Profile

TAYEB MEDJELDI

TAYEB MEDJELDI

C2T3

I’ve professional and faculty experience of more than 28 years. I taught at the university level for over 23 years. I’ve also an experience of six years in the telecom industry and electronic maintenance. I contributed to the formation of dozens of engineering, Masters and PhD and I contributed in many research within national and international projects before coming in Canada. I have about thirty articles published in journals and proceedings. Since my arrival in Canada, I have a postdoc at the University of Sherbrooke for two years followed by a brief stint at Sherbrooke University Hospital, Department of Nuclear Medicine as a professional researcher. From the beginning of 2009, I joined the transfer center of technology (C2T3) as a teacher-researcher. In addition to teaching at the electrical engineer department, I implemented several research projects for which I was able to get subsidized with PART (3), FQRNT (1), NSERC (7) and DECanada (2). In addition I’ve done numerous networking meetings with various government agencies, universities, industry, academia, and colleges. I am the initiator of a project funded by the FQRNT on the development of a remote monitoring system based around an intelligent camera. It must embed a set of sensors to detect any sign of discomfort patients seniors who wish remain at home or in nursing homes. I am also the initiator C2T3 a project to detect the presence of bacteria in food and draw them for a possible early withdrawal of these. The principle is based on the use of RFID. In general, the areas of research that I developed at the C2T3 concern including the acquisition and intelligent data transmission, detection, tracking and positioning, and a partial cooperation in the field of software radio. I am also interested in the inter-vehicular communication and the development of new wireless standards such as WiMAX, WiFi and ZigBee. My other areas of expertise include the identification and diagnosis, signal processing and image by different methods such as neural networks, linear prediction and wavelets. >