Volodymyr Voytenko started teaching in Sheridan's Faculty of Applied Science and Technology in 2010. He has a bachelor’s degree and a master’s degree in computer science (1992), and a PhD in computing technique and mathematical modelling (2000), all of which he received from Taras Shevchenko National University of Kyiv in Ukraine.
Volodymyr has 17 years of teaching and research experience in computer science and information systems. Before joining Sheridan, he taught at King's University College in Edmonton, Alberta and the University of Prince Edward Island in Charlottetown, PEI.
He is a fellow of the Association for Computing Machinery (ACM) and the International Association of Science and Technology for Development (IASTED). He has more than 30 scientific publications, and has participated in many international conferences in Canada and abroad.
Teaching interests: software engineering; mobile application development
Research interests: mobile computing; computer and mathematical interdisciplinary modelling
Contributions to research
CMI project: Using data science and machine learning techniques for the prediction of osteoporosis
In this collaborative research project involving Inovex, Osteoporosis Canada and Sheridan’s Centre for Mobile Innovation (CMI), we are addressing the challenging problem by exploring and analyzing osteoporosis data through data science and machine learning techniques. The goal is to better understand the characteristics and interrelationships between factors that may impact whether a person is susceptible to contracting this disease. The research activities will also include determining the predictors with insights that may lead to better prevention strategies.
CMI project: Predictive analytics in health care
As the main outcome for the project, our team designed and developed a system prototype for decision-making activity in a health-care sector with Boomi integration platform support. Boomi is a business platform provided by industrial partner Interware that specializes in cloud-based integration, API management and master data management. The system prototype we have built provides diagnosis error prevention based on EHR (Electronic Health-care Record) and doctor medical notes. The project demonstrated a great support for Boomi as a platform environment for integrate data from various sources, with effective real-time data management, and with a possibility of further analytics and medical decision making activity in health care.
CMI project: EMS simulator
Design and develop an efficient processing system for multi-channel Electrical Muscle Stimulation (EMS) circuit. EMS involves the use of pulsed electrical current to stimulate muscle "motor points," causing the corresponding muscle to contract. The EMS device generates an amplitude controlled pulsed electrical signal and passes it to the targeted "motor point" via an electrode.
CMI project: Smart home
Creating mobile solutions based on smart-home technologies (using IoT sensors, wireless tag sensors (http://wirelesstag.net) and other sensors) to assist older adults to live well, independently and safely, at their homes.