Dr. Anima Pramanik

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Dr. Anima Pramanik

Assistant Professor

B.Tech, M.Tech, PhD, PDF
animapramanik@tsm.ac.in

Biography
Publications
Courses
others

Biography

I am currently serving as an Assistant Professor at Thiagarajar School of Management (TSM) Madurai, India in Systems & Analytics area (Aug, 2025 – till date). I served as a Research Associate in the Information Systems domain at the Indian Institute of Management (IIM) Ahmedabad, India. I also worked as a Visiting Scientist at Indian Statistical Institute (ISI) Kolkata, India. I received my Ph.D. degree from the Department of Industrial and Systems Engineering, Indian Institute of Technology (IIT) Kharagpur, India. I completed my B. Tech degree in Electronics and Communication Engineering from the West Bengal University of Technology, West Bengal, India, and the M. Tech degree in Mechatronics Engineering from the National Institute of Technical Teacher’s Training and Research (NITTTR), Kolkata, West Bengal, India. My research interests include computer vision, intelligent transportation systems, and recommendation systems. I have been serving as a reviewer in 25 peer-reviewed top-tier journals. I served as a member of the IISE professional body. I have visited two countries, including the Thailand (2022 & 2023) Singapore (2024) for attending international conferences, academic collaboration, and research works.

Publications

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.
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.
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.
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.
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.
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.
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.
Pramanik, A., Sarkar, S., Maiti, J., & Mitra, P. (2021). RT-GSOM: Rough tolerance growing self-organizing map. Information Sciences, 566, 19-37.
Pramanik, A., Sarkar, S., & Maiti, J. (2021). A real-time video surveillance system for traffic pre-events detection. Accident Analysis & Prevention, 154, 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.
Pramanik, A., Pal, S. K., Maiti, J., & Mitra, P. (2021). Granulated RCNN and multiclass deep sort for multi-object detection and tracking. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(1), 171-181.
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.

Courses

Corporate Finance

others

Professional Certifications:

Memberships: Institute of Industrial & Systems Engineers (IISE)
Workshops Organized/Co-ordinated/Resource person for FDP/MDP

Conferences

Sarkar, S., & Pramanik, A. (2023, March). Quantifying data imbalance using Exponential f-Divergence. In 2023 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON) (pp. 403-408). IEEE.

Pramanik, A., Venkatagiri, K., Sarkar, S., & Pal, S. K. (2022, December). Deep Network-based Slow Feature Analysis for Human Fall Detection. In The International Conference on Computational Modelling, Simulation and Optimization (ICCMSO-2022), Bangkok, Thailand. IEEE.

Pramanik, A., Djeddi, C., Sarkar, S., & Maiti, J. (2020, October). Region proposal and object detection using HoG-based CNN feature map. In 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI) (pp. 1-5). IEEE.
Pramanik, A., Gorai, A., Sarkar, S., & Gupta, P. (2018, December). A Novel Feature Extraction-based Human Identification Approach using 2D Ear Biometric. In 2018 IEEE Applied Signal Processing Conference (ASPCON) (pp. 168-172). IEEE.