Publications

Journals: (Selected)

1. Arju Bano, Monidipa Das, "Enhancing Model Explainability Through S-GuISE: A Spectral Clustering-guided Input Sampling Scheme for Explanation". Neurocomputing 650, 130750 (2025) [Accepted]

2. Suparna Dutta, Monidipa Das, and Ujjwal Maulik. "A Lightweight Aerial Scene Classifier Based on Adaptive Fusion of MobileNet and CapsNet." IEEE Signal Processing Letters (2025). [Accepted]

3. Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay, "Gen-GraphEx: Generative In-Distribution Graph Explanations for Time-Efficient Model-Level Interpretability of GNNs". IEEE Transactions on Neural Networks and Learning Systems (2025) [Accepted]

4. Suparna Dutta, Monidipa Das, Ujjwal Maulik, "Lightweight deep learning models for aerial scene classification: A comprehensive survey". Engineering Applications of Artificial Intelligence 142, 109859 (2024) [Accepted]

5. Rahul Dasharath Gavas, Monidipa Das, Soumya K. Ghosh, Arpan Pal, "Design of spatiotemporal variability index for climatic variables". Measurement, 231, p.114577. (2024)

6. Suparna Dutta, Monidipa Das, Ujjwal Maulik, "Toward Causality-Based Explanation of Aerial Scene Classifiers" IEEE Geoscience and Remote Sensing Letters, 21: 1-5 (2024)

7. Rahul Dasharath Gavas, Monidipa Das, Soumya K. Ghosh, Arpan Pal, "Spatial-SMOTE for handling imbalance in spatial regression tasks". Multimedia Tools and Applications, 83(5): 14111-14132 (2024)

8. Monidipa Das, Suparna Dutta, "GrapHiSM: a graph-based hierarchical semantics-driven model for aerial scene classification under scarcity of labelled samples". Applied Intelligence, 53(21): 25919-25930 (2023)

9. Suparna Dutta, Monidipa Das, "An autonomous lightweight model for aerial scene classification under labeled sample scarcity". Applied Intelligence, 53(19): 22216-22227 (2023)

10. Suparna Dutta, Monidipa Das, "Remote sensing scene classification under scarcity of labelled samples - A survey of the state-of-the-arts". Computers and Geosciences, 171: 105295 (2023)

11. Sucheta Dawn, Monidipa Das, Sanghamitra Bandyopadhyay, "SoURA: a user-reliability-aware social recommendation system based on graph neural network". Neural Computing and Applications, 35(25): 18533-18551 (2023)

12. Sucheta Dawn, Monidipa Das, Sanghamitra Bandyopadhyay, "GraMMy: Graph representation learning based on micro-macro analysis". Neurocomputing 506: 84-95 (2022)

13. Monidipa Das, Soumya K. Ghosh, Sanghamitra Bandyopadhyay, "A Multilayered Adaptive Recurrent Incremental Network Model for Heterogeneity-Aware Prediction of Derived Remote Sensing Image Time Series". IEEE Transactions on Geoscience and Remote. Sensing, 60: 1-13 (2022)

14. Monidipa Das, Akash Ghosh, Soumya K. Ghosh, "Does Climate Variability Impact COVID-19 Outbreak? An Enhanced Semantics-Driven Theory-Guided Model". SN Computer Science 2(6): 452 (2021)

15. Monidipa Das, “Real-time Prediction of Spatial Raster Time Series: A Context-aware Autonomous Learning Model”, Journal of Real-Time Image Processing, Springer. 2021 [DOI: https://doi.org/10.1007/s11554-021-01099-7]

16. Monidipa Das, Soumya K. Ghosh, "Reducing Parameter Value Uncertainty in Discrete Bayesian Network Learning: A Semantic Fuzzy Bayesian Approach". IEEE Trans. Emerging Topics in Computational Intelligence, vol. 5, no. 3, pp. 361-372  (2021)

17. Monidipa Das, “Analyzing impact of parental occupation on child's learning performance: a semantics-driven probabilistic approach". International Journal of Data Science and Analytics, vol. 12, no. 1, pp. 31-44 (2021)

18. Monidipa Das, Mahardhika Pratama, Soumya K. Ghosh, "SARDINE: A Self-Adaptive Recurrent Deep Incremental Network Model for Spatio-Temporal Prediction of Remote Sensing Data". ACM Trans. Spatial Algorithms Syst. 6(3): 16:1-16:26 (2020)

