Conferences (38)

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2026 (7)

1. Bhanushali, J., Sarkar, S., & Pramanik, A. (2026, Oct). Powering the Future: EV Charging Infrastructure Planning Using Machine Learning and Stochastic Optimization Techniques. In TENCON 2026, Bali, Indonesia. Accepted & to be presented. (Link)

2. 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)

3. 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/)

4. 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)

5. 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).  

6. 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).  

7. 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)