Christoph Schommer, Professor within the Department of Computer Science at the University of Luxembourg, is principal investigator of the COVID-19 research project “DEEPHOUSE: Deep Mining With The Covid-19 Data Warehouse”.
Funded by the Luxembourg National Research Fund (FNR), the project DEEPHOUSE led by Prof. Christoph Schommer will analyse data and develop a web-based platform.
1) Could you tell us more about your background and expertise?
I studied Artificial Intelligence at the University of Saarbrücken and at the German Research Center for Artificial Intelligence in Saarbrücken before I joined IBM for 8 years. During my time at IBM Research and Development, I was involved in worldwide Business Intelligence projects (Data Warehousing, Data Mining); in parallel to my professional career, I received my PhD in Medical Informatics from the Goethe University Frankfurt/Main in December 2000.
In October 2003, I was appointed Associate Professor at the University of Luxembourg. Today, I am Head of the research group MINE (Knowledge Discovery and Mining) and the ACC lab (Artificial Intelligence and Cognitive System Concepts). My interests lie at the borderline between Machine Learning and Data Science and especially in interdisciplinary projects. I am an internationally recognised scientific reviewer, who acts for the Leibniz Association, Springer and IEEE as well as programme committee member for more than 100 international conferences (e.g., IJCAI, AAMAS, CogSci, ECML, and others). I regularly organise lecture series and PhD workshops and am the author of about 100 scientific papers. I have supervised or co-supervised 21 dissertation projects, mainly at the University of Luxembourg, but also at the University Turin and at UC London. Currently, I am advising 12 PhD students on their research projects in fields such as Computer Science, Finance, Humanities and others.
When it comes to teaching and training, I have taught 133 courses in Luxembourg, but also for the European Union. I have been visiting professor at the universities in Beijing (Tsinghua), Frankfurt/Main, Singapore, Potsdam and the FU Berlin (at the FU, I regularly teach there since Summer Term 2018). I maintain contacts with the industry, the National Ethics Council, and act as an expert for newspaper and radio interviews as well as for television.
2) How is your expertise relevant in the current COVID context?
It is extremely relevant. In a time where COVID-19 is attracting worldwide attention, the data quantity and variety is increasing dramatically. The result are mainly data lakes, where (structured and unstructured) data appears in different formats and quality. Just to say: the Johns Hopkins University Center for Systems Science and Engineering (JSU-CCSE) has compiled a number of various data sources including data from the World Health Organization and others, where the published data itself is largely time-series data that covers worldwide mortality rates, infected and recovered cases of the Covid-19 disease for more than 200 countries.
The Open Research Dataset Challenge (CORD-19) is a resource of almost 60000 scholarly articles, where more than 75% of these are full text articles. These are only two examples of publicly available data that aims to provide a comprehensible analysis of the entire disease development. The decisive problem here, however, is that the heterogeneity, diversity, and (partially) unstructuredness of data makes a deep analysis more difficult rather than easier. In this view, our project DEEPHOUSE has two central goals: first, we want to consolidate available data in a Covid-19 data warehouse by applying appropriate data integration techniques. Second, we want to build a web-based platform being extendable, which should demonstrate a discovery of relevant information.
3) What is your specific role in ongoing COVID projects?
I am the Principal Investigator of the project DEEPHOUSE and will be, together with Dr. Joshgun Sirajzade, responsible for the conceptualization and implementation of the project. As DEEPHOUSE is limited to 6 months, we will use our experiences that we achieved from other data science projects. DEEPHOUSE will become connected to Prof. Reinhard Schneider’s (LCSB) project CovLit, in which a novel collaborative curation interface will be realised.
4) Could you tell us more about your collaborators?
Prof. Reinhard Schneider is heading the Bioinformatics Core facility. Furthermore, he is Deputy Director at the Luxembourg Centre for Systems Biomedicine (LCSB) and, since 2017, the ELIXIR node in Luxembourg. Between 2004 and 2010, he was Team Leader at the European Molecular Biology Laboratory (EMBL) in Heidelberg, where he led the “Data Integration and Knowledge Management” group. Before he was co-founder and CIO in LION bioscience AG and CEO of LION bioscience Research Inc., Cambridge, Massachusetts, establishing an IT based knowledge management system for Bayer. Until 1997, he was a PostDoc researcher in the Bio-computing department at the EMBL, where he studied various aspects of protein structures and became an expert in HPC. He received his Ph.D. in biology at the University of Heidelberg and has over 180 research papers published with over 13thousand citations. He is a member of the board of Directors of the International Society for Computational Biology where he served 7 years as treasurer. He is also involved in several start-ups in Luxembourg and Germany.
Dr. Joshgun Sirajzade received his Doctorate in digital humanities from the University of Trier in 2013. He then held several postdoctoral positions in Trier before finally coming to the University of Luxembourg as a postdoctoral research fellow in 2018. Here he is working in the STRIPS project, which deals with a semantic search toolbox for the retrieve of similar patterns in Luxembourgish documents.