Dr. Anindya Halder

Designation: Associate Professor

Department: Computer Applications

Qualifications:

Academic

  • Ph.D. (Computer Science & Engineering) from Jadavpur University (JU) in 2013. Thesis title "Ant Colony Approach for Certain Tasks of Pattern Recognition". Research work done at Center for Soft Computing Research, Indian Statistical Institute (ISI), Kolkata.
  • Master of Computer Application (M.C.A.) from University of Kalyani in 2005.

Other

  • Qualified NET (Computer Science and Applications).
  • Qualified GATE (Computer Science & IT).

Teaching and Research Experience

  • Associate Professor in Dept. of Computer Science and IT in Cotton University, Guwahati since 21st July, 2022 (On lien from NEHU).
  • Assistant Professor in the Department of Computer Applications, North-Eastern Hill University, Tura Campus, Tura Meghalaya, India from July 2012.
  • Research Scholar in the Center for Soft Computing Research, Indian Statistical Institute, Kolkata from August 2007 to July 2012.
  • Visiting Researcher in Remote Sensing Laboratory, Trento University, Italy from January 2010-June 2010 (on leave from ISI).
  • Project Linked personnel in Machine Intelligence Unit, Indian Statistical Institute (ISI), Kolkata from December 2006 to June 2007 in an International collaborated project (ITPAR) of ISI and Trento University, Italy funded by Department of Science and Technology, Govt. of India.
  • Lecturer and In-Charge, Dept. of Computer Science, KalyaniMahavidyalaya (Kalyani College) Kalyani, Nadia since August 2005 to December 2006.
  • Guest Lecturer (Computer Science) in the Department of Rural Development and Management (INSPARC), University of Kalyani,  Kalyani, Nadia. June to August, 2006.

Administrative positions:

  • Teacher-In-Charge, Dept. of Computer Application from  20.02.2017 to 20.07.2022
  • Member BOS (CA) for three years from 19.05.2016
  • Member BOS (ECE) for three years from 24.06.2016
  • Member School Board (SOT) for two  years from 17.09.2015

Teaching Interests

Machine Learning, Data Mining, Soft Computing, Pattern Recognition, Swarm Intelligence, DBMS, Computer Graphics, Compiler Design, Automata theory, Data Structure, Digital Electronics.

Research Interests

Machine Learning, Soft Computing,Swarm Intelligence, Biomedical Image Analysis, Bioinformatics

Ph.D. Supervision: 4

Degree Awarded:  3 

  • Mr. Ansuman Kumar (Registration #  2670 dated 04.08.2016 of NEHU ) awarded Ph.D. degree from  North-Eastern Hill University on 07.10.2020 for the thesis titled “Effective Prediction of Cancer from Gene Expression Data”.
  • Mr. Nur Alom Talukdar (Registration #  2671 dated 09.08.2016 of NEHU) awarded Ph.D. degree from  North-Eastern Hill University on 05.07.2021 for the thesis titled “Brain Magnetic Resonance Image Analysis using Machine Learning Techniques” .
  • Mr. Rubul Kumar Bania (Registration #  2903 dated 08.08.2017 of NEHU) awarded Ph.D. degree from  North-Eastern Hill University on 07.02.2022 for the thesis titled titled “Detection and Classification of Breast Lesions from Mammogram Images”.

Thesis Submitted :  1 

  • Mr. Rubul Kumar Bania (Registration #  2903 dated 08.08.2017 of NEHU) registered in North-Eastern Hill University on Registration No. 2903) submitted his thesis titled “Detection and Classification of Breast Lesions from Mammogram Images”.

Ongoing : 1  (registered)

  • Ms. Dikme Chisil B. Marak (Registration #  2904, dated 11.08.2017 of NEHU), registered in North-Eastern Hill University, on the  Ph.D. thesis titled  “Machine Learning Techniques for Gene Expression Data Analysis”.

Awards:

  • Won 3rd best paper award (for the paper “Active learning using fuzzy k-NN for cancer classification from microarray gene expression data”) in the National Workshop on Advances in Communication and Computing (WACC), organized by Assam Engineering College, Assam during 26-27 September, 2014.
  • Selected for international travel support scheme for young scientist by Department of Science and Technology (DST), Government of India to present a paper “Ant based semi-supervised classification” in 7thinternational conference on swarm intelligence, ANTS 2010, Brussels, Belgium, during September 8-10, 2010.
  • Won best innovative paper award (for the paper “Ant based supervised and unsupervised land use map generation from remotely sensed images”) in the World Congress on Nature and Biologically Inspired Computing (NaBIC09) organized by Machine Intelligence Research Lab (http://www.mirlabs.org/index.php) at Coimbatore, India in December 9-11, 2009.
  • Obtained Fellowship from CSCR, ISI, Kolkata funded by DST, Govt. of India to carry out research during August 2007 to July 2012.
  • Obtained Fellowship from University of Trento, Italy to carry out research at Remote Sensing Laboratory, University of Trento, Italy during January 2010 to July 2010.

