Published Papers: 

Journals:  

2026 (1) 

1. Pramanik, A., Sarker, S., Sarkar, S., & Bose, I. (2026). Can We Trust What We See? Interpretable Deep Learning for Detecting Face-Swapped Deepfake Videos. Information Systems Frontier. (Link: Paper)- (ABDC: A) 

2025 (5) 

1. Upadhyay, S., Singh, P., Ghosh, P., & Sarkar, S. (2025). Influence of Leader Humility on Subordinates’ Knowledge-Sharing: Exploring the Boundary Conditions. Journal of Knowledge Management, 30(4), 1489–1515. (Link: Paper)- (ABDC: A) 
2. Bag, S., Sarkar, S., & Bose, I. (2025). Enhancing cybersecurity risk assessment using temporal knowledge graph-based explainable decision support system. Decision Support Systems, 198, 114526. (Link: Paper)- (ABDC: A*) 
3. Sreevatsa, B., Sarkar, S., & Mishra, A.N. (2025). Generative Artificial Intelligence for Management Education: Applications, Benefits, Challenges and Future Research Directions. International Journal of Educational Management, 39 (5), 1217–1239. (Link: Paper)- (ABDC: B) 
4. 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, 311, 113038. (Link: Paper)- (ABDC: A) 
5. Bhattacharyya, S., Sarkar, B. D., Sarkar, S., Singh, P., & Manatkar, R. (2025). Developing a Reintegration Index (RI) for a Closed-loop Supply Chain Network in the Automobile Industry. Benchmarking: an International Journal, 33 (3), 736–758. (Link: Paper) (ABDC: B) 

2024 (4) 

1. Chaudhuri, A., Sarkar, S., & Bala, P. K. (2024). Thematic exploration and analysis of cybersecurity policies of businesses: an NLP-based approach. Journal of Organizational Computing and Electronic Commerce, 35(2), 157-187.  (Link: Paper) (ABDC: A) 
2. 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 Frontiers, 28, 615-649. - (Link: Paper) (ABDC: A) 
3. Sabharwal, M., Meena, H., Sarkar, S., Damani, M., & Sharma, N. (2024). Real-time detection of coke particles in Blast Furnace Operations using Machine Learning: A Case of Steel Plant in India. Ironmaking & Steelmaking, 52(9), 1080-1096.  - (Link: Paper) 
4. Sarkar, S., Paramanik, A. R., & Mahanty, B. (2024). A Z-Number Slacks-Based Measure DEA model-based Framework for Sustainable Supplier Selection with Imprecise Information. Journal of Cleaner Production, 436, 140563. - (Link: Paper) (ABDC: A) 

2023 (6) 

1. 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.- (Link: Paper) (ABDC: A) 
2. Bag, S., Golder, R., Sarkar, S., & Maity, S. (2023). SENE: A Novel Manifold Learning Approach for Distracted Driving Analysis with Spatio-Temporal and Driver Praxeological Features. Engineering Applications of Artificial Intelligence, 123, Part C, 106332. (Link: Paper) 
3. Bhattacharyya, S., Sarkar, S., Sarkar, B., & Manatkar, R. (2023). Risk modeling framework for strategic and operational intervention to enhance the effectiveness of a closed-loop supply chain. IEEE Transactions on Engineering Management, 71, 7015-7028. (Link: Paper)- (ABDC: A) 
4. Dey, P., Chowdhury, S., Abadie, A.,Vann Yaroson, E., & Sarkar, S. (2023). Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises. International Journal of Production Research, 62(15), 5417-5456. (Link: Paper)-  (ABDC: A) 
5. Paramanik, A. R., Sarkar, S., & Sarkar, B. (2023). A Two-stage Improved Base Point Slacks-Based Measure of Super-efficiency for Negative Data Handling. Computers & Operations Research, 150, 106057. (Link: Paper)- (ABDC: A) 
6. 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, Part A, 105515. (Link: Paper). 