19. Monidipa Das, Soumya K. Ghosh, "Data-Driven Approaches for Spatio-Temporal Analysis: A Survey of the State-of-the-Arts". Journal of Computer Science and Technology, vol. 35, no. 3, pp. 665-696 (2020)

20. Monidipa Das, Soumya K. Ghosh, "FB-STEP: A fuzzy Bayesian network based data-driven framework for spatio-temporal prediction of climatological time series data". Expert Systems with Applications (ESWA, Elsevier), vol. 117, pp. 211-227 (2019)

21. Monidipa Das, Soumya K. Ghosh, “Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques". Pattern Recognition Letters (PRLETTERS), vol. 105, pp.155-164 (2018)

22. Monidipa Das, Soumya K. Ghosh, “A Deep Learning based Forecasting Ensemble to Predict Missing Data for Remote Sensing Analysis”. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2017 [DOI: 10.1109/JSTARS. 2017.2760202]

23. Monidipa Das, Soumya K. Ghosh, “Measuring Moran’s I in Cost-Efficient Manner to Describe Land-cover Change Pattern in Large-Scale Remote Sensing Imagery”. IEEE Jr. of Select.Topics in Applied Earth Observs. and Remote Sensing (JSTARS), 2017 

24. Monidipa Das, Soumya K. Ghosh, “semBnet: A Semantic Bayesian Network for Multivariate Prediction of Meteorological Time Series Data”. Pattern Recognition Letters (PRLETTERS), Elsevier, 2017

25. Monidipa Das, Soumya K. Ghosh, P. Gupta, V. M. Chowdary, R. Nagaraja, V. K. Dadhwal, “FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics using Spatial Bayesian Network (SpaBN)”. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE) 2017 

26. Monidipa Das, Soumya K. Ghosh, "Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data." IEEE Geoscience and Remote Sensing Letters (GRSL) 13.12 (2016): 1984-1988. 

27. Monidipa Das, Soumya K. Ghosh, V. Chowdary, A. Saikrishnaveni, and R. Sharma. "A probabilistic nonlinear model for forecasting daily water level in reservoir", Water Resources Management, vol. 30, no. 9, pp. 31073122, 2016.  

28. Monidipa Das, Soumya K. Ghosh, "Spatio-temporal Pattern Analysis for Regional Climate Change using Mathematical Morphology", ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. II-4/W2, pp. 185-192, 2015. [DOI: 10.5194/isprsannals-II-4-W2-185-2015]

Conferences: (selected)

1. Suparna Dutta, Monidipa Das, Ujjwal Maulik. "Lightweight Emergency-Net for Aerial Scene Classification", 6th International Conference on Data Science and Applications (ICDSA 2025), MNIT Jaipur, India, July 2025  (Accepted) 

2. Sanjib Chowdhury, Monidipa Das. "A Performance-Preserving Scheme for Classifying Differentially Private Remote Sensing Images", 7th International Conference on Recent Trends in Image Processing and Pattern Recognition, Bhopal, India, December 2024. Published by Procedia Computer Science, Vol. 260, 2024, Pages 761-767 

3. Yogeshkumar Sant, Monidipa Das. "CLayerCAM: A Model for Explaining Aerial Scene Classification using Convolutional Neural Network", International Conference on Machine Learning and Data Engineering (2024), Published in Procedia Computer Science, Vol. 258, 2024, Pages 4291-4300 

4. Arju Bano, Monidipa Das. "A Guided Input Sampling-based Perturbative Approach for Explainable AI in Image-based Application". In: 27th International Conference on Pattern Recognition (ICPR), December 01-05, 2024, Kolkata, India, Pages 144-162 (https://doi.org/10.1007/978-3-031-78128-5_10)

5. Nobin Sahu, Monidipa Das. "A Graph Isomorphism Network-based model for Privacy-Preserving Learning from Partially-Observed Sensitive Attributes". In: 5th International Conference on Data Science and Applications, July 17-19, 2024, MNIT Jaipur, India. Pages 285–298 (https://doi.org/10.1007/978-981-96-1188-1_21) 

6. Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay, "GraphEx: A User-Centric Model-Level Explainer for Graph Neural Networks". ICLR 2023

