Bias in O-Information Estimation

Dr. Jie Li is a postdoctoral researcher at the University of Amsterdam, where his research focus is on building information theoretical higher-order network models and applying the models to unravel the intricacies of human disease associations. The core of his work is to develop novel methods to construct a comprehensive disease network combining pairwise and high-order interactions and identify the biological pathways and causal mechanisms of the development of human diseases. Dr. Li's current research interests lie primarily in information-theoretic causal inference and higher-order interactions, AI in complex systems, multiplex disease networks, and their applications in biomedical and ecological fields. His expertise traverses a diverse spectrum, from bio-complexity engineering, ecological pattern forecasting to human disease connectivity, from digital signal processing, data analytics, and visualization to causal inference, complex networks modeling and ML/DL algorithms. Dr. Li's research efforts have resulted in multiple impactful papers, technical reports within projects, and presentations at international conferences.

Dr. Terho Lehtimäki is currently a professor of Clinical Chemistry and Chief Physician of the Department of Clinical Chemistry, Tampere University, Faculty of Medicine and Health Technology and Fimlab Laboratories (Ltd), Pirkanmaa Hospital District, Finland, which is the second largest clinical laboratory in Finland. His research interests are focused on cardiovascular disease risk factors, atherosclerosis biomarkers, vascular and cell biology and functional genetics of diseases. He has over 1300 publications from the field including articles in all world top journals. In addition, he is the responsible investigator of the genetic section of The Cardiovascular Risk In Young Finns study (YFS) and The Finnish Cardiovascular Study (FINCAVAS) and the leader of The Tampere Vascular Study (TVS) focusing on the use of “OMICS” techniques in the research of atherosclerosis and functional genetics. He has skills in traditional and problem based teaching methods as part of the Faculty of Medicine and Health Technology of Tampere University, which has been nominated three times as a Centre of Excellence in high level teaching by the Finnish Higher Education Evaluation Council. Professor Lehtimäki graduated as MD and PhD in 1992 from Tampere University. He was nominated as senior lecturer (docent) in Medical Biochemistry, at the Tampere University in 1996, Specialist in Clinical Chemistry in 1999 and a senior lecturer (docent) in Clinical Chemistry, University of Kuopio in 2003.

Dr. Jos A. Bosch has been appointed associate professor in the Department of Psychology, section Clinical Psychology in 2012. His research investigates the psychobiology of medical disorders, with the aim of understanding and mitigating the impact of disease. His dual expertise in psychology and biology allows him to approach this topic in a genuinely interdisciplinary manner, whereby he integrates methods and concepts from both fields, and apply these to experimental laboratory studies, clinical investigations, and epidemiological analyses. More recently, his work has expanded to include Data Science and Artificial Intelligence (AI) as a source of novel approaches to the analysis and modification of human biology and behavior. The latter program of research is funded by two H2020 consortium grants, of which he is a lead and a coordinator, and involves intensive collaborations with groups across continental Europe, the UK, and the US. Since 2019, he has been Associate Editor of Health Psychology Review, and he has previously acted as associate/senior editor for Brain, Behavior & Immunity (2011–2014), Psychological Bulletin (2010–2013), and Health Psychology (2010–2015), for which he is currently still on the editorial board. His research interests include biobehavioral pathways linking wellbeing and health, data Science and AI approaches to behavioral assessment and modification, and non-invasive psychophysiological assessment using salivary diagnostics.

Dr. Rick Quax is an Assistant Professor in the Computational Science Lab of the University of Amsterdam and a Resident Fellow of the Institute for Advanced Studies. Furthermore, he is a board member of the Dutch Chapter of NetSci; a board member of the Dutch Institute for Emergent Phenomena; and a member of the Netherlands Platform for Complex Systems. He is fascinated by the emergence of complex systemic behavior which arises from the interactions in a system. Examples include human cognition arising from neurons and synapses; cellular regulatory processes arising from proteins and RNA; flocking patterns arising from birds and fish; and societies arising from individuals. There is currently no universal method to understand or predict such complex, emergent behaviors. He is developing new methods based on information theory. He works on a wide variety of projects, including biomedicine, organized crime, in the hope of transferring knowledge across domains as well as identifying universalities in their emergent properties. His team’s activities include developing new theory; new software; and new data analyses.