2022 (6) 

1. Das, S., & Sarkar, S. (2022). News media mining to explore speed-crash-traffic association during COVID-19. Transportation Research Record, 2678(12), 349-366. (Link: Paper). (ABDC: B) 
2. Das, S., Eun, P., & Sarkar, S. (2022). Impact of operating speed measures on traffic crashes: Annual and daily level models for rural two-lane and rural multilane roadways. Journal of Transportation Safety & Security, 15(6), 584-603. (Link: Paper). 
3. Paramanik, A. R., Sarkar, S., & Sarkar, B. (2022). OSWMI: An Objective-Subjective Weighted method for Minimizing Inconsistency in multi-criteria decision making. Computers & Industrial Engineering, 169, 108138. (Link: Paper). (ABDC: A) 
4. Riccardi, M.R., Mauriello, F., Sarkar, S., Galante, F., Scarano, A., & Montella, A. (2022). Parametric and Non-Parametric Analyses for Pedestrian Crash Severity Prediction in Great Britain. Sustainability, 14(6), 3188.- (Link: Paper). 
5. 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. - (Link: Paper). 
6. Sarkar, S., Vinay, S., Djeddi, C., & Maiti, J. (2022). Classification and pattern extraction of incidents: A deep learning-based approach. Neural Computing & Applications, 34, 14253–14274. - (Link: Paper) 

2021 (3) 

1. 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. (Link: Paper). [Included in the World Health Organization (WHO) database (Link)] (ABDC: A) 
2. Pramanik, A., Sarkar, S., & Maiti, J. (2021). A real-time video surveillance system for traffic pre-events detection. Accident Analysis & Prevention, 154, 106019. (Link: Paper) (ABDC: A*) 
3. Pramanik, A., Sarkar, S., Maiti, J., & Mitra, P. (2021). RT-GSOM: Rough tolerance growing self-organizing map. Information Sciences, 566, 19-37. (Link: Paper) 

2020 (2) 

1. Sarkar, S., & Maiti, J. (2020). Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis. Safety Science, 131, 104900. (Link: Paper) (ABDC: A) 
2. 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. (Link: Paper) (ABDC: A) 

2019 (2) 

1. Sarkar, S., Raj, R., Vinay, S., Maiti, J., & Pratihar, D. K. (2019). An optimization-based decision tree approach for predicting slip-trip-fall accidents at work. Safety Science, 118, 57-69. (Link: Paper) (ABDC: A) 
2. Sarkar, S., Vinay, S., Raj, R., Maiti, J., & Mitra, P. (2019). Application of optimized machine learning techniques for prediction of occupational accidents. Computers & Operations Research, 106, 210-224. (Link: Paper) (ABDC: A) 

2018 (1) 

1. Sarkar, S., Pratihar, D. K., & Sarkar, B. (2018). An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company. Journal of manufacturing systems, 46, 163-178. (Link: Paper) (ABDC: B) 

2017 (2) 

1. Gautam, S., Maiti, J., Syamsundar, A., & Sarkar, S. (2017). Segmented point process models for work system safety analysis. Safety Science, 95, 15-27. (Link: Paper) (ABDC: A) 
2. Singh, K., Raj, N., Sahu, S. K., Behera, R. K., Sarkar, S., & Maiti, J. (2017). Modelling safety of gantry crane operations using petri nets. International journal of injury control and safety promotion, 24(1), 32-43. (Link: Paper) 

2015 (1) 

1. Krishna, O. B., Maiti, J., Ray, P. K., Samanta, B., Mandal, S., & Sarkar, S. (2015). Measurement and modeling of job stress of electric overhead traveling crane operators. Safety and health at work, 6(4), 279-288. (Link: Paper) 

Book Chapters:  

2026 (7) 

