57th VIETNAM World Conference on Artificial Intelligence, Energy & Manufacturing Engineering (AIEME-27) Jan. 18-20, 2027 Ho Chi Minh City (Vietnam)

AIEME-27


Materials Engineering Artificial Intelligence Engineering & Computer Science (General) Manufacturing & Machinery Materials Engineering Aviation & Aerospace Engineering Power Engineering Ceramic Engineering High Energy & Nuclear Physics



Call for papers/Topics



All Abstracts, Reviews, short articles, Full articles, Posters are welcomed related with any of the following research fields:



Artificial Intelligence (AI)



Core AI Foundations





  • Machine Learning (ML): Supervised learning, unsupervised learning, reinforcement learning, and ensemble methods.




  • Deep Learning: Artificial neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers.




  • Natural Language Processing (NLP): Large language models (LLMs), semantic analysis, sentiment tracking, and machine translation.




  • Computer Vision: Image recognition, object detection, semantic segmentation, and edge detection.




  • Probabilistic Reasoning and Knowledge Representation: Bayesian networks, knowledge graphs, and expert systems.





Advanced & Emerging AI





  • Generative AI: Diffusion models, Generative Adversarial Networks (GANs), and synthetic data generation.




  • Edge AI: Localized processing, model quantization, and neuromorphic computing.




  • Explainable AI (XAI): Model interpretability, transparency frameworks, and bias mitigation.





Energy Engineering



Renewable Energy Systems





  • Solar Energy: Photovoltaic (PV) cell efficiency, solar thermal systems, and inverter technology.




  • Wind Energy: Onshore and offshore turbine aerodynamics, rotor dynamics, and drivetrain mechanics.




  • Hydroelectric and Marine Energy: Tidal, wave, and run-of-river generation systems.





Conventional & Nuclear Energy





  • Thermal Power Plants: Gas turbines, combined-cycle power plants, and carbon capture and storage (CCS).




  • Nuclear Engineering: Fission reactors, small modular reactors (SMRs), and fusion energy research.





Grid Infrastructure & Storage





  • Grid Management: High-voltage direct current (HVDC) transmission, substations, and grid stability.




  • Energy Storage Systems: Lithium-ion batteries, solid-state batteries, pumped hydro, and thermal storage.




  • Hydrogen and Alternative Fuels: Electrolysis, hydrogen storage, fuel cells, and biofuels.





Manufacturing Engineering



Traditional & Advanced Manufacturing Processes





  • Subtractive Manufacturing: CNC machining, milling, turning, and electrical discharge machining (EDM).




  • Additive Manufacturing (3D Printing): Powder bed fusion, stereolithography, fused deposition modeling, and direct energy deposition.




  • Forming and Casting: Injection molding, die casting, forging, and sheet metal forming.





Factory Automation & Systems





  • Robotics and Kinematics: Industrial robotic arms, kinematics, end-effectors, and programmable logic controllers (PLCs).




  • Computer-Integrated Manufacturing (CIM): CAD/CAM integration, product lifecycle management (PLM), and automated guided vehicles (AGVs).




  • Metrology and Quality Control: Coordinate measuring machines (CMM), non-destructive testing (NDT), and Six Sigma methodologies.





Interrelated Topics (The Intersections)



AI + Energy (Smart Energy Systems)





  • Smart Grid Optimization: Demand forecasting, dynamic pricing algorithms, and automated load balancing using ML.




  • Predictive Maintenance for Energy Assets: Failure prediction for wind turbine gearboxes, solar inverters, and nuclear plant valves using vibration and thermal data.




  • Renewable Energy Forecasting: Using deep learning and meteorological data to predict solar irradiance and wind patterns.




  • Virtual Power Plants (VPPs): AI-driven aggregation and dispatch of distributed energy resources (DERs).





AI + Manufacturing (Smart Manufacturing / Industry 4.0)





  • Predictive Maintenance in Factories: Anomaly detection in CNC spindles, conveyor belts, and robotic joints using IoT sensor streams.




  • Defect Detection & Quality Assurance: Computer vision systems scanning assembly lines in real-time to catch surface micro-cracks or assembly errors.




  • Generative Design: AI algorithms exploring thousands of design permutations based on material and weight constraints for 3D printing.




  • Robotic Autonomy and Cobots: Reinforcement learning enabling collaborative robots (cobots) to adapt to human movements and varying part orientations.





Energy + Manufacturing (Sustainable Manufacturing)





  • Energy-Efficient Manufacturing Processes: Optimizing the power consumption of energy-intensive processes like metal smelting or injection molding.




  • Life Cycle Assessment (LCA): Evaluating the total environmental and energy footprint of manufactured goods from raw material to disposal.




  • Manufacturing for the Energy Sector: The specialized production of massive wind turbine blades, battery cells, and silicon PV wafers.




  • Circular Economy Engineering: Remanufacturing, recycling processes for lithium batteries, and scrap material upcycling.





The Triple Intersection: AI + Energy + Manufacturing





  • Industrial Microgrids: Manufacturing facilities utilizing AI to manage their own localized solar, storage, and grid interactions to minimize carbon footprints and energy costs.




  • Digital Twins of Industrial Ecosystems: Creating real-time virtual replicas of entire factories that simulate both production output (manufacturing) and energy draw (energy) optimized continuously by machine learning (AI).




  • Autonomous Supply Chain Carbon Accounting: AI systems tracking the logistics, manufacturing energy, and material sourcing to optimize for the lowest possible embedded carbon footprint in real-time.