A.  Joshi, Rajshekhar,, Chandran, S., Phadke, S., Jayaraman, V. K., and Kulkarni, B. D., ?Arrhythmia classification using local Holder exponents and support vector machine?, in 1st International Conference on Pattern Recognition and Machine Intelligence,  Statist Inst. Kolkata, India, 2005, vol. 3776, pp. 242-247.

O. C.  Kulkarni, Vigneshwar, R., Jayaraman, V. K., and Kulkarni, B. D., ?Identification of coding and non-coding sequences using local holder exponent formalism?, Bioinformatics, vol. 21, no. 20, pp. 3818-3823, 2005.

A.  Kulkarni, Jayaraman, V. K., and Kulkarni, B. D., ?Knowledge incorporated support vector machines to detect faults in Tennessee Eastman Process?, Computers & Chemical Engineering, vol. 29, no. 10, pp. 2128-2133, 2005.

N. S.  Patil, Shelokar, P. S., Jayaraman, V. K., and Kulkarni, B. D., ?Regression models using pattern search assisted least square support vector machines?, Chemical Engineering Research and Design, vol. 83, no. 8, pp. 1030-1037, 2005.

R.  Kumar, Jayaraman, V. K., and Kulkarni, B. D., ?SVM classifier incorporating simultaneous noise reduction and feature selection: illustrative case examples?, Pattern Recognition, vol. 38, no. 1, pp. 41-49, 2005.

A. M.  Jade, Jayaraman, V. K., and Kulkarni, B. D., ?Improved time series prediction with a new method for selection of model parameters?, Journal of Physics A-Mathematical and General, vol. 39, no. 30, pp. L483-L491, 2006.

A. B.  Gandhi, Joshi, J. B., Jayaraman, V. K., and Kulkarni, B. D., ?Data-driven dynamic modeling and control of a surface aeration system?, Industrial & Engineering Chemistry Research, vol. 46, no. 25, pp. 8607-8613, 2007.

A. B.  Gandhi, Joshi, J. B., Jayaraman, V. K., and Kulkarni, B. D., ?Development of support vector regression (SVR)-based correlation for prediction of overall gas hold-up in bubble column reactors for various gas-liquid systems?, Chemical Engineering Science, vol. 62, no. 24, pp. 7078-7089, 2007.

Rajshekhar, Gupta, A., Samanta, A. N., Kulkarni, B. D., and Jayaraman, V. K., ?Fault diagnosis using dynamic time warping?, in Pattern Recognition and Machine Intelligence, Proceedings, Heidelberger Platz 3, D-14197 Berlin, Germany, 2007, vol. 4815, pp. 57-66.

P.  Kumar, Jayaraman, V. K., and Kulkarni, B. D., ?Granular support vector machine based method for prediction of solubility of proteins on overexpression in Escherichia coli?, in Pattern Recognition and Machine Intelligence, Proceedings, Heidelberger Platz 3, D-14197 Berlin, Germany, 2007, vol. 4815, pp. 406-415.

P.  Mundra, Kumar, M., K. Kumar, K., Jayaraman, V. K., and Kulkarni, B. D., ?Using pseudo amino acid composition to predict protein subnuclear localization: approached with PSSM?, Pattern Recognition Letters, vol. 28, no. 13, pp. 1610-1615, 2007.

J.  Mitra, Mundra, P., Kulkarni, B. D., and Jayaraman, V. K., ?Using recurrence quantification analysis descriptors for protein sequence classification with support vector machines?, Journal of Biomolecular Structure & Dynamics, vol. 25, no. 3, pp. 289-297, 2007.

P. S.  Shelokar, Jayaraman, V. K., and Kulkarni, B. D., ?Multicanonical jump walk annealing assisted by tabu for dynamic optimization of chemical engineering processes?, European Journal of Operational Research, vol. 185, no. 3, pp. 1213-1229, 2008.

M.  Meshram, Kulkarni, A., Jayaraman, V. K., Kulkarni, B. D., and Lele, S. S., ?Optimal xylanase production using Penicilium janthinellum NCIM 1169: a model based approach?, Biochemical Engineering Journal, vol. 40, no. 2, pp. 348-356, 2008.

A. B.  Gandhi, Joshi, J. B., Kulkarni, A. A., Jayaraman, V. K., and Kulkarni, B. D., ?SVR-based prediction of point gas hold-up for bubble column reactor through recurrence quantification analysis of LDA time-series?, International Journal of Multiphase Flow, vol. 34, no. 12, pp. 1099-1107, 2008.

P. P.  Gupta, Merchant, S. S., Bhat, A. U., Gandhi, A. B., Bhagwat, S. S., Joshi, J. B., Jayaraman, V. K., and Kulkarni, B. D., ?Development of correlations for overall gas hold-up, volumetric mass transfer coefficient, and effective interfacial area in bubble column reactors using hybrid genetic algorithm-support vector regression technique: viscous newtonian and non-newtonian liq?, Industrial & Engineering Chemistry Research, vol. 48, pp. 9631-9654, 2009.

A. B.  Gandhi, Gupta, P. P., Joshi, J. B., Jayaraman, V. K., and Kulkarni, B. D., ?Development of unified correlations for volumetric mass-transfer coefficient and effective interfacial area in bubble column reactors for various gas-liquid systems using support vector regression?, Industrial & Engineering Chemistry Research, vol. 48, no. 9, pp. 4216-4236, 2009.

D.  Patil, Raj, R., Shingade, P., Kulkarni, B., and Jayaraman, V. K., ?Feature selection and classification employing hybrid ant colony optimization/random forest methodology?, Combinatorial Chemistry & High Throughput Screening, vol. 12, no. 5, pp. 507-513, 2009.

G. D.  Yadav, Jayaraman, V. K., and Ravikumar, V., ?Festschrift in Honor of Dr. B. D. Kulkarni?, Industrial & Engineering Chemistry Research, vol. 48, no. 21, pp. 9355-9356, 2009.

S.  Karnik, Prasad, A., Diwevedi, A., Sundararajan, V., and Jayaraman, V. K., ?Identification of defensins employing recurrence quantification analysis and random forest classifiers?, Pattern Recognition and Machine Intelligence, Proceedings, vol. 5909, pp. 152-157, 2009.

S.  Karnik, Mitra, J., Singh, A., Kulkarni, B. D., Sundarajan, V., and Jayaraman, V. K., ?Identification of N-glycosylation sites with sequence and structural features employing random forests?, Pattern Recognition and Machine Intelligence, Proceedings, vol. 5909, pp. 146-151, 2009.

R.  Rajappan, Shingade, P. D., Natarajan, R., and Jayaraman, V. K., ?Quantitative structure-property relationship (QSPR) prediction of liquid viscosities of pure organic compounds employing random forest regression?, Industrial & Engineering Chemistry Research, vol. 48, no. 21, pp. 9708-9712, 2009.

A. J.  Kulkarni, Jayaraman, V. K., and Kulkarni, B. D., ?Review on lazy learning regressors and their applications in QSAR?, Combinatorial Chemistry & High Throughput Screening, vol. 12, no. 4, pp. 440-450, 2009.