FTUI students won First Place in Monash’s Final Year Poster Presentation event. The student is Michael Jehan Pangestu, an International Class double degree program student, Department of Mechanical Engineering FTUI Class of 2018 who is currently completing his education at the Faculty of Engineering, Monash University. Monash’s Final Year Poster Presentation was held as one of a series of project activities for the undergraduate program of the Faculty of Engineering, Monash University.

In this event, all final year student project posters were included in the faculty level competition. Then the posters were assessed by each department head at the Faculty of Engineering, Monash University. The assessment covers aspects of technical content and presentation quality. Out of 105 final year students who took part in Monash’s FYP Poster Presentation, Michael’s poster entitled “Physics Informed Deep Learning in Predicting 2D Unsteady Flows” successfully ranked first.

“My success in conducting this research cannot be separated from the services of the lecturers of the Mechanical Engineering Department, both at the UI Faculty of Engineering and at Monash University, who have educated me in the field of mechanical engineering. In addition, my experience in the Bangkit 2021 program in partnership with UI has facilitated me to learn deep learning. I also learned a lot when I participated in the ShARE-UI program in 2019 and 2020. From this program I learned problem solving and making effective presentations,” said Michael.

In his research, Michael focuses on machine learning in the fields of computational fluid dynamics and experimental fluid dynamics. In his research, Michael revealed that machine learning can speed up and improve the accuracy of fluid simulations even though they use hardware that does not have high computing power. Machine learning can also be used to improve the accuracy of experimental data even if using measuring tools that are not of high quality.

It is hoped that, with further research, this project can improve accessibility in conducting simulations and experiments in the field of fluid mechanics despite hardware limitations.

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Public Communication Bureau
Faculty of Engineering, University of Indonesia

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