Professor Sandra Lorenz is an alumna of the TU Bergakademie Freiberg: she completed her Bachelor’s and Master’s degrees, as well as her PhD, here in the Geosciences. She is now returning to her alma mater, TU Bergakademie Freiberg, as Professor of Image Analysis and Remote Sensing, in a joint appointment with the Helmholtz Centre Dresden-Rossendorf.
“The subject of imaging in remote sensing has been a constant theme throughout my academic career,” says the new professor at the Faculty of Mathematics and Computer Science. “In fact, it was through the ‘Geo-remote sensing’ course that I developed my scientific fascination with contactless mapping of the Earth, also known as remote sensing.”
Since 2015, Lorenz has been conducting research at the Helmholtz Institute Freiberg for Resource Technology at the HZDR, where she has been leading her own research group since obtaining her Degree in 2019. With this appointment, she also takes on the joint leadership of the Exploration Department there, alongside Professor Richard Gloaguen. “The use of autonomous systems (drones, robots) and data integration across scales, spatial dimensions and spectral ranges are at the heart of this research.” The new professor has set several key priorities for her research at the TU Bergakademie Freiberg. The focus is on combining Robotics and spectral imaging:
“I want to develop systems that autonomously capture and analyse image data, such as robots that map rock formations underground or characterise raw material flows in recycling,” says Lorenz. To this end, she is expanding the existing collaboration with the Professorship for Software Technology and Robotics. Other key areas of focus include linking spectral image data with other data types such as radar or 3D point clouds, as well as remote sensing across various scales, from satellites to the laboratory. “Whether for the energy transition or the circular economy: we need methods that allow raw materials to be explored efficiently and with as little impact on nature as possible.”
Teaching with a practial approach
In her teaching, Lorenz emphasises a practical approach. In her seminar module ‘Image Processing and Computer Vision’, which she will be offering from the 2026/27 winter semester onwards, students learn how image data is generated and how it is calibrated and processed. “They’ll be working with the HIF’s hyperspectral, thermal and industrial cameras,” reveals the new professor. Together, students discuss the latest developments in computer vision and, working in small groups, carry out their own projects addressing current scientific questions. “The best way to understand image processing is to work with it yourself,” says Lorenz. “But it’s also important to me that students critically examine how image data is generated, particularly when decisions or machine learning are based on it.”
