Yanuar Rizki Pahlevi defended his Master thesis on 9 June 2022. Congrats!

Yanuar Rizki Pahlevi defended his Master thesis in MPCAS at the Chalmers University of Technology on 9 June 2022 at 17:00. Congrats!

Title: Deep Learning for Optical Tweezers. DeepCalib Implementation for Brownian Motion with Delayed Feedback

Brownian motion with delayed feedback theoretically studied to take control of Brownian particle movement’s direction. One can use optical tweezers to implement delayed feedback. Calibrating optical tweezers with delay implemented is not an easy job. In this study, Deep learning technique using Long Short Term Memory (LSTM) layer as main composition of the model to calibrate the trap stiffness and to measure the delayed feedback employed, using the trapped particle trajectory as an input. We demonstrate that this approach is outperforming variance methods in order to calibrate stiffness, also outperforming approximation method to measure the delay in harmonic trap case.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Examiner: Giovanni Volpe
Supervisor: Aykut Argun
Opponent: Ivan Gentile Japiassu

Place: Nexus
Time: 9 June, 2022, 17:00

Yanuar Rizki Pahlevi joins the Soft Matter Lab

(Photo by A. Argun.)
Yanuar Rizki Pahlevi joined the Soft Matter Lab on 18 January 2022.

Yanuar is a master student in Complex Adaptive Systems at Chalmers University of Technology.

During his time at the Soft Matter Lab, he will focus on implementing deep learning techniques to predict delay in Brownian motion with delayed feedback.