Lyndon Nixon

Dr Nixon is an Assistant Professor in the Department of Applied Data Science. His research interests cover the visual classification of photography to automatically extract the touristic destination image from social networks such as Instagram; the use of deep learning for predictive analytics in open domains such as predicting the next trending topic in online channels; the extraction and modelling of knowledge, e.g. about events, in graph structures and their combination with neural networks to improve computational understanding of the world.

He also leads research projects at the Research Centre for New Media Technology in his role as CTO of MODUL Technology GmbH, the research spin-off of MODUL University. He was project coordinator of the EU Horizon 2020 project ReTV (www.retv-project.eu), which developed tools to help media organisations to optimally select and repurpose their media assets for digital marketing. He led research in predicting future trending topics among online audiences and recommending relevant future events to target in online marketing. He also coordinates the FFG project EPOCH (extracting and predicting events from online communication; www.epoch-project.eu) and participates in the BMVIT project EcoMove (prediction of urban mobility bottlenecks; www.ecomove.at) and the FFG project GENTIO (prediction of future communication success of online publications; www.gentio.eu). Previously he has been active in the EU projects InVID (finding and verifying fake news video on social networks; www.invid-project.eu) and LinkedTV (identifying topics of TV programming and linking them to related Web content on a second screen; www.linkedtv.eu). He also teaches (BBA/BSc, MSc/MBA), supervises theses and works on acquiring new research projects. Dr Nixon welcomes thesis and research project proposals around any of the above topics!