Md Abdus Salam Siddique Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
unknown
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Md Abdus Salam Siddique's research focuses on the application of machine learning and artificial intelligence techniques to address challenges in various domains. His work includes developing algorithms for toxicity classification on text data, such as music lyrics, and enhancing disease detection in aquaculture using convolutional neural networks. He has also investigated unsupervised entity resolution through graph-based methods, including hierarchical record clustering and composite modularity optimization. Additionally, his research extends to creating privacy-preserving systems for document question answering and has explored medical applications, such as corneal clarity assessment following phacoemulsification. Siddique's scholarly contributions are reflected in his h-index of 2 and a total of 8 publications, with 28 citations. He has collaborated with researchers from Arkansas Tech University and the University of Arkansas at Little Rock.
Metrics
- h-index: 2
- Publications: 8
- Citations: 33
Selected Publications
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Privacy-Preserving RAG System for Personal Document Question Answering (2026)
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Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis (2025)
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ModER: Graph-based Unsupervised Entity Resolution using Composite Modularity Optimization and Locality Sensitive Hashing (2022)
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Toxicity Classification on Music Lyrics Using Machine Learning Algorithms (2021)
Collaboration Network
Top Collaborators
- ModER: Graph-based Unsupervised Entity Resolution using Composite Modularity Optimization and Locality Sensitive Hashing
- Graph-based hierarchical record clustering for unsupervised entity resolution
- ModER: Graph-based Unsupervised Entity Resolution using Composite Modularity Optimization and Locality Sensitive Hashing
- Graph-based hierarchical record clustering for unsupervised entity resolution
- Toxicity Classification on Music Lyrics Using Machine Learning Algorithms
- Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis
- Toxicity Classification on Music Lyrics Using Machine Learning Algorithms
- Toxicity Classification on Music Lyrics Using Machine Learning Algorithms
- ModER: Graph-based Unsupervised Entity Resolution using Composite Modularity Optimization and Locality Sensitive Hashing
- Corneal Clarity after Phacoemulsification: Nuclear Management by Stop and Chop Method
- Corneal Clarity after Phacoemulsification: Nuclear Management by Stop and Chop Method
- Corneal Clarity after Phacoemulsification: Nuclear Management by Stop and Chop Method
- Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis
- Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis
- Privacy-Preserving RAG System for Personal Document Question Answering
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