Research Projects

Project Carried Out:   One UGC Major Research Project carried out as Co-PI.

Publications

Research Publications :

  • International Journals (Peer Reviewed): 23  
  • International Conferences (Peer Reviewed): 6
  • National Conference/Workshop/ Seminar (Peer Reviewed): 9    
  • Google Scholar citation: 381  (as on 22.10.2021)
    (>https://scholar.google.co.in/citations?user=uqrUW4EAAAAJ&hl=en)
  • h-index: 12,  i10 index: 14 (as on 05.08.2022)
  • Vidwan Profile: https://vidwan.inflibnet.ac.in/profile/123206

   (I) International Journals (Peer Reviewed)

  1. A. Kumar and A. Halder, “Greedy fuzzy vaguely quantified rough approach for cancer relevant gene selection from gene expression data”, Soft Computing (Springer), Impact factor: 3.732, https://doi.org/10.1007/s00500-022-07312-4, Indexed in SCI, Scopus etc.
  2. A. Kumar and A. Halder,“Semi-supervised ordered weighted average fuzzy-rough nearest neighbour classifier for cancer pattern classification from gene expression data”.International Journal of Biosciences, Vol. 20, No. 5, p. 45-52, 2022. Indexed in Web of Science,UGC CARE.
  3. A. Kumar and A. Halder, “Extreme learning machine for cancer classification from miRNA gene expression data”. International Journal of Biosciences, Vol. 20, No. 5, p. 169-175, 2022. Indexed in Web of Science, UGC CARE.
  4. R. K. Bania, A. Halder, “R-HEFS: Rough set based heterogeneous ensemble feature selection method for medical data classification”, Artificial Intelligence in Medicine (Elsevier), ISSN: 0933-3657  Impact factor: 7.011,  vol 114, 2021,  page 102049 (31 pages)https://doi.org/10.1016/j.artmed.2021.102049Indexed in SCI.
  5. D.C.B. Marak, A. Halder, A Kumar. “Semi-supervised Ensemble Learning for Efficient Cancer Sample Classification from miRNA Gene Expression Data”, New Generation Computing (Springer), 1-27, ISSN: 02883635 /  18827055 Impact factor: 1.113, https://doi.org/10.1007/s00354-021-00123-5Indexed in SCIE.
  6. N.A. Talukdar, A. Halder. “Partially Supervised Kernel Induced Rough Fuzzy Clustering for Brain Tissue Segmentation”. Pattern Recognition and Image Analysis (Springer), ISSN: 1555-6212,vol:31, pages 91–102,2021, https://doi.org/10.1134/S1054661821010156Indexed in Scopus, ACM digital library, UGC CARE, etc.
  7. A. Kumar, A. Halder. “Ensemble-based active learning using fuzzy-rough approach for cancer sample classification”. Engineering Applications of Artificial Intelligence (Elsevier), ISSN: 0952-1976, Impact factor: 7.802, https://doi.org/10.1016/j.engappai.2020.103591, vol. 91 (May), pp, 103591 (12 pages), 2020, Indexed in SCI, Scopus, UGC CARE etc.
  8. R.K.Bania, A. Halder. “Adaptive Trimmed Median Filter for Impulse Noise Detection and Removal with an Application to Mammogram Images”. International Journal of Image and Graphics (World Scientific)https://doi.org/10.1142/S0219467820500321, ISSN: 0219-4678, vol 20 (4),pp. 2050032, 2020, Indexed in SCI expanded, Scopus, UGC CARE etc.
  9. R.K.Bania, A. Halder. “R-Ensembler: A greedy rough set based ensemble attribute selection algorithm with kNN imputation for classification of medical data”. Computer Methods and Programs in Biomedicine (Elsevier), ISSN: 0169-2607, https://doi.org/10.1016/j.cmpb.2019.105122, vol.184  pp 105122 (21 pages), 2020, Impact factor: 7.027, Indexed in SCI, Scopus, PubMed/Medline, UGC CARE etc.
  10. A. Halder, N.A. Talukdar. “Robust brain magnetic resonance image segmentation using modified rough-fuzzy C-means with spatial constraints”. Applied Soft Computing (Elsevier), ISSN: 1568-4946, Impact factor: 8.263, https://doi.org/10.1016/j.asoc.2019.105758, vol. 85(October), pp 1057589 (17 pages), 2019, Indexed in SCI expanded, Scopus, UGC CARE etc.
