Research Groups

 

 Decision Systems    

  • The team focuses on contributions to Algorithmic Decision Theory.
  • Contact: Prof. Dr. Raymond Bisdorff

Parallel Computing and Optimisation 

  • We conduct research on parallel and evolutionary computing, in particular how different species may co-evolve featuring different individuals taking local decisions while ensuring global objectives (e.g., search and optimization). This target is approached through various facets like loosely coupled genetic algorithms, distributed immune systems, and iterated multi-player prisoner dilemma.
  • The main application domains of the team fit the University of Luxembourg priorities: - security, trust and reliability, for example: cryptology, intrusion detection, and reliable scheduling and routing on new generations of networks such as p2p, ad-hoc, and hybrids. - sustainable development, for instance, Energy Efficient Data Centers - systems biomedecine, for example, genomic sequencing, proteine folding, genomic modeling.
  • Contact: Prof. Dr. Pascal Bouvry

Data Mining and Knowledge Discovery

  • We are interested in data exploration and in elaborate on intelligent and adaptive algorithmic concepts to discovery information about the data.
  • Current research is related to the fields of Data Science, Machine Learning and Deep Learning, Natural Language Processing and Text Mining, Emotion Detection ind Texts, Topic Identification.
  • Contact: Prof. Dr. Christoph Schommer

Information Theory and Stochastic Inference

  • Basic areas of competence of the team of Ulrich Sorger are probability, information, and coding theory. The main directions are decoding of error control codes and stochastic interference, where the decoding of error correcting codes can be considered as stochastic inference problem respectively the inversion of a stochastic map. Recent results show that encoding / decoding techniques exist that perform well close to theoretical limits.
     The team investigates these techniques and their applicability to other stochastic inference problems.
  • Network Traffic Modeling concerns the development of stochastic network traffic models which can help to improve performance of data transfers and network security. The aim is to use these network traffic models to derive useful conclusions from the monitored traffic concerning local congestions, localization of spam sources or denial of service (flood) attacks. Particular attention is focused on elaboration of a new approach to the detection of local network congestions based on spectral analysis of multivariate stationary processes.
  • Contact: Prof. Dr. Ulrich Sorger

 Big Data and Information Extraction

Individual and Collective Reasoning  

  • The Individual and Collective Reasoning Group (ICR) is an interdisciplinary research team at the University of Luxembourg which is driven by the insight that intelligent systems (like humans) are characterized not only by their individual reasoning capacity, but also by their social interaction potential. Its overarching goal is to develop and investigate comprehensive formal models and computational realizations of individual and collective reasoning and rationality.
  • ICR is involved in the Interdisciplinary Centre for Security, Reliability and Trust (SnT). The group currently counts more than 15 researchers and is strongly engaged in international cooperation. Our research areas are normative multi-agent systems, autonomous cognitive agents, computational social choice, and the foundations of logic-based knowledge representation and reasoning.

Contact: Prof. Dr. Leon van der Torre

You can find the latest ILIAS publications orbilu.uni.lu or directly at the home pages of the ILIAS research groups.