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ভারতীয় বিজ্ঞান শিক্ষা এবং গবেষণা প্রতিষ্ঠান কলকাতা

भारतीय विज्ञान शिक्षा एवं अनुसंधान संस्थान कोलकाता

INDIAN INSTITUTE OF SCIENCE EDUCATION AND RESEARCH KOLKATA

... towards excellence in science

An Autonomous Institution, Under the Ministry of Education, Government of India

Monidipa Das

Assistant Professor
Dept: Departement of Computational and Data Sciences (CDS)
E-mail: monidipa [at] iiserkol.ac.in

All Publications:

  1. Gavas, Rahul Dasharath; Das, Monidipa; Ghosh, Soumya K and Pal, Arpan. 2024."Spatial-SMOTE for handling imbalance in spatial regression tasks." Multimedia Tools and Applications, 83, 14111-32
  2. Dutta, Suparna; Das, Monidipa and Maulik, Ujjwal. 2024."Toward Causality-Based Explanation of Aerial Scene Classifiers." IEEE Geoscience and Remote Sensing Letters, 21, 1-5
  3. Gavas, Rahul Dasharath; Das, Monidipa; Ghosh, Soumya K and Pal, Arpan. 2024."Design of spatiotemporal variability index for climatic variables." Measurement, 231, 114577
  4. Dawn, Sucheta; Das, Monidipa and Bandyopadhyay, Sanghamitra. 2023."SoURA: a user-reliability-aware social recommendation system based on graph neural network." Neural Computing and Applications, 35, 18533-51
  5. Dutta, Suparna and Das, Monidipa. 2023."Remote Sensing Scene Classi?cation under Scarcity of Labelled Samples— A Survey of the State-of-the-arts." Computers and Geosciences, 171, 105295
  6. Dutta, Suparna and Das, Monidipa. 2023."An autonomous lightweight model for aerial scene classification under labeled sample scarcity." Applied Intelligence, 53, 22216-27
  7. Das, Monidipa and Dutta, Suparna. 2023."GrapHiSM: a graph-based hierarchical semantics-driven model for aerial scene classification under scarcity of labelled samples." Applied Intelligence, 53, 25919-30
  8. Dawn, Sucheta; Das, Monidipa and Bandyopadhyay, Sanghamitra. 2022."GraMMy: Graph representation learning based on micro-macro analysis." Neurocomputing, 506, 84-95
  9. Das, Monidipa; Ghosh, Soumya K and Bandyopadhyay, Sanghamitra. 2022."A Multi-layered 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
  10. Das, Monidipa and Ghosh, Soumya K. 2021."Reducing Parameter Value Uncertainty in Discrete Bayesian Network Learning: A Semantic Fuzzy Bayesian Approach." IEEE Transactions on Emerging Topics in Computational Intelligence, 5, 361-372
  11. Das, Monidipa. 2021."Real-time Prediction of Spatial Raster Time Series: A Context-aware Autonomous Learning Model." Journal of Real-Time Image Processing, 18, 1591–1605
  12. Das, Monidipa; Pratama, M and Ghosh, Soumya K. 2020."SARDINE: A Self-Adaptive Recurrent Deep Incremental Network Model for Spatio-Temporal Prediction of Remote Sensing Data." ACM Transactions on Spatial Algorithms and Systems, 6, 1-26
  13. Das, Monidipa and Ghosh, Soumya K. 2019."Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques." Pattern Recognition Letters, 105, 155-164
  14. Das, Monidipa and Ghosh, Soumya K. 2019."FB-STEP: A fuzzy Bayesian network based data-driven framework for spatio-temporal prediction of climatological time series data." Expert Systems with Applications, 117, 211-227
  15. Das, Monidipa; Ghosh, Soumya K; Chowdary, V M; Nagaraja, R and Dadhwal, V K. 2017."FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics using Spatial Bayesian Network (SpaBN)." IEEE Transactions on Knowledge and Data Engineering, 29, 842 - 855
  16. Das, Monidipa and Ghosh, Soumya K. 2017."semBnet: A Semantic Bayesian Network for Multivariate Prediction of Meteorological Time Series Data." Pattern Recognition Letters, 93, 192-201
  17. Das, Monidipa and Ghosh, Soumya K. 2017."Measuring Moran’s I in Cost-Efficient Manner to Describe Land-cover Change Pattern in Large-Scale Remote Sensing Imagery." IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 10, 2631-2639
  18. Das, Monidipa and Ghosh, Soumya K. 2017."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, 10, 5228-5236
  19. Das, Monidipa; Ghosh, Soumya K; Chowdary, V M; Saikrishnaveni, A and Sharma, R. 2016."A probabilistic nonlinear model for forecasting daily water level in reservoir." Water Resources Management, 30, 31073122
  20. Das, Monidipa and Ghosh, Soumya K. 2016."Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data." IEEE Geoscience and Remote Sensing Letters (GRSL), 13, 1984-88

