Research Database: Projects

MARIA LUISA ESPINEL RAMOS's doctoral thesis focuses on the transmission of infectious diseases from animals to humans. This is facilitated by natural evolutionary processes of pathogens, which adapt to environmental conditions altered by humans, such as land use, intensive animal husbandry, climate change and biodiversity loss. In urban areas in particular, high densities of humans and animals interact frequently, increasing the risk of spillover events. The nature and frequency of these contacts, as well as human behaviour, which is influenced by social and economic factors, have a significant impact on exposure. As these complex relationships are not yet fully understood, the prediction and prevention of emerging zoonoses requires an integrative "One Health" approach that considers environmental, animal and health aspects together.

Autonomous systems and robots operate in dynamic environments that change gradually or radically over time. To perform tasks in such ever-changing environments, the robot should continuously learn and adapt its capabilities. Continual learning (CL) is a machine learning method that learns from continuous streams of data. CL aims to balance the trade-off between the capabilities to be maintained and those to be enhanced, a characteristic that current machine learning struggles with. The PhD thesis of MOHAMMAD WASIL focuses on using the physical interaction of a robot, such as exploiting spatio-temporal information about the environment, to obtain more robust data for addressing the continual learning problem.

Dynamic pricing models have long been commonplace in some industries, particularly in travel and flight bookings. Prices for identical products are adjusted dynamically and now in real time due to changing market conditions over time. Doctoral student LENA RECKI's research focuses on the effects of this pricing policy on consumer behaviour. With her findings, she aims to show the extent to which customers perceive and accept dynamic prices and the potential this model offers in industries such as food retail.

Due to the ongoing advance of digitalisation, it can generally be observed that all kinds of products are increasingly developing into services with fixed-term contracts (subscriptions). In this context, the term "Everything-as-a-Service" (XaaS) is often used. As a result, consumers are entering into more and more (fixed-term) contracts, which they need to keep track of (e.g. comparing, monitoring terms, etc.) and interact with providers (e.g. cancelling). To support this, there are already many apps, service providers and emerging start-ups. PhD student ERIK DETHIER is investigating how information technology can support consumers in managing their contracts, finances and thus their providers. Together with his colleagues from the Consumer Informatics Research Group, he is conducting research on consumers and their acceptance and integration of such IT into their everyday practices, as well as on the developers of such IT/apps.

Thanks to their highly sensitive sense of smell, sniffer dogs have the special ability to detect drugs, explosives, people or animals by their scent. But how sensitive are dogs and how reliable are their detections? To get to the bottom of this, doctoral student JENNIFER BRAUN is investigating methods for the quality-assured quantification of VOCs, primarily using instrumental analysis but also involving detection dogs.

N-nitrosamines are partly volatile compounds that can be produced in many different industrial processes and are classified as carcinogenic. Due to their high health risk, there is an urgent need to develop reliable, sensitive and mobile systems for the detection and quantification of N-nitrosamines. As part of her doctoral studies, PhD student JANA HINZ is working on the development of a GC-FAIMS system, a measuring device for the rapid analysis of N-nitrosamines. This system is intended for use in various branches of industry. Compared to conventional methods, GC-FAIMS offers the advantage of being fast, portable and cost-effective.

The operation of an e-bike generates vibrations and noise, e.g. due to the functioning of the drive unit or the interaction between the rider and the bike. Dynamic effects cause excitation along individual structures up to the system level. Sound is also emitted into the environment from free surfaces. As the development of e-bikes is currently being strongly promoted and noise/vibration issues need to be better understood, a computer-aided model of the drive unit is being developed as part of KEVIN STEINBACH's doctoral thesis. The simulation model will then be used to map and predict the NVH behaviour (noise, vibration, harshness) of the drive unit. This would enable optimisation measures to be carried out on virtual prototypes and – in the interests of resource-efficient development – reduce time-consuming test samples.

Raw meat quickly shows bacterial contamination. If the contaminated meat is consumed, it can be hazardous to health above a certain amount. That is why doctoral student DANIEL KLEIN has made contamination (e.g. bacteria) visible on complex surfaces (e.g. meat). To do this, he combined spectroscopic data from IR and Raman spectroscopy from the same measurement regions to show where contamination can be found. Combining the two methods increases the information content of the data set and at the same time reduces the error rate in contamination detection.

The aim of USHA SINGH's PhD project is to improve the match between applicants and vacancies in order to minimise poor decisions in personnel selection. To this end, influencing factors that distort objective perception and can provide clues for more efficient candidate selection are being investigated. A central component of this project is the analysis of break management, particularly with regard to the effectiveness of various interventions.

Doctoral candidate Cathleen Müller conducts expert interviews with operators of coworking spaces. She evaluates these interviews using grounded theory methodology. The aim is to identify factors that influence the material and immaterial success of rural coworking spaces in Germany. The end result will be a model that represents these factors and how they work. This model is primarily intended to support practitioners and expand research on success factors to include the field of application "rural coworking spaces".