Dr. Indrajit Saha

Department of Computer Science and Engineering

National Institute of Technical Teachers' Training & Research, Kolkata, India

Email: indrajit@nitttrkol.ac.in

Qualifications

2015  Ph.D., Institute of Computer Science, Polish Academy of Sciences, Poland

2014  Ph.D., Computer Science and Engineering, Jadavpur University, India

2007  M.Tech., Computer Science and Engineering, University of Kalyani, India

Publications (Selected)

1. J. P. Sarkar, I. Saha and U. Maulik, “Rough Possibilistic Type-2 Fuzzy C-Means Clustering for MR Brain Image Segmentation”, Applied Soft Computing, Vol. 46, pp. 527-536, 2016.
2. I. Saha, B. Rak, S. S. Bhowmick, U. Maulik, D. Bhattacharjee, U. Kochh, M. Lazniewski, D. Plewczynski, “Binding Activity Prediction of Cyclin-Dependent Inhibitors”, Journal of Chemical Information and Modeling, Vol. 55, No. 7, pp. 1469-1482, 2015.
3. I. Saha, J. P. Sarkar and U. Maulik, “Ensemble based Rough Fuzzy Clustering for Categorical Data”, Knowledge-Based Systems, Vol. 77, pp. 114-127, 2015.
4. I. Saha, J. Zubek, T. Klingstrom, S. Forsberg, J. Wikander, M. Kierczak, U. Maulik and D. Plewczynski, “Ensemble Learning Prediction of Protein-Protein Interactions using Proteins Functional Annotations”, Molecular BioSystems, Vol. 10, No. 4, pp. 820-830, 2014.
5. I. Saha and U. Maulik, “Incremental Learning based Multiobjective Fuzzy Clustering for Categorical Data”, Information Sciences, Vol. 267, pp. 35-57, 2014.
6. S. Dey, I. Saha, U. Maullik and S. Bhattacharyya, “Multi-level Thresholding using Quantum Inspired Meta-heuristics”, Knowledge-Based Systems, Vol. 67, pp. 373-400, 2014.
7. I. Saha, G. Mazzocco and D. Plewczynski, “Consensus classification of Human Leukocyte Antigens class II proteins”, Immunogenetics, Vol. 65, pp. 97-105, 2013.
8. D. Plewczynski, S. Basu and I. Saha, “AMS 4.0: Consensus Prediction of Post-Translational Modifications in Protein Sequences”, Amino Acids, Vol. 43, pp. 573-582, 2012.
9. I. Saha, D. Plewczynski, U. Maulik and S. Bandyopadhyay, “Improved Differential Evolution for Microarray Analysis”, International Journal of Data Mining and Bioinformatics, Vol. 6, No. 1, pp. 86-103,  2012.
10. I. Saha, U. Maulik, S. Bandyopadhyay and D. Plewczynski, “Fuzzy Clustering of Physicochemical and Biochemical Properties of Amino Acids”, Amino Acids, Vol. 43, pp. 583-594, 2012.
11. I. Saha, U. Maulik, S. Bandyopadhyay and D. Plewczynski, “SVMeFC: SVM ensemble Fuzzy Clustering for Satellite Image Segmentation”, IEEE Geoscience and Remote Sensing Letters, Vol. 9, No. 1, pp. 52-55,  2011.
12. I. Saha, U. Maulik, S. Bandyopadhyay and D. Plewczynski, “Improvement of new automatic differential fuzzy clustering using SVM classifier for microarray analysis”, Expert Systems with Applications, Vol. 38, No. 12, pp. 15122-15133 ,  2011.
13. I. Saha, U. Maulik and D. Plewczynski, “A New Multi-objective technique for Differential Fuzzy Clustering”, Applied Soft Computing, Vol. 11, No. 2, pp. 2765-2776,  2010.
14. I. Saha, U. Maulik, S. Bandyopadhyay and D. Plewczynski, “Unsupervised and Supervised learning approaches together for Microarray Analysis”, Fundamenta Informaticae, Vol. 106, No. 1, pp. 45-73,  2010.
15. U. Maulik and I. Saha, “Automatic Fuzzy Clustering using Modified Differential Evolution for Image Classification”, IEEE Transactions on Geoscience and Remote Sensing, Vol. 48, No. 9, pp. 3503-3510, 2010.
16. U. Maulik, S. Bandyopadhyay and I. Saha, “Integrating Clustering and Supervised learning for Categorical Data Analysis”, IEEE Transactions on Systems, Man & Cybernetics - Part A, Vol. 40, No. 4, pp. 664-675, 2010.
17. U. Maulik and I. Saha, “Modified differential evolution based fuzzy clustering for pixel classification in remote sensing imagery”, Pattern Recognition. Vol. 42, No. 9, pp. 2135-2149, 2009.
18. I. Saha and A. Mukhopadhyay, “Improved Crisp and Fuzzy Clustering Techniques for Categorical Data”, IAENG International Journal of Computer Science. Vol. 35, No. 1, Issue-4, pp. 438-450, 2008.