Ray Gosine is a professor of electrical and computer engineering at Memorial University and a visiting professor at the Munk School of Global Affairs and Public Policy at the University of Toronto.
His research is in the areas of intelligent systems, robotics and automation with a particular interest in the application of these technologies to natural resource industries, most recently oil and gas and mining. He has published his research results in top rated journals and conference proceedings. His academic appointments included an NSERC Chair in Industrial Automation at the University of British Columbia and the J.I. Clark Chair of Intelligent Systems for Operations in Harsh Environments at Memorial University.
Ray is also interested in the broader impacts of advanced technologies on the public, and he recently chaired a Public Review Panel (www.nlhfrp.ca) to advise government on the scientific, socio-economic, public policy, regulatory, environmental and public health issues associated with unconventional oil and gas development (i.e. hydraulic fracturing or fracking). Currently he is collaborating with colleagues at the University of Toronto and Memorial University on research related to understanding the opportunities, challenges, and consequences associated with automation and digitalization of Canada’s underground mining and offshore oil and gas industries.
Ray has held various senior roles at Memorial University, including Vice-President Research (pro tempore), Associate Vice-President Research, Dean of Engineering, and Director of Intelligent Systems at C-CORE, a research corporation owned by Memorial University.
Fellow, Canadian Academy of Engineering
Fellow, Engineers Canada
President’s Award for Outstanding Research (Memorial University)
Gosine, R., Dusseault, M., Gagnon, G., Keough, K., Locke, W. (2016) “Unconventional Opportunities and Challenges: Results of the Public Review of the Implications of Hydraulic Fracturing Operations in Western Newfoundland”.
Gosine, R., Warrian, P. (2017). “Digitalizing extractive industries: the state-of-the-art to the art-of-the-possible”. Munk School of Global Affairs Innovation Policy Lab White Paper Series 2017-004.
Nguyen, T., Mann, G., Vardy, A., Gosine, R. (2019). “Developing computationally-efficient nonlinear cubature Kalman filtering for visual inertial odometry”, ASME Journal of Dynamic Systems, Measurement, and Control, 141(8): 081012-081012-10.
Wanasinghe, T., Mann, G., Gosine, R. (2015). “Distributed leader-assistive localization method for a heterogeneous multirobotic system”, IEEE Transaction on Automation Science and Engineering, 12(3): 795-809.
De Silva, O., Mann, G., Gosine, R. (2015). “Efficient distributed multi-robot localization: A target tracking inspired design”, IEEE Int. Conf. on Robotics and Automation (ICRA ’15), Seattle, USA.