Research

Research Objective: Rough Set Theory has emerged in last forty years as a mathematical framework for approximate reasoning with wide range of applications for Data Mining, Machine Learning and Soft Computing. The objective of my research is to utilize the principles of rough sets and its extensions for building feature subset selection (Reduct computation) approaches, evolve approaches for developing hybrid soft computing solutions, build MapReduce based scalable soluctions for meeting the requirements of Big Data scenario.


Research Areas

  1. Rough Set Theory

  2. Data Mining

  3. Fuzzy-Rough Sets

  4. Hybrid Soft computing

  5. Big Data Engineering through Apache Spark

  6. Distributed Machine Learning

Research Publications

List of Journals

  1. Sai Prasad, P. S. V. S. and Raghavendra Rao, C. An Efficient Approach for Fuzzy Decision Reduct Computation. Transactions on Rough Sets XVII (2014). 82-108. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-54756-0_5

  2. Sai Prasad, P. S. V. S. and Raghavendra Rao, C. Non-persistent stratified sampling based IQRA_IG for scalable reduct generation. International Journal of Granular Computing, Rough Sets and Intelligent Systems(2014). https://doi.org/10.1504/IJGCRSIS.2014.060844

  3. Kumar, Anil and Prasad, PSVS Sai. Scalable fuzzy rough set reduct computation using fuzzy min-max neural network preprocessing. IEEE Transactions on Fuzzy Systems (2020) Vol 28. Pages 953-964. IEEE. doi: 10.1109/TFUZZ.2020.2965899.

  4. Kumar, Anil and Prasad, PSVS Sai. Incremental fuzzy rough sets based feature subset selection using fuzzy min-max neural network preprocessing. International Journal of Approximate Reasoning (2021) Vol 139 Pages 69-87. Elsevier. https://doi.org/10.1016/j.ijar.2021.09.006

  5. Kumar, Anil and Prasad, PSVS Sai. Enhancing the scalability of fuzzy rough set approximate reduct computation through fuzzy min-max neural network and crisp discernibility relation formulation. Engineering Applications of Artificial Intelligence(2022) Vol 110. Pages 104697. Elsevier. https://doi.org/10.1016/j.engappai.2022.104697

  6. Sowkuntla, Pandu and Dunna, Sravya and Prasad, PSVS Sai. MapReduce-based parallel attribute reduction in Incomplete Decision Systems. Knowledge-Based Systems (2021) 213, 106677. Elsevier. https://doi.org/10.1016/j.knosys.2020.106677

  7. Sowkuntla, P., Prasad, P.S.V.S.S. MapReduce based parallel fuzzy-rough attribute reduction using discernibility matrix. Applied Intelligence 52, 154–173 (2022). https://doi.org/10.1007/s10489-021-02253-1

  8. Sowkuntla, Pandu and Prasad, PSVS Sai. MapReduce based improved quick reduct algorithm with granular refinement using vertical partitioning scheme. Knowledge-Based Systems (2020). 189, 105104. Elsevier. https://doi.org/10.1016/j.knosys.2019.105104

  9. Bar, Abhimanyu, Kumar, A. & Sai Prasad, P.S.V.S. Coarsest granularity-based optimal reduct using A* search. Granular Computing. (2022). https://doi.org/10.1007/s41066-022-00313-6

  10. Bar, Abhimanyu, Sai Prasad, P.S.V.S.S. Approaches for coarsest granularity based near-optimal reduct computation. Applied Intelligence (2022). https://doi.org/10.1007/s10489-022-03571-8


List of Conferences

  1. Prasad, P.S.V.S.S., Rao, C.R. (2009). IQuickReduct: An Improvement to Quick Reduct Algorithm. RSFDGrC 2009. Lecture Notes in Computer Science(LNCS), vol 5908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10646-0_18

  2. Bindu, K. Hima and Sai Prasad, P. S. V. S. and Rao, C. Raghavendra. Hybrid Decision Tree Based on Inferred Attribute. Association for Computing Machinery(ACM), 2010. https://doi.org/10.1145/1858378.1858379

  3. Rama Devi Yellasiri, P Venu Gopal, PSVS Sai Prasad. Impact analysis of Jensen and Sk pal fuzzification in classification. Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India. 2010. https://dl.acm.org/doi/10.1145/1858378.1858380

  4. Y Rama Devi, P Venu Gopal, PSVS Sai Prasad. Fuzzy Rough Data Reduction Using SVD. International Journal of Computer and Electrical Engineering, Vol. 3, No. 3, June 2011.

