Liseth Siemons, MSc.


Liseth Siemons MSc. is a PhD student at the University of Twente at the department of Psychology, Health & Technology. Her PhD project focusses on the measurement of disease activity in patients with early rheumatoid arthritis. Current treatment strategies in patients with early rheumatoid arthritis emphasize an aggressive interference at an early stage of the disease to suppress the patient’s disease activity as quickly, as completely, and as long as possible. A widely used measure for measuring the patient’s disease activity is the Disease Activity Score for 28 joints (DAS28). The DAS28 is an index measure, including a 28-tender joint count, 28-swollen joint count, an acute phase reactant, and a patient reported outcome measure of wellbeing. However, several studies have raised questions about the impact of residual disease activity in joints not included in the DAS28, the equivalent use of two very different acute-phase reactants, and the inclusion of a patient-reported measure of wellbeing. During her PhD project, a number of limitations of the DAS28 will be addressed and several clues for the improvement of disease activity assessments in early RA will be provided.

Eswar Krishnan, MD, MPhil

Dr. Krishnan is an Assistant Professor of Medicine and Director of Clinical Epidemiology at the Division of rheumatology at Stanford University. He has broad research interests ranging from drug safety among patients on arthritis medications, assessing physical frailty and its association with immune parameters, and methodological innovations to measure patient outcomes in these settings. He is currently developing strategies to leverage Big Data available from numerous sources including medical records, vital statistics, administrative data, and patient originating data to inform day-to-day clinical decision-making.

Dr. Johnny Hartz Søraker

Dr. Johnny Hartz Søraker is Assistant Professor of Philosophy of technology at the Department of Philosophy, University of Twente. He defended his PhD cum laude at the same department, dealing mainly with the epistemology, ontology and ethics of virtual worlds, with a particular focus on their potential impact on personal well-being. Søraker's main research interests and publications lie in the intersections between Information Technology, on the one hand and both theoretical and practical philosophy, on the other. He often grounds his work in psychological research, especially work in the field of Positive Psychology and is developing this toward a comprehensive methodology entitled “Prudential-Empirical Ethics of Technology (PEET)”.

Dr. Djoerd Hiemstra

Djoerd Hiemstra is associate professor search engine and database technology at the University of Twente. He wrote an often cited PhD thesis on the use of statistical language models for information retrieval. His research interests include information retrieval, probabilistic modeling, and data analytics. He co-authored over 200 research papers. Djoerd taught several national and international tutorials, including tutorials for the Dutch Research School on Information and Knowledge Systems (SIKS), the European Summer School on Information Retrieval (ESSIR), The Russian Summer School on Information Retrieval (RuSSIR), and the European Conference on Information Retrieval (ECIR).

Dr. Susan Picavet

Susan Picavet, PhD (1964, HSJ) is project leader of the Doetinchem Cohort Study and senior researcher on public health themes like healthy ageing, musculoskeletal health problems (e.g. pain and osteoarthritis), and survey methodology. Since 1996 she works at the National Institute of Public Health and the Environment. She co-authored 57 peer reviewed papers (H factor=26).

Ghita Berrada, MSc.

Ghita Berrada is a PhD student at the Database Group in the Faculty of Engineering, Mathematics & Computer Science at the University of Twente. She holds a MSc by research in pattern Analysis and Neural Networks from Aston University (Birmingham, UK) as well as an engineering degree (equivalent to an MSc, with a major in Computer Science) from École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE) (Evry, France). The goal of her PhD project is to design a medical data sharing platform, using EEG data as example of medical data, in order to support the diagnosis process.

