ALTAF HUSSAIN

About

Altaf Hussain received his Master’s degree in the field of “IoT, Computer Vision, and Deep Learning” from Islamia College Peshawar, Peshawar, Pakistan in 2020. He is currently pursuing his Ph.D. degree with the Department of Software Convergence, at Sejong University, Seoul, South Korea. He is working as a Research Assistant at the Intelligent Media Laboratory (IM Lab), at Sejong University. His major research interest includes action and activity recognition, video and image analytics, surveillance video analysis, energy informatics, IoT, IIoT, machine learning, and deep learning. Furthermore, he is serving as a reviewer in several well-reputed journals

Employment

• Korea Advanced Institute of Science and Technology Postdoctoral Researcher
  2026 - Present

Education

• Korea Advanced Institute of Science and Technology: Daejeon, Daejeon, KR Postdoctoral Researcher
  2026 - Present
• Sejong University PhD
  2021 - Present
• Islamia College Peshawar MS
  2017 - 2020

Projects & Funding

Projects & funding information is unavailable.

Publications (19)

• Differential attention transformer-enhanced graph neural network for accurate material property prediction
  Engineering Applications of Artificial Intelligence 2026 DOI: 10.1016/j.engappai.2026.114749
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• Pseudo-labeling driven refinement of benchmark object detection datasets via analysis of learning patterns
  Neurocomputing 2026 DOI: 10.1016/j.neucom.2026.133046
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• Quality over quantity: a data-centric survey of annotation errors in object detection datasets
  Artificial Intelligence Review 2026 DOI: 10.1007/s10462-026-11502-z
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• Multi-model structure-agnostic framework for enhanced materials discovery in engineering informatics
  Advanced Engineering Informatics 2026 DOI: 10.1016/j.aei.2026.105038
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• Action understanding in low-light and pitch-dark conditions: A comprehensive survey
  Engineering Applications of Artificial Intelligence 2025 DOI: 10.1016/j.engappai.2025.111996
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• Hierarchical attention-based framework for enhanced prediction and optimization of organic and inorganic material synthesis
  Advanced Engineering Informatics 2025 DOI: 10.1016/j.aei.2025.103462
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• Big Data Analysis for Industrial Activity Recognition Using Attention-Inspired Sequential Temporal Convolution Network
  IEEE Transactions on Big Data 2025 DOI: 10.1109/TBDATA.2024.3489414
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• Human centric attention with deep multiscale feature fusion framework for activity recognition in Internet of Medical Things
  Information Fusion 2024 DOI: 10.1016/J.INFFUS.2023.102211
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• Shots segmentation-based optimized dual-stream framework for robust human activity recognition in surveillance video
  Alexandria Engineering Journal 2024 DOI: 10.1016/j.aej.2023.11.017
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• Industrial defective chips detection using deep convolutional neural network with inverse feature matching mechanism
  Journal of Computational Design and Engineering 2024 DOI: 10.1093/jcde/qwae019
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