  11. A. Halder, N.A. Talukdar. “Brain tissue segmentation using improved kernelized rough-fuzzy C-means with spatio-contextual information from MRI”. Magnetic Resonance Imaging (Elsevier), ISSN: 0730-725X, Impact factor: 3.13, https://doi.org/10.1016/j.mri.2019.06.010, vol. 62(October), pp 129-151, 2019,   Indexed in Web of Science, Scopus, PubMed/Medline, UGC CARE etc.
  12. A. Kumar, A. Halder. “Active Learning using Fuzzy-Rough Nearest Neighbour Classifier for Cancer Prediction from Microarray Gene Expression data”. International Journal of Pattern Recognition and Artificial Intelligence (World Scientific), ISSN: 0218-0014, Impact factor: 1.373, https://doi.org/10.1142/S0218001420570013, vol. 34 (1), pp, 2057001 (28 pages), 2019, Indexed in SCI expanded, Scopus, UGC CARE etc.
  13. A. Halder, A. Kumar. “Active Learning using rough fuzzy classifier for cancer predication from microarray gene expression data”. Journal of Biomedical Informatics (Elsevier), ISSN: 1532-0464, Impact factor: 8.0, https://doi.org/10.1016/j.jbi.2019.103136, vol: 92(April), pp. 103136, 2019, Indexed in SCI, Scopus, PubMed/Medline, UGC CARE etc.
  14. A. Kumar, A. Halder. “Ensemble based Fuzzy-Rough Nearest Neighbor Approach for Classification of Cancer from Microarray Data”. International Journal of Research in Advent Technology, E-ISSN: 2321-9637, Vol. 7(5), pp 1287-1294, 2019.
  15. N.A. Talukdar, A. Halder. “Semi-supervised Rough-Fuzzy Clustering for Brain MRI Segmentation”. International Journal of Research in Advent Technology, E-ISSN: 2321-9637, Vol. 7(3), pp 1287-1294, 2019.
  16. A. Kumar, A. Halder. “Cancer Classification from Gene Expression data using Fuzzy-Rough techniques: An Empirical Study”. International Journal of Computer Sciences and Engineering, ISSN: 2347-2693,  vol: 6(6), pp. 415-420, 2018.
  17. A. Kumar, A. Halder. “Semi-supervised Fuzzy Vaguely Quantified Rough Nearest Neighbour Classifier for Cancer Sample Classification from Gene Expression Data”. Journal of Computer and Mathematical Sciences, ISSN: 0976 - 5727, vol: 9(7), pp. 840-849, 2018.
  18. A. Halder, A.K. Upadhyay and S.K. Das. “Numismatic Image Segmentation: An Empirical Study”. International Journal of Computer Applications, ISSN 0975-8887. 160(4):36-39, 2017, doi/10.5120/ijca2017913044.
  19. A. Halder, S. Ghosh, and A. Ghosh. “Aggregation pheromone metaphor for semi-supervised classification”. Pattern Recognition (Elsevier), ISSN: 0031-3203, Impact factor: 8.518, vol: 46(8),  pp. 2239-2248, 2013, https://doi.org/10.1016/j.patcog.2013.01.002Indexed in SCI, Scopus, UGC CARE etc.
  20. A. Halder, A. Ghosh, and S. Ghosh “Supervised and unsupervised landuse map generation from remotely sensed images using ant based systems”. Applied Soft Computing (Elsevier), ISSN: 1568-4946, Impact factor: 8.263, vol: 11(8), pp.5700-5781, 2011, https://doi.org/10.1016/j.asoc.2011.02.030, Indexed in SCI expanded, Scopus, UGC CARE etc.
  21. A. Halder, A. Ghosh, and S. Ghosh. “Aggregation pheromone density based pattern classification”. FundamentaInformaticae (IOS Press), ISSN: 0169-2968, Impact factor: 1.204, vol: 92(4), pp. 345-362, 2009, doi/10.5555/2362717.2362719, Indexed in SCI expanded, Scopus, UGC CARE etc.
  22. S. Ghosh, M. Kothari, A. Halder, A. Ghosh. “Use of aggregation pheromone density for image segmentation”. Pattern Recognition Letters (Elsevier), ISSN: 0167-8655, Impact factor: 4.757, vol: 30(10), pp. 939–949, 2009, https://doi.org/10.1016/j.patrec.2009.03.004Indexed in SCI, Scopus, UGC CARE etc.
  23. A. Ghosh, A. Halder, M. Kothari, and S. Ghosh. “Aggregation pheromone density based data clustering”. Information Sciences (Elsevier), ISSN: 0020-0255, Impact factor: 8.233, vol: 178(13), pp.2816–2831, 2008, https://doi.org/10.1016/j.ins.2008.02.015,  Indexed in SCI, Scopus, UGC CARE etc.

