Justin Albert

My research focuses on markerless motion capture for analyzing human movement patterns. In collaboration with interdisciplinary partners, such as clinicians and sports scientists, we investigated the accuracy of markerless motion capture systems using a gold-standard marker-based system. Another project investigated fatigue analysis during resistance training using machine learning on multimodal time series data.

Worked on the implementation of a modular and scalable IoT (Internet of Things) edge application to collect and analyze usage data from medical laboratory instruments. Tools used included C# .NET and WPF.

Involvement in teaching activities for two bachelor's degree program courses in Computer Science in New Media. Subjects taught include: - Programming with C and Python: Led practice groups of approx. 20 students to further teach and elaborate on the lecture content. - Generative Computer Graphics: Led the weekly tutorial to explain the lecture content to the students and to support them in completing the weekly assignments.

Maintained and extended a control application for an advanced liquid handling platform to support the development team consisting of mechanical engineers and biochemists. A highlight was the development of an optical error detection system to control and monitor the liquid handling process on the device.

Developed an application to support the engineering team in the development of a novel platform for liquid handling and sample preparation based on electrowetting on film. The functions implemented included dynamic pathfinding algorithms, pattern recognition methods, and device control functions. The software was developed using C# .NET and WPF.

Supported the software development team by implementing unit tests for the airport security systems infrastructure. Tools used included Jython, Java, and Marathon.

Master’s Thesis Title: Unsupervised Segmentation of Intra-Oral Images

Bachelor’s Thesis Title: A parameterization and calibration tool for laboratory robots