for Associations, 2001 (with Prof. D. K. Subramanian).
  • S. V. N. Vishwanathan: Kernel Methods: Fast Algorithms and Real Life Applications, 2003.
  • P. Viswanath: Pattern Synthesis Techniques and Compact Data Representation Schemes for Efficient Nearest Neighbor Classification, 2005 (with Dr. S. Bhatnagar) (Awarded the Best Thesis Award).
  • P. A. Vijaya: Efficient Hierarchical Clustering Techniques for Pattern Classification, 2005 (with Prof. D. K. Subramanian).
  • D. Ambedkar: On generalized Measures of Information with Maximum and Minimum Entropy Prescriptions, 2006(with Dr. S. Bhatnagar).
  • T. Ravindra Babu: Efficient Schemes for Large-Scale Pattern Classification, 2006 (with Dr. V. K. Agrawal).
  • S. Asharaf: Efficient Kernel Methods for Large Scale Classification, 2007 (with Dr. S. K. Shevade)(IBM Outstanding PhD student award).
  • Geetha Manjunath, Semantic Analysis of Web Pages for Task-Based Personal Web Interactions, 2013 (with Dr. Dinkar Sitaram, HP Research Labs, Bangalore).
  • N. N. Ranga Suri, Outlier Detection with Applications in Graph Data Mining, 2014 (with Dr. Athithan, CAIR, Bangalore).
  • Shyni Thomas, Planning based on Informed Search (In Progress) (with Dr. Dipti Deodhare, CAIR, Bangalore).
  • Govind Sharma, Document Summarization(In Progress).
  • Sharad Nandanawar, Topic Models(In Progress).

M. Sc. (Engg.) Students:

  • C. Srinivas: Pattern classification using conjunctive conceptual clustering procedures, 1986.
  • S. Choudhury: Hierarchical Data Structures for Pattern Recognition, 1987.
  • Malini K. Bhandaru: Learning from examples using Hierarchical Counterfactual Expressions, 1989.
  • Atul Negi: Algorithmic knowledge for a knowledge-based clustering environment, 1989.
  • V. Rajasekar: Intelligent Backtracking in Logic Programs, 1990.
  • V.S.S. Suresh Babu: Preprocessing for Optimal Multilevel clustering, 1990.
  • Francis Joy: Reason Maintenance and Logic, 1993.
  • V. Vijaya Saradhi: Pattern Representation and Prototype Selection for Handwritten Digit Recognition, 1999.
  • P. Ramanujam: Development of a General-Purpose Sanskrit Parser, 1999 (with Prof. Nagaraj Shenoy).
  • T. Ravindra Babu: Data Clustering and Evolutionary Algorithms for Data Mining, 2000 (with Dr. M. Sambasiva Rao).
  • D. Ambedkar: ACE-Model: A Conceptual Evolutionary Model for Evolutionary Computation and Artificial Life, 2002.
  • B. N. Ranganath: Efficient Frequent Closed Itemset Algorithms with Applications to Stream Mining and Classification, 2009.
  • Govind Sharma: Sentiment-Driven Topic Analysis of Song Lyrics, 2012.



  • Leader, Team winning the KDD Cup 2003 (task 1) organized by the Cornell University
  • The paper "Pattern Clustering: A Review" coauthored by him is the most frequently downloaded article during 2004, 2005, and 2006 from ACM publications (Source: Communications of the ACM).
  • Alumni Award for Excellence in Research for Engineering, IISc, Bangalore, 2007.
  • Fellow, Indian National Academy of Engineering (INAE), India, 2008.
  • IISc Colloquium, "Clustering Large Data sets", delivered on March 29, 2010.
  • Associate Editor, Sadhana, An Official Journal of the Indian Academy of Sciences, published by Springer.
  • Fellow, The National Academy of Sciences (NASI), India, 2011.



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