Assistant Professor

Dr Sowkuntla Pandu

Department of Computer Science Engineering


  1. Machine Learning
  2. Data mining
  3. Big Data Analytics



JNTU Hyderabad


JNTU Hyderabad


University of Hyderbad


  • Feb 2016 – Oct 2021 | Research Scholar | School of Computer and Information Sciences, University of Hyderabad, Hyderabad, Telangana, India.
  • June 2011 – Nov 2015 | Assistant Professor | Department of Computer Science and Engineering, School of Engineering, NNRG group of institutions (affiliated to JNTU Hyderabad), Hyderabad, Telangana, India.
  • June 2006 – July 2007 |IT Associate | Institute for Electronic Governance, Government of Andhra Pradesh, Hyderabad, India.

Research Interest

  • The current research is focused in the area of MapReduce based parallel/distributed attribute reduction using Rough Sets and Fuzzy-Rough Sets.
  • Investigating appropriate MapReduce-based strategies for scalable attribute reduction that can simultaneously scale in both huge object space and huge attribute space (high dimensional) of the big data sets.
  • Proposing MapReduce-based incremental attribute reduction approaches for streaming data.

Awards & Fellowships

  • December 2014 - National Eligibility Test (NET) – UGC
  • June 2015 - State Eligibility Test (SET) -UGC (AP/TS)
  • Feb 2016-Jan 2021 - Research Fellowship from Visvesvaraya PhD scheme - Ministry of Electronics and Information Technology (MeitY), Govt. of India.


  • IEEE Membership (96133891)


  • Pandu Sowkuntla* and P. S. V. S. Sai Prasad. MapReduce based improved quick reduct algorithm with granular refinement using vertical partitioning scheme. Knowledge-Based Systems, Elsevier, 189:105104, Feb 2020. (Indexed in SCI, SCOPUS and DBLP)
  • Pandu Sowkuntla*, Sravya Dunna, and P. S. V. S. Sai Prasad. MapReduce based parallel attribute reduction in Incomplete Decision Systems. Knowledge-Based Systems, Elsevier, 213:106677, Feb 2021. (Indexed in SCI, SCOPUS and DBLP)
  • Pandu Sowkuntla and P. S. V. S. Sai Prasad*. MapReduce based parallel fuzzy-rough attribute reduction using discernibility matrix. Applied Intelligence, Springer, pages 1–20, April 2021. (Indexed in SCI, SCOPUS and DBLP).
  • Pandu Sowkuntla and P. S. V. S. Sai Prasad. MapReduce based parallel attribute reduction in high dimensional hybrid decision systems. International Journal of Machine Learning and Cybernetics, Springer,(Indexed in SCI, SCOPUS and DBLP) (*work is completed and will be communicated soon).
  • Kiran Bandagar, Pandu Sowkuntla*, Salman Abdul Moiz, and P. S. V. S. Sai Prasad. MR_IMQRA: An Efficient MapReduce Based Approach for Fuzzy Decision Reduct Computation. In International Conference on Pattern Recognition and Machine Intelligence, pages 306–316. Springer International Publishing, 2019. (Indexed in SCOPUS and DBLP)
  • Neeli Lakshmi Pavani, Pandu Sowkuntla*, K. Swarupa Rani, and P. S. V. S. Sai Prasad. Fuzzy Rough Discernibility Matrix Based Feature Subset Selection With MapReduce. In IEEE Region10 Conference (TENCON), pages 389–394. IEEE, Oct 2019. DOI:10.1109/TENCON.2019.8929668 (Indexed in SCOPUS and DBLP)
  • The PhD dissertation entitled: “Explorations into MapReduce based Parallel Reduct Computation” is accepted in Doctoral Symposium of First International Conference on AI- ML Systems, jointly organized by ACM and MeitY at Bangalore, India 21-24 October 2021.

Contact Details