Academic Profile

Mr. Hassan Ahmed is an Instructor in Computer Science with a strong academic and research background in artificial intelligence, machine learning, and deep learning. He holds a Master of Science in Computer Science, with a thesis that focused on deep learning-based intrusion detection systems for autonomous vehicles. His recent research interests include deep learning, explainable AI, medical imaging, and large language models. He is committed to utilizing technology-driven research to address real-world problems, particularly in healthcare and safety-critical domains.

Editorial Roles

No Editorial Roles

This user currently does not serve as an editor for any ICCK journals.

ICCK Publications

Total Publications: 1
Open Access | Research Article | 02 January 2026
Enhancing Social Media Bot Detection with Cross-Feature Gating and Residual Learning
ICCK Transactions on Emerging Topics in Artificial Intelligence | Volume 3, Issue 1: 20-32, 2026 | DOI: 10.62762/TETAI.2025.791029
Abstract
The growing presence of malicious bot accounts on social media poses a threat to the authenticity of online communities, as they amplify misinformation, spread spam, and manipulate engagement. Reliable detection of these accounts is therefore essential to protect the integrity of platforms such as Instagram. This study introduces a deep learning–based detection framework built on the CrossGatedTabular (CGT) architecture, designed to learn complex patterns in user activity. To strengthen evaluation, two publicly available datasets of Instagram accounts were merged into a comprehensive benchmark representing diverse user behaviors. Natural language processing (NLP) was applied to refine text... More >

Graphical Abstract
Enhancing Social Media Bot Detection with Cross-Feature Gating and Residual Learning