Dr. Dolf Trieschnigg

Dolf Trieschnigg is a postdoctoral researcher with the Human Media Interaction group of the University of Twente. He is interested in various areas of information retrieval and natural language processing. After receiving his MSc degree in computer science from the University of Twente, he started his PhD project in the area of biomedical information retrieval under supervision of prof. dr. Franciska de Jong and prof. dr. ir. Wessel Kraaij. During his PhD project he worked at the European Bioinformatics Institute in Cambridge as a visiting researcher (to work with Dietrich Rebholz-Schuhmann). In his PhD work he investigated how to incorporate domain knowledge into search engines for biomedical researchers. He adapted conventional models for cross-lingual information retrieval to effectively incorporate knowledge from concept thesauri in the retrieval process. After receiving his PhD degree in 2010, he joined the Database Group of the University of Twente as a postdoctoral researcher, where he worked on distributed information retrieval. Since 2012, he has worked for the Meertens Insitute in Amsterdam and the Human Media Interaction group as part of the FACT (Folktales As Classifiable Text) project. In this project he is researching techniques to (semi) automatically assign metadata to Dutch folktales collected in the Dutch folktale database.

Sytske Wiegersma, MSc.

Sytske Wiegersma works as a researcher at the Department of Research Methodology, Measurement and Data Analysis of the University of Twente. After receiving her MSc. degree in Educational Science & Technology, she worked as a research assistant on a project in which she analysed and validated several screening tools for sleep apnea. She recently started her PhD research on new methods and techniques for analysing complex datasets. The focus of her research is to investigate the application of text mining techniques in screening for Post-traumatic Stress Disorder (PTSD), using spoken and written narratives. Next to her PhD research, she works for the IGS Datalab at the University of Twente where she advises on handling, collecting, analysing and archiving research data.

Dr. Carel F.W. Peeters

Carel F.W. Peeters (1982, Nijmegen) received an M.A. in Political Science from VU University Amsterdam as well as an M.Sc. in Statistics from the Katholieke Universiteit Leuven. He obtained his Ph.D. degree in Bayesian Statistics at Utrecht University. Currently he is employed as a postdoctoral researcher at the Department of Epidemiology & Biostatistics, VU University medical center. His research focuses on high-dimensional statistics and integrative statistcal genomics. 

Dr. Stéphanie van den Berg

Stéphanie van den Berg is associate professor at the Department of Research Methodology, Measurement and Data-Analysis at the University of Twente. Her research is at the interface between psychometrics and genetics: it aims at solving problems in genetic research that involve the measurement of behaviour and cognition. The main activity is the development of statistical methods for estimating psychometric-genetic models for both human and animal data sets. Examples include understanding the genetic basis of personality, intelligence and school achievement in humans, and fearful behaviour in dogs. 

Dr. Marieke Coenen

Dr. Marieke Coenen is an Assistant Professor at the Radboud university medical center. Her research entails population-based gene-finding studies, construction of genetic prediction models, and cost-effectiveness analyses of pharmacogenetic tests. The gene-finding research focuses on rheumatoid arthritis disease progression and treatment of patients with biologicals. She has access to two well-characterized cohorts of rheumatoid arthritis patients. For both cohorts detailed longitudinal information concerning demographics, disease activity scores, treatment response, type of medication used and dosing information is available. Her main interest is to develop a prediction model to personalize treatment of rheumatoid arthritis patients treated with the biological anti-tumour necrosis factor (anti-TNF). For this research she closely collaborates with five groups in Europe and the United States to perform a genome-wide association study. Besides genome-wide association studies she has performed several candidate gene association studies to identify predictors of treatment outcome but also to unravel the common genetic background of autoimmune diseases (e.g. RA, psoriasis, celiac disease, systemic sclerosis). Her expertise is in pharmacogenetics of autoimmune diseases and she also applies to optimize treatment of childhood-cancer (osteosarcoma and leukaemia). Concerning cost-effectiveness analyses, she leads a national randomized controlled trial for cost-effectiveness of thiopurine-S-methyltransferase genotyping prior to thiopurine treatment in patients with inflammatory bowel disorders (n=852). This largest prospective study world-wide shows that pre-treatment genotyping results in a statistically significant reduction of leukopenia. She is also involved in research related to the genetic background of pain sensitivity, chronification and treatment. Pain sensitivity and modulation (in combination with EEG) have been measured in 250 healthy subjects. In this cohort we showed that the Drosophila pain gene CACNA2D3 is associated with pain sensitivity.