Conferences (36)

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2026 (5)

1. 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. Accepted & to be presented. (Link: https://ficta.co.uk/)

2. 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. Accepted & to be presented. (Link: https://ol2a.ipb.pt/ui/#/home)

3. 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. - Accepted & presented. (Link: https://www.iccece.com/)

4. 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. - Accepted & presented. (Link: https://www.iccece.com/)

5. Jaiswal, B. & Sarkar, S.  (2026, Jan). Employee Attrition Prediction Using Machine Learning Approaches. In the 7th Mediterranean Conference on Pattern Recognition and Artificial Intelligence. Springer. - Accepted & presented. (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. - Accepted & presented. (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)