The availability of accurate and computationally cheap combustion models is merely a prerequisite that enables research and design engineers to improve current technologies and develop the next generation of heat and power appliances. It is often very challenging to improve a design even when detailed measurements and simulations are available. Even when large parameter studies are performed, this will only lead to an optimal design within the investigated parameter space. Automatic design optimization methods are a very powerful tool and adjoint-based optimization is specifically interesting for industrial designs that have high degrees of freedom. A number of manufacturing processes allowing high degrees of freedom or even ‘free shapes’ are 3D printing, casting and molding. Only recently has adjoint optimization been performed for design optimization of combustion appliances to reduce emissions using the open source software suite SU2. Development and use of adjoint method to improve combustion processes, specifically for hydrogen applications, is the focus of my work.