Professor Yanxia Sun

Overview

Academic Profile Google Scholar Citations (H-Index = 20): https://scholar.google.co.za/citations?user=3X_n4q0AAAAJ&hl=en Scopus (H-Index = 18: 48561117900: https://www.scopus.com/authid/detail.uri?authorId=35180292400 Qualification(s) PhD List of publications https://scholar.google.co.za/citations?user=3X_n4q0AAAAJ&hl=en Research Interests Evolutionary algorithms, Artificial intelligence, Power systems optimsation, Automation, and Nonlinear dynamics. Biography Prof. Yanxia Sun received her joint qualification: DTech in Electrical Engineering, Tshwane University of Technology, South Africa and PhD in Computer Science, University Paris-EST, France in 2012. She has therefore an approach that brings together computing and electrical engineering. She has more than 10 years teaching and research experience. Currently she is serving as an Associate Professor and Acting Vice Dean: Teaching, Learning and Operations in the Faculty Of Engineering and The Built Environment, University of Johannesburg, South Africa. She has lectured seven courses in the universities. Currently she is supervising fifteen D-Tech/PhD students and six MTech/MSc students in the areas of Electrical Engineering. Yanxia Sun has 67 papers published/accepted including 25 ISI master indexed journal papers. She was awarded the National Research Foundation (NRF) rating Y2 (2015-2020) and obtained the NRF incentive grant. She is an IEEE and South African Young Academy of Science (SAYAS) member. She is/was the principal or co-principle investigator of 11 projects including national research grants and industrial projects. For example, I am the principle investigator for one industrial project, using the data provided from the company to develop an algorithm that can predict the "end of life" (predictive maintenance) of sensor ; and determine whether a sensor has been poisoned" instead of reaching "end of life". Related the Industry 4.0, I am the co-investigator of the NRF GRANT for 2018-2020: High Tech Automated Real-time SCADA System for Bottling Process Control Using Basic Industry 4.0 Concept. In this project, we develop a high tech automated bottling process, with very little human intervention, using the advantages of today's current trend of automation, the Industry 4.0, known as "smart factory".