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Research

Research drafts, academic papers in progress, technical studies, course research, and research notes. These are working archive entries, not formal claims.

2026Survey Paper
Completed

A Survey on Privacy-Preserving Machine Learning: Toward Feature-Level Selective Protection

A survey paper reviewing major privacy risks, protection techniques, and feature-level selective protection in privacy-preserving machine learning.

2026Literature review
Completed

AI-Based Optimization of Horizontal Handover in Mobile Networks: A Literature Review

A literature review on AI-based horizontal handover optimization in mobile networks, covering machine learning, reinforcement learning, LSTM prediction, and simulation-based evaluation.

2026Technical Review Paper
Completed

Pipelining in Computer Architecture: A Technical Review

A technical review explaining processor pipelining, the classical five-stage RISC pipeline, pipeline hazards, and performance improvement techniques.

2026Implementation-Based Technical Paper
Completed

Deep Learning-Based Drone Detection for Counter-UAV Cybersecurity Using YOLOv8

An implementation-based technical paper presenting a YOLOv8 drone detection system for counter-UAV cybersecurity with training, evaluation, and deployment workflows.

2026Technical Survey Paper
Completed

Artificial Intelligence in Semiconductor Manufacturing and Microprocessor Design: A Technical Survey

A technical survey on how AI supports semiconductor manufacturing, smart fabs, EDA workflows, chip floorplanning, and microprocessor design optimization.

2026Technical Review Paper
Completed

Secure Data Sharing in Cloud Computing: A Cryptographic Review and Methodology

A technical review paper on secure cloud data sharing, cryptographic protection methods, and a layered methodology for confidentiality, integrity, authentication, and auditing.

2026Conference Paper
Completed

Evaluating Machine Learning Models for Network Anomaly Detection in IoT Environments

A conference paper evaluating five machine learning models for binary IoT network anomaly detection using the cleaned ML-EdgeIIoT dataset.

2026Literature review
Draft

Evaluating Machine Learning Models for Network Anomaly Detection in IoT Environments

A literature review comparing machine learning and deep learning approaches for intrusion and anomaly detection in IoT networks.

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