Anima Pramanik
Assistant Professor
[email protected]
Profile
Dr. Anima is currently serving as an Assistant Professor in the Information Management area at Management Development Institute (MDI) Gurgaon, India (February 2026 – present). Before joining MDI, she was associated with the Thiagarajar School of Management (TSM) Madurai, India. As a post-doctoral research fellow, she worked as a Research Associate in the Information Systems area at the Indian Institute of Management Ahmedabad (IIMA). She also served as a Visiting Scientist at the Indian Statistical Institute (ISI), Kolkata. Dr. Anima earned a Ph.D. from the Department of Industrial and Systems Engineering, Indian Institute of Technology (IIT) Kharagpur. She holds an M.Tech in Mechatronics Engineering from the National Institute of Technical Teacher’s Training and Research (NITTTR), Kolkata, and a B.Tech in Electronics and Communication Engineering from the West Bengal University of Technology, West Bengal, India. Her research interests include Intelligent Transportation Systems and Recommendation Systems. She has served as a reviewer for 25 peer-reviewed top-tier international journals and has been a member of the IISE professional body. She has also participated in academic collaborations and international conferences and has traveled to Thailand (2022, 2023, & 2025) and Singapore (2024) in connection with research and scholarly activities.
1. Artificial Intelligence & Machine Learning
2. Data Mining for Business Intelligence
3. Applied Business Analytics
4. Management Information Systems
5. Data Visualization
Pramanik, A. & Pal, S. K. (2026). RBKWOT: Rough allowance Borderline K-modes clustering Weighted Oversampling Technique. IEEE Transactions on Systems, Man, and Cybernetics: Systems - (DOI:10.1109/TSMC.2025.3627388).
Pramanik, A. & Pal, S. K. (2025). Intelligent Traffic Systems for Anomaly Detection: A State-of-the-art. Proceedings of the Indian National Science Academy, 1-24. (DOI: 10.1007/s43538-025-00616-7).
Chang, L., Deng, J, Pramanik, A., & Xu, X. (2025). Self-Supervised Learning for Labeling Unlabeled Data using Generalized Label. Journal of the Franklin Institute, 108230. (DOI: 10.1016/j.jfranklin.2025.108230).
Pramanik, A., Sarker S., Sarkar S., & Pal S.K. (2025). Real-time fall detection on roads using transfer learning-based granulated Bi-LSTM. Knowledge-Based Systems, 113038. (DOI: 10.1016/j.knosys.2025.113038).
Pramanik, A., Sarker S., Sarkar S., & Bose I. (2024). FGI-CogViT: Fuzzy Granule-based Interpretable Cognitive Vision Transformer for Early Detection of Alzheimer’s Disease using MRI Scan Images. Information Systems Frontier, 1-35. (DOI: 10.1007/s10796-024-10541-7).
Pramanik, A., Sarkar S., & Pal, S. K. (2023). Video Surveillance-based fall detection system using object-level feature thresholding and Z-numbers. Knowledge Based Systems, 280, 110992. (DOI: 10.1016/j.knosys.2023.110992).
Sarkar, S., Pramanik, A., & Maiti, J. (2023). An integrated approach using rough set theory, ANFIS, and Z-number in occupational risk prediction. Engineering Applications of Artificial Intelligence, 117, 105515. (DOI: 10.1016/j.engappai.2022.105515).
Pramanik, A., Pal, S. K., Maiti, J., & Mitra, P. (2022). Traffic Anomaly Detection and Video Summarization using Spatio-Temporal Rough Fuzzy Granulation using Z-numbers. IEEE Transactions on Intelligent Transportation Systems, 23(12), 24116-24125. (DOI: 10.1109/TITS.2022.3198595).
Sarkar, S., Ejaz, N., Maiti, J. & Pramanik, A. (2022). An integrated approach using growing self-organizing map-based genetic K-means clustering and tolerance rough set in occupational risk analysis. Neural Computing & Applications, 34, 9661-9687. (DOI: 10.1007/s00521-022-06956-5).
Sarkar, S., Pramanik, A., Maiti, J., & Reniers, G. (2021). COVID-19 outbreak: A data driven optimization model for allocation of patients. Computers & Industrial Engineering, 161, 107675. (DOI: 10.1016/j.cie.2021.107675).
Pramanik, A., Sarkar, S., Maiti, J., & Mitra, P. (2021). RT-GSOM: Rough tolerance growing self-organizing map. Information Sciences, 566, 19-37. (DOI: 10.1016/j.ins.2021.01.039).
Pramanik, A., Sarkar, S., & Maiti, J. (2021). A real-time video surveillance system for traffic pre-events detection. Accident Analysis & Prevention, 154, 106019. (DOI: 10.1016/j.aap.2021.106019).
Pal, S. K., Pramanik, A., Maiti, J., & Mitra, P. (2021). Deep learning in multi-object detection and tracking: state of the art. Applied Intelligence, 51(9), 6400-6429. (DOI: 10.1007/s10489-021-02293-7).
Pramanik, A., Pal, S. K., Maiti, J., & Mitra, P. (2021). Granulated RCNN and multi class deep sort for multi-object detection and tracking. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(1), 171-181. (DOI: 10.1109/TETCI.2020.3041019).
Sarkar, S., Pramanik, A., Maiti, J., & Reniers, G. (2020). Predicting and analyzing injury severity: A machine learning-based approach using class-imbalanced proactive and reactive data. Safety Science, 125, 104616. (DOI: 10.1016/j.ssci.2020.104616).