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Kaya Kuru is a Lecturer/Researcher in the School of Engineering, University of Central Lancashire (UCLan). Before UCLan, he has studied and worked in several best universities for 15 years such as Middle East Technical University (METU), Southampton University and Gulhane Training and Research Hospital and Medical University (GATA). He is interested in developing autonomous intelligent systems and decision support systems based on machine learning and image processing algorithms. He is keen to develop these kinds of applications on Android systems using wireless technologies.
Kaya contributes to several scholarly journals as a reviewer.
Kaya Kuru has been working as a Lecturer/Researcher in the School of Engineering at the University of Central Lancashire. Prior to joining the University of Central Lancashire, he has worked at the department of Communication, Electronics and Information Systems (IT) within a university, GATA, for 15 years as a database administrator, software developer, web designer, software development manager and department manager (1998-2014) excluding his work for NATO as an advisor in 2005/2006 and his postdoc studies in 2012/2013. He was one of the key people who established the Department of Medical Informatics in GATA. He was also one of the chief people directing one of the biggest software project into the success, named “Military Health Care Automation System” with a budget over $50 million for six years in addition to many other projects. The project including many different kinds of systems such as inpatient, outpatient, laboratory, clinic, pharmacy, radiology, PACS, nursing, logistics, finance and billing, management, decision support and insurance modules was a tough project and all the previous software systems were replaced by new systems from scratch in which the use of paper has been minimized through automation and transition. What makes the project more difficult was that all designed software, hardware, network, and medical devices were supposed to work harmoniously connected to each other in more than 100 military health units (41 of them are big hospitals, 2 of them are the two biggest hospitals in the country) scattered all around the country in different cities.
He has graduate certificates of MSc (2003) and PhD (2010) degrees in Information Systems from the Middle East Technical University in addition to his MBA degree (2007) from the Selcuk University after completing his undergraduate studies (1993) from the Turkish Military Academy and the Middle East Technical University. The methodology he established during his PhD studies using ML algorithms was published by International journal of Medical Informatics (SCI). He studied both Applied Forensic Sciences in the School of Gendarmerie in 1995 and Applied Electronics and Computer Systems in the Military School of Communication, Electronics and Information Systems in 1999. During his work for NATO, he attended a certificate program of Medical Informatics for a year in the Medical Faculty at University of Sarajevo under the supervision of Prof. Izet Masic. This program forms part of this School's PhD in Medical Informatics and Statistics. Furthermore, he carried out his post doctorate studies (2012-2013) in machine learning, image processing and decision support systems in the School of Electronics and Computer Science at the University of Southampton as a member of the Signals, Images and Systems (ISIS) Research Group under the supervision of Prof. Mahesan Niranjan. During his postdoc studies, a novel clustering algorithm and a diagnostic decision support system named "A biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics" was developed and published by International Journal of Artificial Intelligence (SCI).
He has a considerable industrial experience. He has a patent for the treatment of nocturnal enuresis (NE) disease titled as "Methods and apparatuses for estimating bladder status". In addition, he has several certificates in programming, web design and database administration from several leading companies such as Microsoft and Oracle by attending short term applied training courses. His previous studies are in the subject areas of artificial intelligence, machine learning, computer vision/image processing, pattern recognition, data mining, bioinformatics, knowledge acquisition and modelling/simulation. His research interest is development of embedded autonomous and hybrid intelligent systems using ML and image processing algorithms. He is keen to develop these kinds of applications on Android systems by employing intelligent knowledge based systems, sensors and mobile/wireless technologies. In this sense, Kaya is actively working in a number of collaborative research projects in the Intelligent Systems Research Group at UCLan.
He published his studies in scholarly journals in Science Citation Index (SCI), and he attended many top level conferences in Conference Proceedings Citation Index - Science (CPCI-S) as a speaker. He has been awarded for his studies and work many times. Some of his awards are presented below:
He is currently working in several autonomous intelligent systems projects in a collaboration with several leading companies and prominent organizations.
Kuru K., Ansell D., Khan W. and Yetgin H. (2019). Analysis and optimisation of unmanned aerial vehicle swarms in logistics: An intelligent delivery platform. IEEE Access, IEEE, 7(1): pp.15804 - 15831. ISSN: 2169-3536. DOI: 10.1109/ACCESS.2019.2892716.
Khan W., Ansell D., Kuru K., Bilal M.(2018). The Flight Guardian: An Intelligent Warning System for the Flight Safety Improvements by Regular Monitoring of Aircraft Cockpit Instruments. Journal of Aerospace Information Systems,15(4): pp. 203-214, ScholarOne. DOI: 10.2514/1.I010570.
Kuru K., Khan W. (2018). Novel hybrid object-based non-parametric clustering approach for grouping similar objects in specific visual domains. Applied Soft Computing, Elsevier, 62: pp. 667–701. ISSN: 1568-4946. DOI: 10.1016/j.asoc.2017.11.007.
Khan W., Kuru K. (2017). Intelligent system for spoken term detection using the belief combination. IEEE Intelligent systems, IEEE, 32(1): pp. 70-79. ISSN: 1541-1672. DOI: 10.1109/MIS.2017.13.
Kuru K., Niranjan M.,Tunca Y., Osvank E., and Azim T.(2014). A biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics. Artificial Intelligence in Medicine, Elsevier, 62(2): pp. 105-18, 2014. DOI: 10.1016/j.artmed.2014.08.003.