1. Luharuka, I., Varshney, A., Sarkar, S., & Bose, I. (2026). V-SVM: A VGG19-based Support Vector Machine for Early Detection of Parkinson's Disease. In: Maiti, J., Rai, R.N., Menon, B.G., Ahuja, R., Shrigondekar, H.H. (eds) Safety, Health, and Analytics-Driven Governance Toward Sustainable Development. SHADG 2024. Lecture Notes in Mechanical Engineering. pp 169–177. Springer, Singapore. (Link: Paper) 
2. Kumar, A., Amrita, & Sarkar, S. (2026). Social media sentiment analysis of impacts of COVID-19 on mothers and children. In: Operations research and data analytics: Current trends and future perspectives (Lecture Notes on Multidisciplinary Industrial Engineering), (p. 139–155). Springer. (Link: Paper) 
3. Varshney, A., Luharuka, I., Sarkar, S., & Bose, I. (2026). Alzheimer's Disease Detection using Gaussian-Based Bayesian Parameter Optimization-based Deep Convolution Neural Network. In Operations Research and Data Analytics: Current Trends and Future Perspectives. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 157–175). Springer, Singapore. (Link: Paper) 
4. Srivastava, A., Sarkar, S., & Bose, I. (2026). Toward Early Parkinson's Disease Detection: A Novel RL-CNN Based Approach. In Operations Research and Data Analytics: Current Trends and Future Perspectives. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 177–193). Springer, Singapore. (Link: Paper) 
5. Tulsyan, P., Ghosh, A., & Sarkar, S. (2026). Eye-Tracking-Based Packaging Analysis for Toy Industry Using Bayesian Belief Networks and Evidential Reasoning Approach. In Recent Advances in Industrial and Systems Engineering. Lecture Notes on Multidisciplinary Industrial Engineering. (p. 103–121) Springer, Singapore. (Link: Paper) 
6. Sarker, S., Pramanik, A., Sarkar, S., & Bose, I.  (2026). OptiTrackEx: A Deep Learning Approach to Real Time Vehicle Collision. In Proceedings of the 13th Asia Pacific Conference on Transportation and the Environment (APTE) 2024. APTE 2024. Lecture Notes in Civil Engineering, vol 722. (p. 445-455). Springer, Singapore. (Link: Paper) 
7. Sarker, S., Pramanik, A., & Sarkar, S. (2026). A Two-Stage Method for Detection and Distance Perception of Traffic Lights. In Proceedings of the 13th Asia Pacific Conference on Transportation and the Environment (APTE) 2024. Lecture Notes in Civil Engineering, vol 722.  (pp 457–466). Springer, Singapore. (Link: Paper) 

2025 (1) 

1. Srivastava, Apurb, Sarkar, S., & Djeddi, C. (2025). Soil Fertility Detection using Reinforcement Learning-based Recurrent Neural Network. In: García Márquez, F.P., Hameed, A.A., Jamil, A. (eds) Pattern Recognition and Artificial Intelligence. Lecture Notes in Networks and Systems, vol 1393. Springer, Cham. (Link: Paper) 

2022 (5) 

1. Pramanik, A., Sarkar, S., Djeddi, C., & Maiti, J. (2022). Real-Time Detection of Traffic Anomalies Near Roundabouts. In Mediterranean Conference on Pattern Recognition and Artificial Intelligence (pp. 253-264). Springer, Cham. (Link: Paper) 
2. Maity, S., Rastogi, A., Djeddi, C., Sarkar, S., & Maiti, J. (2022). A Novel Optimized Method for Feature Selection Using Non-linear Kernel-Free Twin Quadratic Surface Support Vector Machine. In Mediterranean Conference on Pattern Recognition and Artificial Intelligence (pp. 339-353). Springer, Cham. (Link: Paper) 
3. Kosuri, M., Tandu, C., Sarkar, S., & Maiti, J. (2022). Multivariate Deep Learning Model with Ensemble Pruning for Time Series Forecasting. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 321-334). Springer, Singapore. (Link: Paper) 
4. Rao, A., Sarkar, S., Pramanik, A., & Maiti, J. (2022). Predicting and Analysing Pedestrian Injury Severity: A Machine Learning-Based Approach. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 485-497). Springer, Singapore. (Link: Paper) 
5. Tandu, C., Kosuri, M., Sarkar, S., & Maiti, J. (2022). A Two-Fold Multi-objective Multi-verse Optimization-Based Time Series Forecasting. In Proceedings of the Seventh International Conference on Mathematics and Computing (pp. 743-754). Springer, Singapore. (Link: Paper) 