  5. Prasad, P.S.V.S.S., Bindu, K.H., Rao, C.R. (2011). Incremental Learning in AttributeNets with Dynamic Reduct and IQuickReduct. Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(LNCS), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_27

  6. P.S.V.S., S.P., Raghavendra Rao, C. (2011). Extensions to IQuickReduct. Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2011. Lecture Notes in Computer Science(LNCS), vol 7080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25725-4_31

  7. Sai Prasad, P.S.V.S., Raghavendra Rao, C. (2012). Scalable Improved Quick Reduct: Sample Based. Rough Sets and Knowledge Technology. RSKT 2012. Lecture Notes in Computer Science(LNCS), vol 7414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31900-6_5

  8. P.S.V.S. Sai Prasad, C Raghavendra Rao . Seed-based fuzzy decision reduct for hybrid decision systems. 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://ieeexplore.ieee.org/document/6622535

  9. S., R., Sai Prasad, P.S.V.S., Chillarige, R.R. (2014). A New Preprocessor to Fuzzy c-Means Algorithm. In: Murty, M.N., He, X., Chillarige, R.R., Weng, P. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2014. Lecture Notes in Computer Science(LNCS), vol 8875. Springer, Cham. https://doi.org/10.1007/978-3-319-13365-2_12

  10. Praveen Kumar Singh, PSVS Sai Prasad. Scalable quick reduct algorithm: Iterative MapReduce approach. Proceedings of the 3rd IKDD Conference on Data Science, 2016. https://dl.acm.org/doi/10.1145/2888451.2888476

  11. Ghosh, S., Sai Prasad, P.S.V.S., Rao, C.R. (2016). An Efficient Gaussian Kernel Based Fuzzy-Rough Set Approach for Feature Selection. In: Sombattheera, C., Stolzenburg, F., Lin, F., Nayak, A. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2016. Lecture Notes in Computer Science(), vol 10053. Springer, Cham. https://doi.org/10.1007/978-3-319-49397-8_4

  12. Shashikant Ilager, PSVS Sai Prasad. Scalable mapreduce-based fuzzy min-max neural network for pattern classification. Proceedings of the 18th International Conference on Distributed Computing and Networking. https://dl.acm.org/doi/10.1145/3007748.3007776

  13. Sai Prasad, P.S.V.S., Bala Subrahmanyam, H., Singh, P.K. (2017). Scalable IQRA_IG Algorithm: An Iterative MapReduce Approach for Reduct Computation. In: Krishnan, P., Radha Krishna, P., Parida, L. (eds) Distributed Computing and Internet Technology. ICDCIT 2017. Lecture Notes in Computer Science(), vol 10109. Springer, Cham. https://doi.org/10.1007/978-3-319-50472-8_5

  14. Ghosh, S., Sai Prasad, P.S.V.S., Rao, C.R. (2017). Third Order Backward Elimination Approach for Fuzzy-Rough Set Based Feature Selection. In: Shankar, B., Ghosh, K., Mandal, D., Ray, S., Zhang, D., Pal, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2017. Lecture Notes in Computer Science(LNCS), vol 10597. Springer, Cham. https://doi.org/10.1007/978-3-319-69900-4_32

  15. Venkata Divya, U., Sai Prasad, P.S.V.S. (2018). Hashing Supported Iterative MapReduce Based Scalable SBE Reduct Computation. In: Negi, A., Bhatnagar, R., Parida, L. (eds) Distributed Computing and Internet Technology. ICDCIT 2018. Lecture Notes in Computer Science(LNCS), vol 10722. Springer, Cham. https://doi.org/10.1007/978-3-319-72344-0_13

  16. Kumar, A., Sai Prasad, P.S.V.S. (2019). Hybridization of Fuzzy Min-Max Neural Networks with kNN for Enhanced Pattern Classification. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-13-9939-8_4

  17. Neeli Lakshmi Pavani, Pandu Sowkuntla, K Swarupa Rani, PSVS Sai Prasad. Fuzzy rough discernibility matrix based feature subset selection with MapReduce. TENCON 2019-2019 IEEE Region 10 Conference (TENCON). https://ieeexplore.ieee.org/abstract/document/8929668

  18. Bandagar, K., Sowkuntla, P., Moiz, S.A., Sai Prasad, P.S.V.S. (2019). MR_IMQRA: An Efficient MapReduce Based Approach for Fuzzy Decision Reduct Computation. In: Deka, B., Maji, P., Mitra, S., Bhattacharyya, D., Bora, P., Pal, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2019. Lecture Notes in Computer Science(LNCS), vol 11941. Springer, Cham. https://doi.org/10.1007/978-3-030-34869-4_34

  19. Bar, A., Kumar, A., Sai Prasad, P.S.V.S. (2019). Finding Optimal Rough Set Reduct with A* Search Algorithm. In: Deka, B., Maji, P., Mitra, S., Bhattacharyya, D., Bora, P., Pal, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2019. Lecture Notes in Computer Science(), vol 11941. Springer, Cham. https://doi.org/10.1007/978-3-030-34869-4_35

  20. Bar, A., Sai Prasad, P.S.V.S. (2020). Multiple Reducts Computation in Rough Sets with Applications to Ensemble Classification. In: Singh, P., Panigrahi, B., Suryadevara, N., Sharma, S., Singh, A. (eds) Proceedings of ICETIT 2019. Lecture Notes in Electrical Engineering, vol 605. Springer, Cham. https://doi.org/10.1007/978-3-030-30577-2_39

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