7. Aysha Basheer, Monidipa Das, Sanghamitra Bandyopadhyay. "TURBaN: A Theory-Guided Model for Unemployment Rate Prediction Using Bayesian Network in Pandemic Scenario". In: Hybrid Intelligent Systems 2022

8. Aysha Basheer, Monidipa Das, Sanghamitra Bandyopadhyay, “Theory-Guided Bayesian Analysis for Modeling Impact of COVID-19 on Gross Domestic Product”. IEEE Region 10 Conference (TENCON), November 1-4, 2022, Hong Kong

9. Monidipa Das, Suparna Dutta. “SELFIE: A Semantically-Enhanced Load Forecasting Approach with Indirect Estimate of Spatial Influences”. IEEE Region 10 Conference (TENCON), Dec 7-10, 2021, Auckland, New Zealand 

10. Suparna Dutta, Monidipa Das, “PReLim: A Modeling Paradigm for Remote Sensing Image Scene Classification under Limited Labeled Samples”. 9th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2021), ISI Kolkata, India, 15-18 December, 2021. 

11. Sucheta Dawn, Monidipa Das, S. Bandyopadhyay, “CateReR: A Graph Neural Network-based Model for Category-wise Reliability-aware Recommendation”. 9th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2021), ISI Kolkata, India, Dec, 2021. 

12. Sucheta Dawn, Monidipa Das, S. Bandyopadhyay, “SInGER: A Recommendation System based on Social-Influence-aware Graph Embedding Approach”.  18th IEEE India Conference (INDICON 2021), IIT Guwahati, India, 19-21 December, 2021. 

13. Sayan Saha, Monidipa Das, Sanghamitra Bandyopadhyay, "A Model-Centric Explainer for Graph Neural Network based Node Classification". CIKM 2022: 4434-4438, 2021

14. Monidipa Das, Soumya K. Ghosh, “Analyzing Impact of Climate Variability on COVID-19 Outbreak: A Semantically-enhanced Theory-guided Data-driven Approach”. In Proceedings of the 8th ACM IKDD CoDS and 26th COMAD, ACM, pp. 1-9. 2021. 

15. Monidipa Das,  “Online Prediction of Derived Remote Sensing Image Time Series: An Autonomous Machine Learning Approach”, In 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2020). IEEE, Waikoloa, Hawaii, USA, pp. 1496-1499. IEEE, 2020   

16. Monidipa Das, Mahardhika Pratama, T. Tjahjowidodo. “A Self-Evolving Mutually-Operative Recurrent Network-based Model for Online Tool Condition Monitoring in Delay Scenario”.  In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), pp. 2775-2783. 2020.

17. Monidipa Das, Mahardhika Pratama,  J. Zhang, Y. S. Ong. “A Skip-connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario”, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, USA, vol. 34, no. 04, pp. 3717-3724. 2020. 

18. Monidipa Das, Mahardhika Pratama, Septiviana Savitri, Zhang Jie, "MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification". IEEE International Conference on Data Mining (ICDM 2019), Beijing, China, November 2019 

19. Monidipa Das, Mahardhika Pratama, Andri Asfahani, Subhrajit Samanta, "FERNN: A Fast and Evolving Recurrent Neural Network Model for Streaming Data Classification". International Joint Conference on Neural Networks (IJCNN 2019), Budapest, Hungary, July 2019 

20. Monidipa Das, Soumya K. Ghosh, "Space-time Prediction of High Resolution Raster Data: An Approach based on Spatio-temporal Bayesian Network (STBN)". ACM India Joint International Conference on Data Science & Management of Data. COMAD/CODS 2019, pp. 129-135

21. Monidipa Das, Soumya K. Ghosh, Pramesh Gupta, Vemuri M. Chowdary, Ravoori Nagaraja, Vinay Kumar Dadhwal,"FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics Using Spatial Bayesian Network (SpaBN) (Extended Abstract)". ICDE 2018, pp. 1799-1800

22. Monidipa Das, Soumya K. Ghosh, “Spatio-temporal Prediction under Scarcity of Influencing Variables: A Hybrid Probabilistic Graph-based Approach”. In Proceedings of the 9th International Conference on Advances in Pattern Recognition (ICAPR-2017), ISI Bangalore, India, December 27-30, 2017. (accepted)