2021 (4) 

1. Pramanik, A., Sarkar, S., Siddharth, V.S., & Maiti, J. (2021). Semi-automated ontology creation and upgradation for rail-road incidents: A case of a steel plant in India. In Emerging Technologies in Data Mining and Information Security. 164, (pp. 285-294). Springer, Singapore. (Link: Paper) 
2. Pramanik A., Nande V., Pradhan A.S., Sarkar S., Maiti J. (2021). Dynamic Functional Bandwidth Kernel-Based SVM: An Efficient Approach for Functional Data Analysis. In Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing. 1286, (pp. 673-681 ). Springer, Singapore. (Link: Paper) 
3. Sarkar, S., Vinay, S., Djeddi, C., & Maiti, J. (2021). Text Mining-Based Association Rule Mining for Incident Analysis: A Case Study of a Steel Plant in India. Pattern Recognition and Artificial Intelligence, 1322, 257-273. (Link: Paper) 
4. Mekhaznia, T., Djeddi, C., & Sarkar, S. (2021). Personality Traits Identification Through Handwriting Analysis. Pattern Recognition and Artificial Intelligence, 1322, 155-169. (Link: Paper) 

2020 (6) 

1. Sarkar, S., Pramanik, A., Khatedi, N., & Maiti, J. (2020). An investigation of the effects of missing data handling using ‘R’-packages. In Data Engineering and Communication Technology (pp. 275-284). Springer, Singapore.  (Link: Paper) 
2. Sarkar, S., Gaine, S., Deshmukh, A., Khatedi, N., & Maiti, J. (2020). A structural topic modeling-based machine learning approach for pattern extraction from accident data. In Data engineering and communication technology (pp. 555-564). Springer, Singapore. (Link: Paper) 
3. Sarkar, S., Khatedi, N., Pramanik, A., & Maiti, J. (2020). An ensemble learning-based undersampling technique for handling class-imbalance problem. In Proceedings of ICETIT 2019 (pp. 586-595). Springer, Cham. (Link: Paper) 
4. Sarkar, S., Ejaz, N., Promod, C. S., & Maiti, J. (2020). Pattern Extraction Using Proactive and Reactive Data: A Case Study of Contractors’ Safety in a Steel Plant. In Proceedings of ICETIT 2019 (pp. 731-742). Springer, Cham. (Link: Paper) 
5. Sarkar, S., Pramanik, A., Khatedi, N., Balu, A. S. M., & Maiti, J. (2020). GSEL: A Genetic Stacking-Based Ensemble Learning Approach for Incident Classification. In Proceedings of ICETIT 2019 (pp. 719-730). Springer, Cham. (Link: Paper) 
6. Sarkar, S., Ejaz, N., Kumar, M., & Maiti, J. (2020). Root Cause Analysis of Incidents Using Text Clustering and Classification Algorithms. In Proceedings of ICETIT 2019 (pp. 707-718). Springer, Cham. (Link: Paper) 

2019 (2) 

1. Sarkar, S., Chain, M., Nayak, S., & Maiti, J. (2019). Decision support system for prediction of occupational accident: a case study from a steel plant. In Emerging Technologies in Data Mining and Information Security (pp. 787-796). Springer, Singapore. (Link: Paper) 
2. Pramanik, A., Sarkar, S., & Maiti, J. (2019). Oil spill detection using image processing technique: An occupational safety perspective of a steel plant. In Emerging Technologies in Data Mining and Information Security (pp. 247-257). Springer, Singapore. (Link: Paper) 

2018 (2) 

