Muhammad Shahid Anwar

Assistant Professor

Gachon University

South Korea

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About

Dr. Muhammad Shahid Anwar is an Assistant Professor at Gachon University, South Korea. His research areas include machine learning applications, privacy-preserving AI, and deep learning methods for low-resource languages. He has recently published articles focusing on topics such as load forecasting, sarcasm detection, and the healthcare utility of chipless RFID sensors.

Articles (20)

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2025

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2024

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2024

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2024

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2024

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

Collaborators (7)

Musaed Alhussein

SAUDI ARABIA

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Javed Ali Khan

University of Hertfordshire

UNITED KINGDOM

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Khursheed Aurangzeb

SAUDI ARABIA

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Gauhar Ali

SAUDI ARABIA

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Ahyoung Choi

SOUTH KOREA

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Jaroslav Frnda

SLOVAKIA

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Andrew Hines

Assistant Professor

Dublin City University

IRELAND

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Muhammad Shahid Anwar

Research Interests

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About

Articles (20)

Hybrid long short-term memory and bidirectional multichannel network cascaded with split convolution for short-term load forecasting

A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities

A Moving Metaverse: QoE challenges and standards requirements for immersive media consumption in autonomous vehicles

AD-CAM: Enhancing Interpretability of Convolutional Neural Networks With a Lightweight Framework - From Black Box to Glass Box

A novel transformer attention-based approach for sarcasm detection

Privacy-preserving AI for early diagnosis of thoracic diseases using IoTs: A federated learning approach with multi-headed self-attention for facilitating cross-institutional study

Pashto poetry generation: deep learning with pre-trained transformers for low-resource languages

Pashto script and graphics detection in camera captured Pashto document images using deep learning model

Range aware message drop policy for delay tolerant networks

A Comprehensive Study of Chipless RFID Sensors for Healthcare Applications

Robust Approach for Global Stabilization of a Class of Underactuated Mechanical Systems in Presence of Uncertainties

NeuPD—A Neural Network-Based Approach to Predict Antineoplastic Drug Response

Applying Enhanced Real-Time Monitoring and Counting Method for Effective Traffic Management in Tashkent

A Computationally Efficient Distributed Framework for a State Space Adaptive Filter for the Removal of PLI from Cardiac Signals

Cyber Forensic Investigation Infrastructure of Pakistan: An Analysis of the Cyber Threat Landscape and Readiness

Multi-Clustered Mathematical Model for Student Cognitive Skills Prediction Optimization

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images

Validation of Parallel Distributed Adaptive Signal Processing (PDASP) Framework through Processing-Inefficient Low-Cost Platforms

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images

Optimization of Students’ Performance Prediction through an Iterative Model of Frustration Severity

Collaborators (7)

Musaed Alhussein

Javed Ali Khan

Khursheed Aurangzeb

Gauhar Ali

Ahyoung Choi

Jaroslav Frnda

Andrew Hines

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