23. Monidipa Das, Soumya K. Ghosh, “BESTED: An Exponentially Smoothed Spatial Bayesian Analysis Model for Spatiotemporal Prediction of Daily Precipitation. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL’17), Redondo Beach, CA, USA, November 7–10, 2017, https://doi.org/10.1145/3139958.3140040

24. Monidipa Das, Soumya K. Ghosh, “Spatio-temporal Prediction of Meteorological Time Series Data: An Approach based on Spatial Bayesian Network (SpaBN)”. In Proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2017), Springer, ISI Kolkata, India, December 05-08, 2017. (accepted)

25. Monidipa Das, Soumya K. Ghosh. “Spatio-temporal Autocorrelation Analysis for Regional Land-cover Change Detection from Remote Sensing Data”. In Proceedings of the 4th IKDD Conference on Data Science (CoDS), ACM, 2017.

26. Monidipa Das, "Data-Driven Modeling for Spatio-temporal Prediction", 3rd ACM SIGSPATIAL PhD Symposium, 2016. (Accepted [not presented])

27. Monidipa Das, Soumya K. Ghosh. “A cost-efficient approach for measuring Moran's index of spatial autocorrelation in geostationary satellite data”. In IEEE International Conference on Geoscience and Remote Sensing Symposium (IGARSS 2016). pp. 5913-5916. IEEE, 2016. 

28. Monidipa Das, Soumya K. Ghosh. Modeling spatio-temporal change pattern using mathematical morphology. In Proceedings of the 3rd IKDD Conference on Data Science (CoDS), page 4. ACM, 2016. 

29. Monidipa Das, Soumya K. Ghosh, “Spatio-temporal Pattern Analysis for Regional Climate Change using Mathematical Morphology”, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-4/W2, 2015, July, 2015 

30. Monidipa Das, Soumya K. Ghosh, “Detection of Climate Zones using Multifractal Detrended Cross-Correlation Analysis: A Spatio-temporal Data Mining Approach”, 8th International Conference on Advances in Pattern Recognition (ICAPR-2015), ISI, Kolkata, India, IEEE, January, 2015 

31. Monidipa Das, Soumya K. Ghosh, “A Probabilistic Approach for Weather Forecast using Spatio-temporal Inter-relationships among Climate Variables”, 9th IEEE International Conference on Industrial and Information Systems (ICIIS-2014), ABV-IIITM, Gwalior, India, December, 2014 

32. Monidipa Das, Soumya K. Ghosh, “Short-term Prediction of Land Surface Temperature using Multifractal Detrended Fluctuation Analysis”, 11th IEEE India Conference (INDICON-2014), Yashada, Pune, India, December, 2014 

33. Monidipa Das, Jaya Sil, “Query Selection using Fuzzy Measures to Diagnose Diseases”. International Conference on (AIM), India 2013, ACEEE Conference Series, Elsevier, vol. 1, pp. 246-254, 2013

Book Chapters:

1. Sucheta Dawn, Monidipa Das, Sanghamitra Bandyopadhyay. “Graph Representation Learning for Protein Classification”, Artificial Intelligence Technologies for Computational Biology,  [edited by Ranjeet Kumar Rout, Saiyed Umer, Sabha Sheikh and A. L. Sangal], CRC Press, Taylor & Francis Group. 2022

2. Atul Patel, Monidipa Das, Soumya K. Ghosh, "Short-Term Load Forecasting: An Intelligent Approach Based on Recurrent Neural Network". In Advances in Intelligent Systems and Computing, vol 1179. Springer, pp. 52-62

3. Monidipa Das, Soumya K. Ghosh. "Performance Analysis for NFBN—A New Fuzzy Bayesian Network Learning Approach". In Recent Findings in Intelligent Computing Techniques. Advances in Intelligent Systems and Computing, vol 708.pp. 363-376, Springer, Singapore

Books:

1. Monidipa Das, Soumya K. Ghosh, V. M. Chowdary, Pabitra Mitra and Santosh Rijal (Eds.), "Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements", Remote Sensing, MDPI, ISBN 978-3-0365-4591-2 (PDF) https://doi.org/10.3390/books978-3-0365-4591-2 

2. Monidipa Das, Soumya K. Ghosh, "Enhanced Bayesian Network Models for Spatial Time Series Prediction - Recent Research Trend in Data-Driven Predictive Analytics". Studies in Computational Intelligence 885, Springer 2020, ISBN 978-3-030-27748-2