1. Verma, A., Chatterjee, S., Sarkar, S., & Maiti, J. (2018). Data-driven mapping between proactive and reactive measures of occupational safety performance. In Industrial Safety Management (pp. 53-63). Springer, Singapore. (Link: Paper) 
2. Sarkar, S., Verma, A., & Maiti, J. (2018). Prediction of occupational incidents using proactive and reactive data: a data mining approach. In Industrial Safety Management (pp. 65-79). Springer, Singapore.  (Link: Paper) 

2017 (2) 

1. Sarkar, S., Lohani, A., & Maiti, J. (2017). Genetic algorithm-based association rule mining approach towards rule generation of occupational accidents. In International Conference on Computational Intelligence, Communications, and Business Analytics (pp. 517-530). Springer, Singapore. (Link: Paper) 
2. Sarkar, S., Lakha, V., Ansari, I., & Maiti, J. (2017). Supplier selection in uncertain environment: a fuzzy MCDM approach. In Proceedings of the First International Conference on Intelligent Computing and Communication (pp. 257-266). Springer, Singapore. (Link: Paper)  

Conference Papers: 

2026 (9) 

1. Jain, H. & Sarkar, S. (2026, Dec). Uncovering User Dissatisfaction in Mobile Applications: A Cross-Category Analysis Using LLM-Enhanced BERTopic on Google Play Store Reviews. In INDICON 2026, Chennai, Tamil Nadu, India.- Under review 
2. Ishika, & Sarkar, S. (2026, Dec). Predicting and Mapping Road Accident Black Spots in Indian Cities: A Multi-Signal Geospatial Machine Learning Approach. In INDICON 2026, Chennai, Tamil Nadu, India.- Under review 
3. Bhanushali, J., Sarkar, S., & Pramanik, A. (2026, Oct). Powering the Future: EV Charging Infrastructure Planning Using Machine Learning and Stochastic Optimization Techniques. In INDICON 2026, Chennai, Tamil Nadu, India.- Under review 
4. Thopte, Y., Gupta, R., & Sarkar, S. (2026, Oct). ValuRipple: Learning Customer Value Dynamics via a Contrastive GAN-Graph Churn Prediction Framework. In TENCON 2026, Bali, Indonesia. Accepted & to be presented. (Link) 
5. Sarkar, S., Biswas, K., & Pramanik, A.  (2026, June). Multi-Class Affect Detection in Educational Chatbots: Evidence from Imbalanced Dialogue Data. In The 2026 International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2026). London, UK. Springer. In press. (Link: https://ficta.co.uk/) 
6. Jain, D., & Sarkar, S.  (2026, June). Is Prediction Enough? A Dynamic Graph Attention and Reinforcement Learning Framework for Automated Trading. In the VI edition of the International Conference on Optimization, Learning Algorithms and Applications (OL2A 2026), Malaga, Spain. Springer. In press. (Link: https://ol2a.ipb.pt/ui/#/home) 
7. Kumar, T., & Sarkar, S.  (2026, Feb). Anticipatory Analytics: Transforming Enterprise Decision-Making with AI. In the International Conference on Computer, Electrical & Communication Engineering 2026, Kolkata. IEEE. - (Link: Paper).   
8. Hamza, M., Rai, K., & Sarkar, S. (2026, Feb). Movie Review Helpfulness Prediction using Semantic Alignment and Evidential Fusion-based Multimodal Approach. In the International Conference on Computer, Electrical & Communication Engineering 2026, Kolkata. IEEE. - (Link: Paper).   
9. Jaiswal, B. & Sarkar, S.  (2026, Jan). Can AI-Enabled Business Intelligence Predict Renewable Energy Waste? In the 7th Mediterranean Conference on Pattern Recognition and Artificial Intelligence. Springer. - In press. (Link: https://www.medprai.com/) 

2025 (3) 

1. Paul, D., Pattrea, P., Sarkar, S. & Basu, M.  (2025, Dec). Employee Attrition Prediction Using Machine Learning Approaches. In the 19th ISDSI-Global Conference 2025, Kolkata. - In press. (Link: https://isdsi-global.com/themes.php) 
2. Kashyap, Aryan, Mehak, Sarkar, S., & Pramanik, A.  (2025, Nov). Lightweight Deepfake Detection for Real-World Augmented Images in Social Media. In The 20th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2025). Phuket, Thailand. IEEE. - (Link: Paper).   
3. Singh, Sakshi, Khandelwal, Siddhi, & Sarkar, S.  (2025, Nov). Scalable Multimodal Misinformation Detection Across Social Media Platforms. In The 20th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP 2025). Phuket, Thailand. IEEE. - (Link: Paper).  

