Assistant Professor

Dr Abinash Pujahari

Department of Computer Science and Engineering


  1. Recommender Systems
  2. Information Retrieval
  3. Sentiment Analysis



National Institute of Technology Raipur
Computer Science and Engineering


Sambalpur University
Computer Science


SOA University
Master’s in computer application


Sambalpur University
Bachelor of Science


  • Aug 2021 – Feb 2022 – Assistant Professor – Bennett University, Greater Noida, India
  • Aug 2016 – Aug 2017 – Lecturer, Ravenshaw, University, Cuttack, Odisha
  • Aug 2013 – May 2014 – Assistant Professor, Sambalpur University Institute of Information Technology, Burla, Odisha

Research Interest

  • Personalized recommender systems, specifically focused on reducing sparsity and improving the ranking quality of recommender systems.
  • Modeling change in users’ behaviour over time in personalized recommender systems.

Awards & Fellowships

2019 – SIGCHI Gary Marsden Travel Award – ACM SIGCHI Gary Marsden- For attending RecSys Summer School 2019 at University of Gothenburg, Sweden.


IEEE Member

ACM Professional Member


  • 1. Abinash Pujahari, and Dilip Singh Sisodia, “Handling Dynamic User Preferences using Integrated Point and Distribution Estimations in Collaborative Filtering,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, Early Access (Online) , SCI (IF:13.451)
  • 2. Abinash Pujahari, and Dilip Singh Sisodia. "Pair-wise preference relation based probabilistic matrix factorization for collaborative filtering in recommender system." Knowledge-Based Systems 196 (2020): 105798, SCI (IF: 8.038)
  • 3. Abinash Pujahari, and Dilip Singh Sisodia. "Aggregation of preference relations to enhance the ranking quality of collaborative filtering based group recommender system." Expert Systems with Applications 156 (2020): 113476. SCIE (IF: 6.954)
  • 4. Abinash Pujahari, and Dilip Singh Sisodia. "Modeling side information in preference relation based restricted boltzmann machine for recommender systems." Information Sciences 490 (2019): 126-145. SCI (IF: 6.795)
  • 5. Abinash Pujahari, and Dilip Singh Sisodia. "Preference relation based collaborative filtering with graph aggregation for group recommender system." Applied Intelligence 51.2 (2021): 658-672. SCI (IF: 5.086)
  • 6. Abinash Pujahari, and Dilip Singh Sisodia. "Clickbait detection using multiple categorisation techniques." Journal of Information Science 47.1 (2021): 118-128. SCIE (IF: 3.282)


  • 1. Pujahari, A. and Padmanabhan, V., 2015, December. Group recommender systems: Combining user-user and item-item collaborative filtering techniques. In 2015 International Conference on Information Technology (ICIT) (pp. 148-152). IEEE.
  • 2. Pujahari, A. and Padmanabhan, V., 2014, December. An approach to content based recommender systems using decision list based classification with k-DNF rule set. In 2014 International Conference on Information Technology (pp. 260-263). IEEE.
  • 3. Pujahari, A. and Padmanabhan, V., 2015. A new grouping method based on social choice strategies for group recommender system. In Computational Intelligence in Data Mining-Volume 1 (pp. 325-332). Springer, New Delhi.
  • 4. Pujahari, A., Padmanabhan, V. and Patel, S., 2016. Nearest Neighbour with Priority Based Recommendation Approach to Group Recommender System. In Computational Intelligence in Data Mining—Volume 2 (pp. 347-354). Springer, New Delhi.
  • 5. Pujahari, Abinash, and Dilip Singh Sisodia. "Model-based collaborative filtering for recommender systems: An empirical survey." 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T). IEEE, 2020.
  • 6. Sisodia, Dilip Singh, et al. "A comparative performance study of machine learning algorithms for sentiment analysis of movie viewers using open reviews." Performance Management of Integrated Systems and its Applications in Software Engineering. Springer, Singapore, 2020. 107-117.

Contact Details

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