Atiqur Rahman

Employment

• Missouri University of Science and Technology Graduate Research Assistant
  2023 - Present
• Barisal Electric Power Company Limited Commercial Manager & Sr. Executive Engineer (Mechanical)
  2022 - 2026

Education

• Missouri University of Science and Technology Doctor of Philosophy (Ph.D.)
  2024 - Present
• University of Science and Technology Beijing Bachelor of Engineering
  2018 - 2022

Projects & Funding

Projects & funding information is unavailable.

Publications (11)

• Preliminary design and rapid prototyping method for a hybrid VTOL tilt tri-rotor UAV
  Aerospace Science and Technology 2026 DOI: 10.1016/j.ast.2026.113075
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• A Transfer-Learning and Continuous Optimization-Based Framework for Predicting Heat Treatment-Dependent Mechanical Properties of DED-Processed Low-Alloy Steels
  Metals 2026 DOI: 10.3390/met16080892
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• Hyperdimensional computing and ridge regression for airfoil aerodynamic prediction : A physics-informed machine learning framework
  Aerospace Science and Technology 2026 DOI: 10.1016/j.ast.2025.111591
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• Evaluating Classical Machine Learning Classifiers for Real-Time Intrusion Detection on Smart Network Interface Cards
  2026 28th International Conference on Advanced Communications Technology (ICACT) 2026 DOI: 10.23919/icact68090.2026.11431504
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• Machine Learning-Based Job Recommendation Systems, Techniques and Approaches Based on Bangladesh
  2026 28th International Conference on Advanced Communications Technology (ICACT) 2026 DOI: 10.23919/icact68090.2026.11431296
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• A MACHINE LEARNING MODEL TO PREDICT MECHANICAL PROPERTY OF DIRECTED ENERGY DEPOSTION PROCESSED LOW ALLOY STEELS
  Solid Freeform Fabrication 2025: Proceedings of the 36th Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference 2025 DOI: https://doi.org/10.26153/tsw/63514
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• Industry 5.0, human–machine interface, and smart manufacturing in additive manufacturing—a recent trend
  The International Journal of Advanced Manufacturing Technology 2025 DOI: 10.1007/s00170-025-16782-3
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• Physics-Based Machine Learning Framework for Predicting Structure-Property Relationships in DED-Fabricated Low-Alloy Steels
  Metals 2025 DOI: 10.3390/met15090965
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• Physics-Based Machine Learning Framework for Predicting Structure-Property Relationships in DED-Fabricated Low Alloy Steels
  2025 DOI: 10.20944/preprints202507.1536.v1
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• A Comprehensive Study of Cooling Rate Effects on Diffusion, Microstructural Evolution, and Characterization of Aluminum Alloys
  Machines 2025 DOI: 10.3390/machines13020160
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