Journals
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[2026]
Singh, A., Saini, N., Zervoudakis, K., & Tiwari,
V. (2026): PULSE: A Multi-Stage Artificial Intelligence Framework
for Analyzing Vaccine Hesitancy on Twitter Using Particle Swarm
Optimization and Large Language Models,
Swarm and Evolutionary Computation DOI:
10.1016/j.swevo.2025.102218
(IF: 8.5)
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[2026]
Singh, Y., Saini, N. & Tiwari, V.K. (2026):
Towards Unified Multi-View Ensemble Models for Multi-Label Podcast
Genre Prediction,
The Journal of Supercomputing (IF: 2.7)
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[2025]
Pooja, K. M., Long, C., & Sun, A. (2025): PGMEL:
Policy Gradient-based Generative Adversarial Network for
Multimodal Entity Linking,
arXiv preprint arXiv:2510.02726. URL:
https://arxiv.org/abs/2510.02726
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[2024]
S. Palmal, S. Saha, Nikhilanand Arya, and S.
Tripathy. (2024): CAGCL: Predicting Short- and Long-Term Breast
Cancer Survival with Cross-Modal Attention and Graph Contrastive
Learning,
IEEE Journal of Biomedical and Health Informatics. DOI:
10.1109/JBHI.2024.3449756
(IF: 6.7)
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[2024]
A. Mathur, Nikhilanand Arya, K. Pasupa, S. Saha,
S. Roy, and S. Saha. (2024): Breast cancer prognosis through the
use of multi-modal classifiers: Current state of the art and the
way forward, Briefings in Functional Genomics,
Oxford University Press. DOI:
https://doi.org/10.1093/bfgp/elae015
(IF: 4.3)
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[2024]
S. Palmal, Nikhilanand Arya, S. Saha, S.
Tripathy. (2024): Integrative prognostic modeling for breast
cancer: Unveiling optimal multimodal combinations using graph
convolutional networks and calibrated random forest,
Applied Soft Computing. DOI:
10.1016/j.asoc.2024.111379
(IF: 8.7)
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[2023]
Nikhilanand Arya, and S. Saha. (2023):
Deviation-support based fuzzy ensemble of multi-modal deep
learning classifiers for breast cancer prognosis prediction,
Scientific Reports. DOI:
10.1038/s41598-023-47543-5
(IF: 4.9)
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[2023]
S. Palmal, Nikhilanand Arya, S. Saha, and S.
Tripathy. (2023): Breast cancer survival prognosis using the graph
convolutional network with Choquet fuzzy integral,
Scientific Reports. DOI:
10.1038/s41598-023-40341-z
(IF: 4.9)
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[2023]
Nikhilanand Arya, S. Saha, A. Mathur, and S.
Saha. (2023): Improving the robustness and stability of a machine
learning model for breast cancer prognosis through the use of
multi-modal classifiers, Scientific Reports. DOI:
10.1038/s41598-023-30143-8
(IF: 4.9)
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[2023]
Saini, N., Reddy, S., Saha, S., Moreno J.G., &
Doucet, A. (2022): Multi-view multi-objective clustering-based
framework for scientific document summarization using citation
context, Applied Intelligence. DOI:
https://doi.org/10.1007/s10489-022-04166-z
(IF: 5.01)
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[2022]
Nikhilanand Arya, A. Mathur, S. Saha, and S.
Saha. (2022): Proposal of SVM Utility Kernel for Breast Cancer
Survival Estimation,
IEEE/ACM Transactions on Computational Biology and
Bioinformatics. DOI:
10.1109/TCBB.2022.3198879
(IF: 4.5)
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[2021]
Nikhilanand Arya, and S. Saha. (2021): Generative
Incomplete Multi-View Prognosis Predictor for Breast Cancer:
GIMPP,
IEEE/ACM Transactions on Computational Biology and
Bioinformatics. DOI:
10.1109/TCBB.2021.3090458
(IF: 4.5)
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[2021]
D. Bansal, R. Grover, Saini, N., & Saha, S.
(2021): GenSumm: A Joint Framework for Multi-task Tweet
Classification and Summarization using Sentiment Analysis and
Generative Modelling,
IEEE Transactions on Affective Computing. DOI:
https://doi.org/10.1109/TAFFC.2021.3131516
(IF: 10.506)
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[2021]
D. Bansal, Saini, N., S., & Saha, S..: DCBRTS: A
Classification-Summarization Approach for Evolving Tweet Streams
in Multiobjective Optimization Framework,
IEEE Access. DOI:
https://doi.org/10.1109/ACCESS.2021.3120112
(IF: 3.367)
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[2021]
Saini, N., S., Saha, S., Bhattacharyya, P.,
Mrinal, S. & Mishra, S.: On Multi-modal Microblog Summarization,
IEEE Transactions On Computational Social Systems. DOI:
https://doi.org/10.1109/TCSS.2021.3110819
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[2021]
Saini, N., Saha, S.: Multi-objective Optimization
Techniques: A Survey of the State-of-the-Art and Applications,
European Physical Journal Special Topics. DOI:
10.1140/epjs/s11734-021-00206-w
(IF: 1.668).
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[2020]
Nikhilanand Arya, and S. Saha. (2020):
Multi-Modal Classification for Human Breast Cancer Prognosis
Prediction: Proposal of Deep-Learning Based Stacked Ensemble
Model,
IEEE/ACM Transactions on Computational Biology and
Bioinformatics. DOI:
10.1109/TCBB.2020.3018467
(IF: 4.5)
Conferences
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[2024]
Singh, A., Saini, N. & Tiwari, S., (2024, Aug).
Unraveling COVID-19 Vaccine Hesitancy: A Multi-Label
Classification Approach Using Nested LSTM. In
Proceedings of the 31st International Conference on Neural
Information Processing (ICONIP 2024). (In Press)
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[2024]
Verma, C., Saini, N. & Shukla, S., (2024, Aug).
Harmonizing Data: Multilingual, Multistep Deep Learning Approach
for Classifying Audio Content into Songs, Podcasts (Talk), and
Advertisement. In
Proceedings of the 31st International Conference on Neural
Information Processing (ICONIP 2024). (In Press)
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[2024]
Bangde, Y. & Saini, N., (2024, Aug). Multi-view
Ensemble Clustering-based Podcast Recommendation in Indian
Regional Setting. In
Proceedings of the 27th International Conference on Pattern
Recognition (ICPR 2024). DOI:
https://doi.org/10.1007/978-3-031-78107-0_12
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[2024]
Goswami, S., Saini, N., & Shukla, S. (2024,
June). Incorporating Domain Knowledge in Multi-objective
Optimization Framework For Automating Indian Legal Case
Summarization. In
Proceedings of the 27th International Conference on Pattern
Recognition (ICPR 2024). DOI:
https://doi.org/10.1007/978-3-031-78495-8_17
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[2024]
Parmar, J., Saini, N., & Dey, D. (2024, March).
An Unsupervised Evolutionary Approach for Indian Regional Language
Summarization. In
Proceedings of the The IEEE World Congress on Computational
Intelligence (IEEE WCCI 2024). DOI:
https://doi.org/10.1109/CEC60901.2024.10612059
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[2023]
Nikhilanand Arya, K. Gupta, & S. Saha (2023,
July). SARS-CoV-2 Detection: Radiology based Multi-modal
Multi-task Framework. In
Proceedings of the 45th Annual International Conference of the
IEEE Engineering in Medicine & Biology Conference (EMBC). DOI:
10.1109/EMBC40787.2023.10340386