Houxiang Zhang Headshot
Houxiang Zhang
Associate Editor
Houxiang Zhang (IEEE Member 2004-IEEE Senior Member 2012) is a full Professor at the Department of Ocean Operations and Civil Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU). Dr. Zhang received his Ph.D. degree on Mechanical and Electronic Engineering in 2003. From 2004, he worked as Postdoctoral fellow, senior researcher at the Institute of Technical Aspects of Multimodal Systems (TAMS), Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. In Feb. 2011, he finished the Habilitation on Informatics at University of Hamburg. Dr. Zhang joined the NTNU, Norway in April 2011 where he is a Professor on Mechatronics. From 2011 to 2016, Dr. Zhang also hold a Norwegian national GIFT Professorship on product and system design funded by Norwegian Maritime Centre of Expertise. In 2019, Dr. Zhang has been elected to the member of Norwegian Academy of Technological Sciences. Dr. Zhang has engaged into two main including control, optimization and AI application especially on autonomous vehicle, and marine automation, digitalization and ship intelligence. He has applied for and coordinated more than 30 projects supported by Norwegian Research Council (NFR), German Research Council (DFG), EU, and industry. In these areas, he has published over 200 journal and conference papers as author or co-author. Dr. Zhang has received four best paper awards, and five finalist awards for best conference paper at International conference on Robotics and Automation. Recently Dr. Zhang organizes a Special Issue on Intelligent Transportation Systems in Epidemic Areas with IEEE Transactions on Intelligent Transportation Systems (https://ad051eeb-2ac9- 4983-9271-c88f64105e50.filesusr.com/ugd/eaf218_5a846d78c6314d6d9259ce3c4d36af5d.pdf)
Research Interests
1. Control, optimization, and human machine interaction especially on field robotics and autonomous vehicle 2. Artificial intelligence and machine learning 3. Hybrid modelling and co-simulation 4. Marine automation, digitalization and ship intelligence