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Sureshkumar Pemmada

Sureshkumar Pemmada

Assistant Professor

Education

Ph. D.

Dr. Suresh Kumar Pemmada, Asst. Prof. at GITAM (Deemed to be University), VSKP, holds an M.Tech in CSE from JNTUK and a Ph.D. from VSSUT. With over a decade of academic experience, his expertise encompasses ML, DL, and Optimization. He is a prolific author, with contributions to esteemed journals and conferences by Elsevier, Springer, and IEEE. Dr. Pemmada also plays an active role as a reviewer for prestigious publications and conferences, including ICCIDM, CIPR, etc..

Research Publications

  • Suresh Kumar Pemmada, H. S. Behera, Anisha Kumari. K, J. Nayak, and B. Naik, "Advancement from neural networks to deep learning in software effort estimation : Perspective of two decades," Computer Science Review, vol. 38, pp. 100288, 2020, doi: 10.1016/j.cosrev.2020.100288. [Impact Factor: 12.9] [Indexing: SCIE, SCOPUS] [ELSEVIER] [h-Index: 60]
  • Suresh Kumar Pemmada, J. Nayak, and B.naik, " A deep intelligent framework for software risk prediction using improved firefly optimization, "Neural Computing and Applications (2023), doi: 10.1007/s00521-023-08756-x. [Indexing: SCIE, SCOPUS] [Impact Factor: 5.102] [h-Index: 111]
  • Suresh Kumar Pemmada, H. S. Behera, J. Nayak, and B. Naik, "Correlation-based modified long short-term memory network approach for software defect prediction," Evolving Systems, Feb. 2022, doi: 10.1007/s12530-022-09423-7. [Indexing: SCIE, SCOPUS] [SPRINGER] [Impact Factor: 1.9] [h-Index: 31]
  • Suresh Kumar Pemmada, H. S. Behera, J. Nayak, and B. Naik, "Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature," Innovations in Systems and Software Engineering, vol 17, pp. 1–22, May 2021, doi: 10.1007/s11334-021-00399-2. [Indexing: ESCI, SCOPUS] [SPRINGER] [Impact Factor: 1.2] [h-Index:30]
  • Suresh Kumar Pemmada, H. S. Behera, J. Nayak, and B. Naik, "A pragmatic ensemble learning approach for effective software effort estimation," Innovations in Systems and Software Engineering, Jan. 2021, doi: 10.1007/s11334-020-00379-y. [Indexing: ESCI, SCOPUS] [SPRINGER] [Impact Factor: 1.2] [h-Index:30]

Ongoing Research Projects

  • Check Icon 1. Title of the Project: A Photoplethysmography-based Mental Workload Evaluation Using Deep Convolutional Recurrent Neural Network. Sanctioning Authority: Research Seed Grants (RSG) by Gandhi Institute of Technology and Management (GITAM) Deemed to be University.

Expertise

  • Check Icon Machine Learning, Neural Networks, Deep Learning
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