Mohammad Masudur Rahman

Orcid: 0000-0001-8091-511X

Affiliations:
  • Bangladesh University of Engineering and Technology, Dhaka, Bangladesh


According to our database1, Mohammad Masudur Rahman authored at least 10 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Exploring the Ethical Concerns in User Reviews of Mental Health Apps using Topic Modeling and Sentiment Analysis.
CoRR, February, 2026

A Scoping Review of Deep Learning for Urban Visual Pollution and Proposal of a Real-Time Monitoring Framework with a Visual Pollution Index.
CoRR, February, 2026

2025
Surgeons Are Indian Males and Speech Therapists Are White Females: Auditing Biases in Vision-Language Models for Healthcare Professionals.
Proceedings of the IEEE International Conference on Data Mining, 2025

Extracting Latent Insights and Tagging Fall Injuries from Clinical Narratives Using Unsupervised Learning.
Proceedings of the IEEE International Conference on Big Data, 2025

2024
Smart reception: An artificial intelligence driven bangla language based receptionist system employing speech, speaker, and face recognition for automating reception services.
Eng. Appl. Artif. Intell., 2024

2023
Exploring Federated Learning with Naïve Bayes using AVC Information.
Proceedings of the 14th International Conference on Computing Communication and Networking Technologies, 2023

2021
Generating Cyber Threat Intelligence to Discover Potential Security Threats Using Classification and Topic Modeling.
CoRR, 2021

A Health Service Delivery Relational Agent for the COVID-19 Pandemic.
Proceedings of the Next Wave of Sociotechnical Design, 2021

2020
Internet of Things (IoT): Vulnerabilities, Security Concerns and Things to Consider.
Proceedings of the 11th International Conference on Computing, 2020

Adaptive Feature Selection and Classification of Colon Cancer From Gene Expression Data: an Ensemble Learning Approach.
Proceedings of the ICCA 2020: International Conference on Computing Advancements, 2020


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