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In 2021, Lisa Kellner completed her master's degree at TU Wien. At VRVis, however, the computer scientist has already stood with both feet firmly in applied research for many years now.

Lisa Kellner is a researcher in our Geospatial Visualization, Semantic Modelling and Acquisition Group, where she collaborates with corporate partners to develop solutions for handling and visualizing real-world data.

However, non-researchers who ask Lisa Kellner about her work often find this information rather hard to grasp. That's why she describes her work by talking about her daily routine: about the manifold discussions with her team, about reaching project milestones, and how adventurous solving IT problems as a team can be. To make her work more visible, Lisa Kellner invited us to have a look over her shoulder during a day in her everyday life as a "young researcher."

For example, in the morning, she heads to the office like everyone else - or, because of the CoV pandemic, she goes online at home. The first item on her to-do list: checking messages. What e-mails and information have arrived from colleagues or project partners? What questions and tasks are there that need to be dealt with right away? The next step is to look at the calendar and update her to-do lists accordingly. Since Lisa Kellner is involved in not just one but several research projects simultaneously, it is essential to keep on top of everything.

While she almost always has to deal with code on the screen, the application fields of her research work are diverse: from automatic detection of noise barriers in point clouds to solutions for additive manufacturing for railroad replacement parts to real-time construction site documentation with robot dogs. In her master thesis Classification of Urban Point Clouds Using 3D CNN, she explained in great detail how this research work can look in concrete terms, illustrated by developing solutions for automated sidewalk classification.

For Lisa Kellner, close contact with all her research group colleagues is indispensable: As a team, everyone is engaged in brainstorming, experimenting, coming up with new ideas, and, above all, solving problems. A key meeting is always the weekly scientific discussion, where the latest research developments are discussed. Each team member presents their project progress to everyone, often finding improvements together "almost by accident."

Lisa Kellner researches at the intersection of (geo)data visualization, point cloud research, and artificial intelligence. In order to stay up-to-date here, keeping up with scientific publications and the latest developments in these fields is, of course, part of the job. Yet, Lisa Kellner spends a great deal of her time directly programming. Fortunately, she is not only "fluent in code" but has a real passion for what she does. After all, getting the correct details and information out of huge point clouds, which often encompass entire urban spaces or even cities, requires both technical knowledge and the drive to keep thinking creatively outside the box. The main goal of their work is to use large amounts of data for automatic segmentation and reconstruction, for example, for train platform edges or noise protection walls. A major focus here is always on combining different data sources. These data sources are sometimes as diverse as the application fields they come from. But even when things get complicated, the computer scientist stays focused. For Lisa Kellner, a significant motivation is that her research work actively contributes to important technological advances in practice - whether for green rail traffic of the future or sustainable construction site documentation for customized BIM and building management.