Research interests:

• Thermoacoustic instabilities in combustion
• Machine/ Deep Learning
•  Data assimilation

Corporations/affiliations (e.g. previous projects, partnerships with industry):

• SCOUT: signal correction and uncertainty quantification toolbox in MATLAB (Technische Universität Braunschweig)

Publication:

• Semaan, R. and Yadav, V., 2020. SCOUT: Signal Correction and Uncertainty Quantification Toolbox in MATLAB. SoftwareX, 11, p.100474.

Teaching Experience:

• Block course on ’Machine Learning for dynamical systems’, Every semester
•  X-student Research Project organized by Berlin University Alliance, Summer semester 2021
•  Thermoacoustic Projects, Winter semester 2021-22

What (e.g. experiences) shaped you as a researcher?
My ever-growing interest in solving puzzles and problems.
What motivated you to do research in this field or specific project?
My knowledge of mechanical engineering was gained throughout my studies. Moreover, during my master’s program, I dived deep into numerical methods and advanced mathematics. I also got the opportunity to work on the latest data-driven techniques in my student project and master thesis, which eventually veered me into this field.
What do you think is important in your field or research in general?
A deep understanding of traditional and modern developments in thermoacoustic and combustion domain is really important in my field of research. There are already many data-driven techniques present in the scientific community. But it becomes important to customize those developed approaches to the problem at hand for extracting maximum benefit.
What helps you in your research?
Regular interaction with my supervisors and colleagues has proven to be really useful. At the same time, constant support and appreciation from supervisors motivate me to continue giving my best in my research.
What shapes you besides research? Do you have hobbies or volunteer work, which you want to share?
I like doing physical activities, like trekking, cycling, playing football, etc.