Alexandru LAVRIC
Ph.D. Eng. Lecturer
Lecturer Eng. Ph.D. Alexandru LAVRIC was born in 1987. He received the Bachelor’s Degree in Administrative Sciences and the Master’s Degree in Business Affairs from the Faculty of Economics and Public Administration, “Ștefan cel Mare” University of Suceava, in 2008 and 2010, respectively, and the M.Sc. degree in computer and communication networks and the Ph.D. degree in computer technology from the “Ștefan cel Mare” University of Suceava, in 2011 and 2013, respectively. He is currently with the Faculty of Electrical Engineering and Computer Science, “Ștefan cel Mare” University of Suceava. The research activity developed so far reasserts the author’s researcher ability, based on a solid background in the field of WSN sensor networks and neural network algorithms. The proposed algorithms and the development systems presented in various scientific papers are visible on an international level, as revealed by the presence of citations. The proposed findings are very topical and are viable solutions directed at increasing the efficiency of the high-density sensor networks. As a doctoral research student, he was a member of the project “Improvement of the doctoral studies quality in engineering science for development of the knowledge-based society- QDOC” Contract No. POSDRU/107/1.5/S/7853. During the period 2014-2015, he was a member of the post-doctoral research project “SOCERT. Knowledge society, dynamism through research”, Contract No. POSDRU/159/1.5/S/132406., which allowed him to continue his research on WSN wireless network sensors, particularly their impact as part of the Smart City concept. He has published more than 50 scientific papers. During his activity he was member of various research projects like ”Intelligent conductive charging stations, fixed and mobile, for electrical propulsion transport (SMiLE-EV)”, PN-III-P1-1.2-PCCDI-2017-0776/No. 36 PCCDI/15.03.2018. His research interests include WSN, the IoT systems, smart sensors, wireless communication technologies, neural networks, machine-vision artificial intelligence and deep-learning techniques.