AI and machine learning for optimization and operations research
Under this research theme, we develop both mathematical theory and applications for artificial intelligence and machine learning in areas such as optimization and operations research. This includes optimization regarding planning, operation, reliability and maintenance for sustainable energy, production and transport systems. The research theme is closely connected to the Master of Science in Engineering Mathematics Programme.
Artificial intelligence (AI) and machine learning are today the basis for much development in technology and science. This applies to robotics, image recognition, voice control, self-driving cars, automation, operations research, optimal control and e-health, to name a few areas.
A focus area of the research theme AI and machine learning for optimization and operations research is reinforcement learning and its applications in optimization and operations research for sustainable energy, production and transport systems.
The area of operations research is about mathematical modeling for optimization in the manufacturing industry and public sector, transport and production flows, inventory, reliability analysis, optimal control theory and decision theory.
In scientific machine learning, data-driven modeling in the form of machine learning is combined with knowledge of mathematical models in technology and science. An overall purpose is to develop new, or improve existing, methods in computational science.
The research theme is closely connected to the Master of Science in Engineering Mathematics Programme.