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Faculty Directory Rabi Narayan Behera
Rabi Narayan Behera

Rabi Narayan Behera

Assistant Professor

[email protected]
Vidwan Profile Google Scholar

Academic Information

Ph.D(Submitted), NOU, 2025

Research Areas

Machine Learning Data Science

Research Interests

My research interests lie in Machine Learning and Data Science, with a focus on developing intelligent models for data-driven decision making. I am particularly interested in supervised and unsupervised learning, deep learning architectures, and natural language processing for extracting meaningful insights from large-scale, real-world data. My work also explores feature engineering, dimensionality reduction, model interpretability, and performance optimization. I aim to apply these techniques to domains such as healthcare, smart systems, and intelligent automation, emphasizing scalable, ethical, and explainable AI solutions.

Courses Taught

AI & ML, Theory of Computation, NLP, DBMS, Software Engineering

Positions Held

Assistant Professor

Publications

[1] R. N. Behera, M. Roy, and S. Dash, “Ensemble based hybrid machine learning approach for sentiment classification – A review,” International Journal of Computer Applications, vol. 146, no. 6, pp. 31–36, 2016, doi: 10.5120/ijca2016910813. [2] R. N. Behera and S. Dash, “A particle swarm optimization based hybrid recommendation system,” International Journal of Knowledge Discovery in Bioinformatics (IJKDB), vol. 6, no. 2, p. 10, 2016, doi: 10.4018/IJKDB.2016070101. [3] R. N. Behera, P. L. Saha, A. Chakraborty, and S. Dash, “Hybrid movie recommendation system based on PSO-based clustering,” International Journal of Control Theory and Applications, vol. 10, no. 18, pp. 41–49, 2017. [4] R. N. Behera, P. Baral, S. Saha, and S. Dash, “Emotion-based classification of human voice using an optimized machine learning approach,” International Journal of Control Theory and Applications, vol. 10, no. 18, pp. 51–55, 2017. [5] R. N. Behera and S. Dash, “Emotion-based classification of human voice using an optimized machine learning approach,” in Proc. 22nd Int. Symp. Frontiers of Research in Speech and Music (FRSM), 2016. [6] S. Dash and R. N. Behera, “Sampling-based hybrid algorithms for imbalanced data classification,” Human-centric Computing and Information Sciences (HIS), vol. 13, no. 2, 2016, doi: 10.3233/HIS-160226. [7] R. N. Behera, M. Roy, and S. Dash, “A novel machine learning approach for classification of emotion and polarity in Sentiment140 dataset,” in Proc. 3rd Int. Conf. Business & Information Management (ICBIM), NIT, Durgapur 2016. [8] R. N. Behera and S. Dash, “Using Attention-Based LSTM Model with VADER Integration for Improved Aspect-Based Sentiment Analysis,” in Proc. 2nd Int. Conf. Advanced Computing and Systems (AdComSys 2025), UEM, Kolkata, Lecture Notes in Networks and Systems. Springer, 2025. [9] R. N. Behera and R. Sinha, “A Hybrid Attention-Based LSTM-VADER Model with Nature- Inspired Feature Selection for Enhancing Aspect Based Sentiment Analysis” in Proc. 4th IEEE International Conference on Computer Vision and Machine Intelligence (CVMI 2025), NIT Rourkela, indexed in IEEE Xplore, 2025. [10] R. N. Behera and Kajaree Das, “A Survey on Machine Learning: Concept, Algorithms and Applications” International Journal of Innovative Research in Computer and Communication Engineering Volume 5, Issue 2, Pages 9, 2017.