Using Big Data and various Machine Learning algorithms and Ensembles in order to predict hospitalization and mortality in end-stage renal disease (ESRD) patients.
Real-time Audio Signal Compression Using Machine Learning and Pattern Recognition for Online Streaming.
Analyses of management-employee relations at company level of multi-national companies, in order to identify patterns in attitude and collaboration.
Prediction of health complications of patients with certain diseases and/or illnesses, by means of detection of early signs and symptoms.
Identifying combinations of Gene Expressions in order to categorise and probability of certain patients being susceptible to ALM or AML Leukaemia.
Applying AI and Machine Learning to all available information in order to identify one or several matches. This can be either matching a job to a set of candidates, or a candidate to a set of jobs, as a support to HR departments and recruitment.
Using various Machine Learning, Pattern Recognition and Artificial Intelligence Techniques for Autonomous Vehicles Path Planning, Optimisation, Object Detection and Collision Avoidance.
Serkawt Khola (PhD, MIET, BEng(Hons))
Dr. Khola has a PhD in Electronic Engineering with Focus on Genetic and Evolutionary Algorithms, with in-depth expertise in Machine Learning and Pattern Recognition. He has worked in Research and Development within the fields of Information Technology, Machine Learning, Pattern Recognition and Artificial Intelligence for 20+ years at various public and private organisations, and academic institutions in several countries(Sweden, France, United Kingdom, Denmark, Belgium and others). He has also experience from large multi-national- and multi-disciplinary research and development projects, patent filing, scientific and academic publications etc.
Associate Prof. Dr. Trine P. Larsen (PhD, MA, BA)
Associate Professor Dr. Larsen holds a Ph.D. in Social Policy from the University of Kent, UK with in-depth knowledge of European industrial relations, work-life balance policies and non-standard employment. She has worked in academia within the field of sociology and has been affiliated with different world-leading universities (University of Copenhagen, University of Sorbonne, University of Kent, University of Salahaddin). She has researched, managed large scale projects and published within high ranked international journals. She has recently started in close collaboration with AI experts to apply Machine Learning algorithms to the field of sociology, more specifically industrial relations, management-employee relations and segmented labour markets.