2024 (1) 

1. Sarker, S., Thakur, A., Saha, S., & Sarkar, S.  (2024, Nov). NovaNet: A Novel Method for Enhanced Pothole Detection on Road. In The 8th International Conference on System Reliability and Safety, Sicily, Italy - (Link: Paper).  

2023 (2) 

1. Maity, S., Khan, S., & Sarkar, S. (2023, Nov). A Two-phase Approach to Determine User-Preference and Feature Importance in Pricing of Cryptocurrencies using Twitter Data. In 2023 IEEE International Conference on E-Business Engineering (ICEBE) (pp. 1-7). Sydney, Australia. IEEE.- (Link: Paper). 
2. 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. Thailand. - (Link: Paper) 

2022 (7) 

1. Pramanik, A., Venkatagiri, K., Sarkar, S., & Pal, S. K. (2022, Dec). Deep Network-based Slow Feature Analysis for Human Fall Detection. In 2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) (pp. 53-58), Bangkok, Thailand. IEEE.- (Link: Paper) 
2. Sadafule, S., Sarkar, S., & Wu, S. (2022, Dec). G-AUC: An improved metric for classification model selection. In 2022 26th International Computer Science and Engineering Conference (ICSEC) (pp. 100-104), Sakon Nakhon, Thailand. IEEE. (Link: Paper)  
3. Bag, S., Kumar, A., & Sarkar, S. (2022, Oct). Handling sparsity and seasonality problems simultaneously in session-based recommender systems using graph collaborative filtering. In 2022 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 11-15), Bahrain. IEEE. (Link: Paper) 
4. Bag, S., Maity, S., & Sarkar, S. (2022, Oct). Crash severity analysis in distracted driving using unlabeled and imbalanced data: A novel approach using Robust Two-Phase Ensemble Predictor. In 2022 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 88-92), Bahrain. IEEE. (Link: Paper) 
5. Balakrishna, V., Bag, S., & Sarkar, S. (2022, Oct). Identifying spammer groups in consumer reviews using meta-data via bipartite graph approach. In 2022 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 650-654), Bahrain. IEEE. (Link: Paper) 
6. Singh, A. K., Golder, R., & Sarkar, S. (2022, Oct). Unsupervised and Categorical Sentiment Segmentation of Customer Product Reviews. In 2022 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 624-628), Bahrain. IEEE. (Link: Paper) 
7. Karkaria, P., Golder, R., & Sarkar, S. (2022, Oct). Implementation of a Priority Queue to Optimize Resources during Manual Verification of Fake News. In 2022 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 1-5), Bahrain. IEEE. (Link: Paper) 

2021 (3) 

1. Pradhan, S., Kumar, S., Sarkar, S., & Maiti, J. (2021, Oct). A kernel-free support vector machine with Q-margin. In 2021 International Conference on Data Analytics for Business and Industry (ICDABI) (pp. 443-447), Bahrain. IEEE. (Link: Paper)
2. Saha, S., Das, M., Mondal, B. S., Sarkar, S., & Maiti, J. (2021, Oct). DiPSVM : Polynomial Kernel-Free Support Vector Machine. In 2021 international conference on data analytics for business and industry (ICDABI) (pp. 448-452), Bahrain. IEEE. (Link: Paper) 
3. Bhattacharyya, S., Sarkar, S., & Manatkar, R. (2021, Jan). Strategic and Operational interventions in Effectiveness and Risk Optimization of Closed-Loop Supply Chain Network for End-of-Life Vehicles’ recovery. In International Conference on Operations and Supply Chain Management (ICOSCM 2021), Symbiosis Institute of Operations Management, Nasik, Maharashtra, India. (Link: Paper) 