   (II) International Conference (Peer Reviewed)

  1. A. Halder. “Kernel based Rough Fuzzy c-Means clustering optimized using Particle Swarm Optimization”, In Proceedings of the IEEE International Seminar on Computing and Communications, ISBN: 978-1-4673-6707-3 organized by Dept. of CSE, Assam University, Slichar, IEEE CS press, pp.41-48, 2015.
  2. A. Halder, S. Mishra, “Semi-supervised fuzzy K-NN for cancer classification from microarray gene expression data”, In Proceedings of the 1st International Conference on Automation, Control, Energy and Systems, organized by Academy of Technology, West Bengal,  ISSN No.: 978-1-4799-3893-3, IEEE CS press, pp. 1-5,  February 2014.
  3. A. Halder, S. Ghosh and A. Ghosh, “Ant based semi-supervised classification”, In Proceedings of the 7th International Conference on Swarm Intelligence, ANTS 2010, Brussels, Belgium, ISSN No. 978-3-642-15460-7, Springer, LNCS, Volume 6234/2010, pp.376-383, September 2010. (Young Scientist award for international travel support by DST, Govt. of India).
  4. A. Halder, S. Ghosh, and A. Ghosh. “Ant based supervised and unsupervised land use map generation from remotely sensed images”, In Proceedings of the World Congress on Nature and Biologically Inspired Computing (NaBIC’09). ISSN No. 978-1-4244-5612-3, IEEE CS Press, December 2009, pp.158-163 (best innovative paper in the Congress).
  5. A. Halder, S. Ghosh, and A. Ghosh. “Aggregation pheromone density based classification”. In Proceedings of the 10th International Conference on Information Technology (ICIT’08). ISSN No. 978-0-7695-3513-5, IEEE CS Press, pp. 100-105, December 2008.
  6. S.  Dasgupta, S. Bhattacharya, A. Khan, A. Halder, G. Saha, and R.K. Pal. “Disease-Relevant Gene Selection Using Mean Shift Clustering”, In Proceedings of the 8th  International Doctoral Symposium on Applied Computation and Security Systems (ACSS 2021), doi DOI: 10.1007/978-981-16-4294-4_13,  Lecture Notes in Networks and Systems (LNNS), Springer,  vol 14, pp. 151-164. 2021.

   (III) National Conference/Workshop/ Seminar (Peer Reviewed)

  1. A. Halder, “Semi-supervised landuse map generation from remotely sensed images of Kolkata”, In Proceedings of the UGC sponsored National Seminar on “Contemporary Issues on Environments & Development in India and Adjacent Countries”, ISBN:978-81-92847-2-9, pp. 82-90 organized by Kalyani Mahavidyalaya, Kalyani, West Bengal held during September 20-21, 2013.
  2. A. Halder, S. Dey, A. Kumar, Active learning using  fuzzy k-NN for cancer classification from microarray gene expression data, In Proceedings of the National Workshop on Advances in Communication and Computing (WACC), ISSN: 1876-1100, pp.103-113, Lecture Notes in Electrical Engineering (Springer) organized by  Assam Engineering College, Assam during 26-27 September, 2014 (3rd best  paper in the Workshop).
  3. A. Kumar and A. Halder.  Active Learning using Multiclass SVM based on Breaking Ties and Mutual information for Cancer prediction from microarray gene expression data.  In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2018.
  4. N.A. Talukdar and A. Halder.  Brain MRI segmentation suing kernelized Rough Fuzzy C-Means and new ground truth construction techniques for result analysis and validation.  In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2018.
  5. N.A. Talukdar and A. Halder. Brain MRI Segmentation using Clustering Based Techniques: An Empirical Study. In Proceedings of National Conference on Applied Sciences, Sustainable & Evolving Technologies (ASSET), 2018.
  6. R.K. Bania and A. Halder.  Empirical study towards segmentation of mass lesion in digitized mammogram images.  In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2018
  7. N.A. Talukdar and A. Halder. Segmentation of Brain MRI using Unsupervised and Semi-supervised Techniques. In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2019, Chapter 39, pp.232-238 McGraw Hill Education (India).
  8. D.C.B.  Marak and A. Halder. Cancer Sample Classiï¬Â cation from microRNA Gene Expression Data: An Empirical Study. In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2019, Chapter 38, pp.224-231 McGraw Hill Education (India).
  9. R.K. Bania and A. Halder. Automatic Removal of Pectoral Muscle from Mediolateral Oblique View Mammograms. In Proceedings of National Conference on Recent Advances in Science and Technology (NCRAST), 2019, Chapter 40, pp.239-244 McGraw Hill Education (India).

Member Academic/Professional/Scientific Bodies/Societies:

  • Member IEEE
  • Member of International Association of Engineers, Hong Kong
  • Member of Computer Science Teachers Association (CSTA), New York, founded by Association for Computing Machinery (ACM)