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Development of a Synchronization Pipeline for Multi-Modal, Multi-Source Timeseries Data: Collaboration with Tohoku University, Japan. + Potential option for a research stay in Japan.
Modern robots collect data from various sensors. When these sensors operate independently, time-synchronization through rectification of their individual clocks and correction for temporal drift is required.
In our previous work, we developed an initial version of a synchronization pipeline in Python, designed for offline data synchronization. Our current pipeline already effectively synchronizes sensors that include a common external synchronization signal. Despite already working well, our current pipeline still requires some expertise to configure the data sources. To make the pipeline widely usable, we now need to make it function seamlessly even without expert knowledge and access to external synchronization signals. This enhancement should also extend to scenarios involving continuous online data as well.
Furthermore, we want to prove the correctness of the synchronization and showcase the performance based on synthetic data.
In essence, your thesis will comprise the following key objectives:
1. Understand the challenges involved in data synchronization.
2. Familiarize yourself with the existing synchronization pipeline.
3. Innovate strategies for achieving data synchronization without relying on external synchronization signals.
4. Enhance the user interface by creating an intuitive guide for using the pipeline effectively.
5. Extend the functionality to accommodate online data streams.
6. Assess the pipeline's correctness and performance using synthetic biosignals, as well as pre-recorded biosignals from the SMS-Lab and Tohoku University.
Throughout this project, you will receive guidance from me, a 4th year PhD candidate at the Sensory-Motor Systems Lab at ETH Zurich, and researchers at Tohoku University in Sendai, Japan. As I will be in Japan from October, we will conduct the weekly meetings over Zoom.
Furthermore, in case of interest, you have the exciting opportunity to visit us in Japan. This opportunity can be pursued either through personal funding or by applying for respective scholarships, such as the Heyning-Roelli Foundation, SEMP, Spickenreuther Foundation, and others. I have received scholarships in the past and I am happy to provide guidance and support throughout the application process.
Keywords: Signal processing, data synchronization, computer science, data validation, benchmarking, software engineering, master thesis, research stay, international collaboration
Not specified
You will be continuing our previous efforts in developing an open-source synchronization pipeline, including its validation.
You will be continuing our previous efforts in developing an open-source synchronization pipeline, including its validation.
You will be part of an international research collaboration between the Sensory-Motor Systems Lab and Tohoku University in Sendai, Japan. You will have access to our brand-new infrastructure in the GLC building, and we can provide you with a personal student desk if needed.
If you are interested, you will also have the opportunity to visit Tohoku University in Sendai during your master's thesis (personal or external funding required).
You will be part of an international research collaboration between the Sensory-Motor Systems Lab and Tohoku University in Sendai, Japan. You will have access to our brand-new infrastructure in the GLC building, and we can provide you with a personal student desk if needed. If you are interested, you will also have the opportunity to visit Tohoku University in Sendai during your master's thesis (personal or external funding required).
We are looking for exceptional candidates for this one-of-a-kind opportunity. We expect a high level of commitment, a certain level of independence, and previous experience in signal/data processing, Python, and Git. Experience in ROS and ROS2 is a plus. Ideally, you have a background in computer science or robotics.
We are looking for exceptional candidates for this one-of-a-kind opportunity. We expect a high level of commitment, a certain level of independence, and previous experience in signal/data processing, Python, and Git. Experience in ROS and ROS2 is a plus. Ideally, you have a background in computer science or robotics.
Alexander Breuss, alexander.breuss@hest.ethz.ch (primary)
Please send me your CV, transcript, and a short motivation letter. Please also mention any related work previously done.
Alexander Breuss, alexander.breuss@hest.ethz.ch (primary)
Please send me your CV, transcript, and a short motivation letter. Please also mention any related work previously done.