  1. Bano, Arju and Das, Monidipa. 2024." A Guided Input Sampling-based Perturbative Approach for Explainable AI in Image-based Application", "27th International Conference on Pattern Recognition". Springer,
  2. Sahu, Nobin Trinath and Das, Monidipa. 2024." A Graph Isomorphism Network-based model for Privacy-Preserving Learning from Partially-Observed Sensitive Attributes", "5th International Conference on Data Science and Applications". Springer,
  3. Saha, Sayan; Das, Monidipa and Bandyopadhyay, Sanghamitra. 2023." GraphEx: A User-Centric Model-Level Explainer for Graph Neural Networks", "ICLR". OpenReview.net,
  4. Dawn, Sucheta; Das, Monidipa and Bandyopadhyay, Sanghamitra. 2022." Graph Representation Learning for Protein Classification", "Artificial Intelligence Technologies for Computational Biology". CRC Press, Taylor & Francis Group, ISBN: 9781003246688
  5. Saha, Sayan; Das, Monidipa and Bandyopadhyay, Sanghamitra. 2021." A Model-Centric Explainer for Graph Neural Network based Node Classification", "CIKM". ACM,
  6. Das, Monidipa and Ghosh, Soumya K. 2020." Performance Analysis for NFBN—A New Fuzzy Bayesian Network Learning Approach", "Recent Findings in Intelligent Computing Techniques. Advances in Intelligent Systems and Computing". Springer, ISBN: 9789811086366
  7. Das, Monidipa; Pratama, M and Tjahjowidodo, T. 2020." 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". ACM,
  8. Das, Monidipa and Ghosh, Soumya K. 2020." ", "Enhanced Bayesian Network Models for Spatial Time Series Prediction - Recent Research Trend in Data-Driven Predictive Analytics". Springer Nature Switzerland AG, ISBN: 9783030277482
  9. Das, Monidipa. 2020." Online Prediction of Derived Remote Sensing Image Time Series: An Autonomous Machine Learning Approach", "IEEE International Geoscience and Remote Sensing Symposium". IEEE,
  10. Das, Monidipa; Pratama, M; Zhang, J and Ong, Y S. 2020." A Skip-connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario", "Thirty-Fourth AAAI Conference on Artificial Intelligence ". AAAI,
  11. Das, Monidipa; Pratama, M; Savitri, S and Zhang, J. 2019." MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification", "IEEE International Conference on Data Mining". IEEE,
  12. Das, Monidipa; Pratama, M and Samanta, S. 2019." FERNN: A Fast and Evolving Recurrent Neural Network Model for Streaming Data Classification", "International Joint Conference on Neural Networks". IEEE,
  13. Das, Monidipa and Ghosh, Soumya K. 2017." 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,
  14. Das, Monidipa and Ghosh, Soumya K. 2016." A cost-efficient approach for measuring Moran's index of spatial autocorrelation in geostationary satellite data", "IEEE International Conference on Geoscience and Remote Sensing Symposium". IEEE,
  15. Das, Monidipa and Ghosh, Soumya K. 2016." Modeling spatio-temporal change pattern using mathematical morphology", "In Proceedings of the 3rd IKDD Conference on Data Science". ACM,