Bernhard Haslhofer Research Profile
My general research interest lies in finding and applying quantitative methods for gaining new insights from large-scale, connected datasets. Currently, I am working on:
Industrial Data Science: I coordinate the COGNITUS research project, which aims at predicting outages in jewelry production and warehousing logistics.
Digital Humanities: in the TRAVELOGUES project, I am collaborating with historians to gain insight into the perception of the Other (Fremdheit) by analyzing travelogues in digitized corpus of the Austrian National Library.
Our working paper on Cross Layer Deanonymization Methods in the Lightning Protocol is now online.
We released v.0.4.4 of our GraphSense Cryptocurrency Analytics platform, supports tag coherence scores as an indicator for clustering quality.
Our work on Identifying Historical Travelogues in Large Text Corpora Using Machine Learning received the Lee Dirks Award for Best Full Research Paper at the iConference 2020.