Abinash Pujahari
Assistant Professor
abinash.pujahari@mahindrauniversity.edu.in
Dr. Abinash Pujahari is an Assistant Professor in the Department of Computer Science & Engineering at Mahindra University École Centrale School of Engineering. He completed his Ph.D. in Computer Science and Engineering from the National Institute of Technology Raipur, India, in 2021.
His current research interests include recommender systems, information retrieval, and application areas of machine learning and deep learning. He has published several papers in Q1 SCI journals as the leading author, including IEEE Transactions, with high impact factors. He has given several invited talks at many FDPs across India. Prior to joining MU, he worked as an assistant professor in the Department of Computer Science & Engineering at SRM University-AP.
Education
- Ph.D. (Computer Science & Engineering) from NIT Raipur: 2021
Thesis title: Investigation of Various Issues in Recommender Systems for Performance Improvement
- M.Tech. (Computer Science) from Sambalpur University: 2013
- MCA from Siksha O Anusandhan University: 2011
Experience
- Working as an Assistant Professor at Mahindra University in the Department of Computer Science & Engineering since January 2026.
- SRM University AP: Assistant Professor: February 2022 to December 2025
- Bennett University: Assistant Professor: August 2021 to February 2022.
Journals
Journals
- 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. doi: https://doi.org/10.1016/j.ins.2019.03.064 Quartile-1, Impact Factor: 6.8
- 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. doi: https://doi.org/10.1016/j.knosys.2020.105798 Quartile-1, ABDC-A, Impact Factor: 7.6
- 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. doi: https://doi.org/10.1016/j.eswa.2020.113476 Quartile-1, ABDC-C, Impact Factor: 7.5
- 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. doi: https://doi.org/10.1007/s10489-020-01848-4 Quartile-2, Impact Factor: 3.5
- Abinash Pujahari, and Dilip Singh Sisodia. "Clickbait detection using multiple categorisation techniques." Journal of Information Science 47(1) (2021): 118-128. doi: https://doi.org/10.1177/0165551519871822 Quartile-1, Impact Factor: 1.7
- 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 52(10) (2022): 6639-6651. doi: https://doi.org/10.1109/TSMC.2022.3148675 Quartile-1, Impact Factor: 8.7
- Abinash Pujahari, and Dilip Singh Sisodia. "Item feature refinement using matrix factorization and boosted learning based user profile generation for content-based recommender systems" Expert Systems with Applications 206 (2022): 117849. doi: https://doi.org/10.1016/j.eswa.2022.117849 Quartile-1, ABDC-C, Impact Factor: 7.5
- Abinash Pujahari, and Dilip Singh Sisodia. "Ordinal consistency based matrix factorization model for exploiting side information in collaborative filtering." Information Sciences 643 (2023): 119258. doi: https://doi.org/10.1016/j.ins.2023.119258 Quartile-1, Impact Factor: 6.8
- Abinash Pujahari, and Dilip Singh Sisodia. "Modeling users’ preference changes in recommender systems via time-dependent Markov random fields." Expert Systems with Applications 234 (2023): 121072. doi: https://doi.org/10.1016/j.eswa.2023.121072 Quartile-1, ABDC-C, Impact Factor: 7.5
- Xiangting Shi, Yakang Zhang, Abinash Pujahari and Sambit Kumar Mishra, “When latent features meet side information: A preference relation based graph neural network for collaborative filtering.” Expert Systems with Applications 260 (2024): 125423. doi: https://doi.org/10.1016/j.eswa.2024.125423 Quartile-1, ABDC-C, Impact Factor: 7.5
- Jhansi Lakshmi Vigrahala, Abinash Pujahari"FIGNNCF: Feature integrated graph neural network based collaborative filtering for sequential recommendation," in Neurocomputing, vol. 663, pp. 132026, 2025, doi: https://doi.org/10.1016/j.neucom.2025.132026 . Quartile-1, Impact Factor: 6.5
- Abinash Pujahari, Tapas Kumar Mishra, and Rasmikanta Pati. "Heterogeneous Graph Neural Collaborative Filtering with Attribute Completion for Sparse Recommendation." Expert Systems with Applications 306 (2025): 130866. Doi: https://doi.org/10.1016/j.eswa.2025.130866 Quartile-1, Impact Factor: 6.5
Patents
Patents
- “A system and a method for navigating a vacuum cleaner” Dr Tapas Kumar Mishra, Dr Kshira Sagar Sahoo and Dr Abinash Pujahari, Patent Application No: 202241054606, Date Filed: 23-09-2022, Published: 30-09-2022. Granted: 07-05-2024
- “A system and a method for controlling smart street lights” Dr Tapas Kumar Mishra, Dr Sambit Kumar Mishra, Dr Kshira Sagar Sahoo, Dr Abinash Pujahari, Patent Application No: 202241046793, Date Filed: 17-08-2022, Date Published: 26-08-2022
Research Interests
Recommender Systems, Information Retrieval, Sentiment Analysis
