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The 2nd INTERNATIONAL CONFERENCE ON COMPUTATIONAL ENGINEERING AND INTELLIGENT SYSTEMS - ICCEIS 2022
Multidisciplinary Engineering is a currently proliferating area in which focus is put on an engineering practice by combining several academic disciplines. Computational Engineering is a modern and multidisciplinary science for computer based modeling, simulation, analysis, and optimisation of complex engineering applications and natural phenomena. Sitting at the intersection of computer science and applied math, Computational Engineering deals with mathematical techniques for modeling and simulation of complex systems; parallel programming and collaborative software development; and methods for organizing, exploring, visualizing, processing, and analyzing very large data sets. Computational Engineering englobes fundamental engineering and science, and advanced knowledge of mathematics, algorithms and computer languages. On the other hand, Intelligent systems engineering offers the next generation of solutions, powered by computing and artificial intelligence. Intelligent systems are technologically advanced machines that are designed to respond to some specific requirements. In Intelligent Systems Engineering, the scope is about creating systems that sense and react to their environments.
The aim of this conference is to bring together scientists, research individuals and industrials to share knowledge abnd findings about the topics withion the scope of the conference. The purpose is to provide a platform for possible collaboration and exchange of ideas to advance more in this field.
Topics of interest may include, but not limited to, the following:
- Biomedical engineering and applications
- Climate modeling
- Energy systems
- Modeling and simulation
- Multiphysical models and co-simulation
- Cybersecurity
- Data Science and Engineering
- High Performance Computing
- Optimization
- Multi-agent systems
- Evolutionary computation
- Artificial intelligence
- Complex systems
- Computation intelligence and soft computing
- Intelligent control
- Advanced control technology
- Robotics and applications
- Intelligent information processing
- Iterative learning control
- Machine learning
- Smart grids and systems
