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Personal vid Högskolan
Akademin för informationsteknologi
Research Interests: Artificial Intelligence, Machine Learning and Data Mining, especially for Streaming Big Data, with a focus on Knowledge Representation and Weakly-Supervised Models.
* Predictive maintenance, Prognostics, Diagnostics, Data-driven fault detection methods;
* Information-driven Healthcare, Machine Learning for Health;
* Smart Industry, Smart Cities, Smart Energy, Smart Transport, and more.
In my research, I focus on the discovery of interesting patterns and relations, where the "interestingness" can be treated as a metric and quantitatively measured. In this respect, we are evaluating of both the data and the extracted knowledge. In many applications, it is not feasible to store all the data, and therefore a preliminary decision needs to be made as to what are the most useful subsets to use in further analysis. We aim for interestingness metrics that are suitable for evaluating partial results in distributed environments. An important feature, however, is that they should be adaptable to different tasks and domains, as well as work for both supervised and unsupervised learning.
Specifically on the topic of self-organisation and self-awareness, beyond solutions that work well for specific application domains, we aim to obtain a deeper understanding of fundamental concepts, allowing us to build a general theory on top of those successful application examples. This often involves guiding the learning process using (both structured and semi-structured) expert and historic knowledge. In particular, this can be done before the learning starts, but also later, as a way to evaluate results and have the user guide the process in an interactive way. I am working towards designing knowledge representation models that allow for efficient learning, while being flexible enough to capture different aspects of the data simultaneously.
Special Assignments: I am Research Leader for School of Information Technology.
Supervision: I currently supervise six PhD students, and co-supervise another one (both academic and industrial). I have supervised four students until their PhD dissertation, and another four until their Lic degrees.
Current Teaching: I am course responsible and examiner for the Master of Science thesis for Master and Civilingenjör programmes. I am also teaching is several other courses, such as Applied Data Mining, Big Data Parallel Programming, Data Mining, Introduction to Programming, and