Excellence in Academia Award
Sini Raj Pulari
Abu Dhabi University,United Arab Emirates
The Excellence in Academia Award profile presents the scholarly work of Sini Raj Pulari, an academic researcher affiliated with Abu Dhabi University in the United Arab Emirates. The supplied publication record highlights contributions to automatic text summarization, reinforcement learning, generative artificial intelligence, Internet of Things (IoT) communications, and AI-assisted disease prediction. These topics reflect contemporary research interests in intelligent computing, language technologies, and data-driven applications.
Abstract
Sini Raj Pulari’s listed research from 2025 addresses several developing areas of computer science, particularly natural language processing, generative AI, reinforcement learning, IoT communication, and computational healthcare. The publications examine text summarization methods, human-feedback-guided model refinement, emerging directions in generative AI, and AI/ML applications associated with sustainable development. The supplied Scopus profile reports 39 documents, 115 citations, and an h-index of 7. These indicators provide a quantitative snapshot of the research record, while the publication topics offer context for assessing its breadth. [1]
Keywords
Computer science; artificial intelligence; natural language processing; automatic text summarization; reinforcement learning; generative AI; Internet of Things; machine learning; large language models; healthcare prediction.
Introduction
Artificial intelligence is transforming how information is processed, interpreted, and applied across research and professional settings. Text summarization supports the efficient interpretation of lengthy documents, while generative models and reinforcement learning offer approaches for improving system responses. IoT communication research extends these capabilities to connected environments, and multimodal prediction explores the integration of heterogeneous data. Pulari’s supplied publication list intersects with these research directions through five works published or listed in 2025. [2]
Research Profile
The available records associate Pulari with research spanning language processing, AI-assisted prediction, and emerging computational methods. The listed publications include journal articles and book chapters, suggesting engagement with both research dissemination and broader technical discussions. The supplied institutional affiliation is Abu Dhabi University. Detailed employment history, educational qualifications, and project leadership are not established by the information provided and should be verified through authoritative institutional sources before publication.
Research Contributions
The listed work on automatic text summarization examines extractive, abstractive, and hybrid approaches. Another article considers fine-tuned reinforcement learning from human feedback and prompting methods for news summarization. These themes concern the production of concise, useful text while addressing the quality and relevance of generated outputs. Additional chapters discuss generative AI and AI/ML-supported IoT communications in relation to sustainable development. A further journal article addresses multimodal disease prediction using generated prompts and large language models. [3]
Publications
The five supplied records dated 2025 are listed below. Their bibliographic details and DOI identifiers should be checked against the publisher records.
- “A Comprehensive and Systematic Exposition on Automatic Text Summarization Technique: A Deeper Coverage on Extractive, Abstractive and Hybrid Methods.” Fusion Practice and Applications. DOI: 10.54216/FPA.200114.
- “Future Trends and Innovations in IoT-based Communication Through AI/ML for SDG.” Book chapter. DOI: 10.1002/9781394337262.ch14.
- “Generative AI – Challenges and Future Directions.” Book chapter. DOI: 10.1201/9781003533009-20.
- “Improved Fine-Tuned Reinforcement Learning From Human Feedback Using Prompting Methods for News Summarization.” International Journal of Interactive Multimedia and Artificial Intelligence. DOI: 10.9781/ijimai.2025.02.001.
- “Optimizing Multimodal Personalized Disease Prediction Accuracy Using Generated Prompts and Large Language Models.” Image and Vision Computing. DOI: 10.1016/j.imavis.2025.105649.
Research Impact
The supplied bibliometric figures—115 citations and an h-index of 7 across 39 documents—provide an initial indication of scholarly visibility. Citation totals and author indices change over time and depend on database coverage, attribution, and update schedules. They should therefore be presented with a retrieval date when used in formal evaluation. The publication themes also indicate potential relevance to language technology, connected systems, and computational health research. [1]
Award Suitability
The listed publications and reported bibliometric indicators provide material for consideration under an academic recognition category. Relevant assessment criteria may include publication quality, originality, documented research contribution, reproducibility, collaboration, and verified scholarly influence. Inclusion in this profile does not itself establish that an award has been granted; eligibility and final recognition remain subject to the event’s official assessment and confirmation.
Conclusion
Sini Raj Pulari’s supplied 2025 publication records cover several active areas of computer science, from summarization and generative AI to IoT communication and multimodal prediction. Together with the reported Scopus metrics, these records provide a basis for reviewing the research profile in the context of academic recognition. Independent verification of publications, affiliation, and bibliometric data is recommended to maintain accuracy and transparency.
External Links
References
- Elsevier. (n.d.). Scopus author details: Sini Raj Pulari, Author ID 57939225700. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57939225700
- Pulari, S. R. (2025). A comprehensive and systematic exposition on automatic text summarization technique: A deeper coverage on extractive, abstractive and hybrid methods. Fusion Practice and Applications. DOI: https://doi.org/10.54216/FPA.200114. Author attribution should be confirmed against the publisher record.
- Pulari, S. R. (2025). Improved fine-tuned reinforcement learning from human feedback using prompting methods for news summarization. International Journal of Interactive Multimedia and Artificial Intelligence. DOI: https://doi.org/10.9781/ijimai.2025.02.001. Author attribution should be confirmed against the publisher record.
- Pulari, S. R. (2025). Optimizing multimodal personalized disease prediction accuracy using generated prompts and large language models. Image and Vision Computing. DOI: https://doi.org/10.1016/j.imavis.2025.105649. Author attribution should be confirmed against the publisher record.
- Pulari, S. R. (2025). Future trends and innovations in IoT-based communication through AI/ML for SDG. Book chapter. DOI: https://doi.org/10.1002/9781394337262.ch14. Author attribution should be confirmed against the publisher record.
- Pulari, S. R. (2025). Generative AI—Challenges and future directions. Book chapter. DOI: https://doi.org/10.1201/9781003533009-20. Author attribution should be confirmed against the publisher record.