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Applied Machine Learning

The Applied Machine Learning group aims to develop and apply novel Machine Learning methods for real-world applications. Emerging digitalization allows companies from different fields of industry to produce and collect data from various resources. This is realized by technologies like the Internet of Things (IoT), cyber-physical systems and cloud-computing. All of which is summarized by the fourth industrial revolution, called Industry 4.0, with an increasing demand on research in the area of data analytics. Since these ever-growing amounts of data are difficult to process by conventional methods, machine learning and artificial intelligence provide a powerful and promising approach to handle Big Data. Thus, topics like predictive maintenance, process optimization and process automation benefit from new intelligent algorithms that are developed in the Industry 4.0 environment.

Research areas: Machine Learning, Signal Processing, Wearables, Experimental Studies

 

Group Head

An Nguyen, M. Sc.

Room: Room 01.015

 

Group Members

 

Current Students

  • Srijeet Chatterjee
    Data-Driven Customer Experience Management (Master's Thesis)
  • Christopher Kraus
    Statistical Modeling for Cooperative Positioning with RSSi data (Bachelor's Thesis)
  • Kirill Menke
    Exploring the Applicability of Mixed Reality for Paramedic Training (Bachelor's Thesis)
  • Maximilian Rüthlein
    Interactive segmentation in RGB-D indoor scenes using Deep Learning (Master's Thesis)
  • Mengyue Wang
    CAD2Image: Image Synthesis using CAD Models to Augment Training Data (Master's Thesis)

If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.

 

Completed Project

 

Projects