2020 (1) 

1. Pramanik, A., Harshvardhan, 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. (Link: Paper) 

2018 (4) 

1. 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. (Link: Paper) 
2. Sarkar, S., Lodhi, V., & Maiti, J. (2018, November). Text-clustering based deep neural network for prediction of occupational accident risk: A case study. In 2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP) (pp. 1-6). IEEE. (Link: Paper) 
3. Sarkar, S., Maiti, J., Nayak, S., & Chain, M. (2018, May). Data-driven Decision Support System for Prediction of Occupational Accidents (Abstract only). In IISE Annual Conference & Expo 2018, Orlando, Florida, USA. 
4. Sarkar, S., Ejaz, N., & Maiti, J. (2018, March). Application of hybrid clustering technique for pattern extraction of accident at work: a case study of a steel industry. In 2018 4th International Conference on Recent Advances in Information Technology (RAIT) (pp. 1-6). IEEE. (Link: Paper) 

2017 (3) 

1. Sarkar, S., Kumar, A., Mohanpuria, S. K., & Maiti, J. (2017, November). Application of Bayesian network model in explaining occupational accidents in a steel industry. In 2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) (pp. 337-392). IEEE. (Link: Paper) 
2. Sarkar, S., Baidya, S., & Maiti, J. (2017, November). Application of rough set theory in accident analysis at work: a case study. In 2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) (pp. 245-250). IEEE. (Link: Paper) 
3. Sarkar, S., Pateshwari, V., & Maiti, J. (2017, July). Predictive model for incident occurrences in steel plant in India. In 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-5). IEEE. (Link: Paper) 

2016 (5) 

1. Sarkar, S., Vinay, S., Pateshwari, V., & Maiti, J. (2016, December). Study of optimized SVM for incident prediction of a steel plant in India. In 2016 IEEE Annual India Conference (INDICON) (pp. 1-6). IEEE. (Link: Paper) 
2. Sarkar, S., Patel, A., Madaan, S., & Maiti, J. (2016, December). Prediction of occupational accidents using decision tree approach. In 2016 IEEE Annual India Conference (INDICON) (pp. 1-6). IEEE. (Link: Paper) 
3. Maiti, J., Sarkar, S., Pardhu, S., & Ayi, R. (2016, November). Proactive data: A rich source of occupational accident prediction (Abstract only). In INFORMS Annual Meeting 2016, Nashville, Tennessee, USA. INFORMS. 
4. Sarkar, S., Lakha, V., Ansari, I., & Maiti, J. (2016, November). Text mining based prediction model for incident occurrences in steel plant (Abstract only). In INFORMS Annual Meeting 2016, Nashville, Tennessee, USA. INFORMS. 
5. Sarkar, S., Vinay, S., & Maiti, J. (2016, March). Text mining based safety risk assessment and prediction of occupational accidents in a steel plant. In 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT) (pp. 439-444). IEEE. (Link: Paper) 

2014 (2) 

1. Sarkar, S., & Sarkar, B. (2014). A new way to performance evaluation of technical institutions: Vikor approach. Proceeding of 2014 Global Sustainability Transitions: Impacts and Innovations, 209-216. (Link: Paper) 
2. Sarkar, S., & Sarkar, B. (2014). A De Novo approach for the Performance evaluation of Indian technical institutions. Global Journal of Finance and Management, 6(5), 457-468. (Link: Paper) 

Handbook chapter in Edited book 

2022 

1. Maiti, J., Sarkar, S., & Haight, J. (2022). Safety Analytics. In Maynard's Industrial and Systems Engineering Handbook, 6-th Edition, McGraw Hill Education, pp.- 405-420 (Chapter 24)- (Link: Paper)