Keynote Speakers


Prof. Neil Bose
Memorial University, Canada

Neil Bose has been VP Research at Memorial University since November 2017. Prior to this, he served as principal of the Australian Maritime College (AMC), the national institute for maritime education, training, research and consultancy at the University of Tasmania. Dr. Bose was also a professor of maritime hydrodynamics at the AMC. From 2009 to 2011, he was director of the AMC’s National Centre for Maritime Engineering and Hydrodynamics. He joined the college in May 2007 as the manager of the Australian Maritime Hydrodynamics Research Centre. Before his move to Tasmania, Dr. Bose was a long-standing and respected member of Memorial University’s research community. He came to Memorial in May 1987 as an assistant professor in the naval architectural engineering program. In his time at Memorial, Dr. Bose served as director of the Ocean Engineering Research Centre, chair of ocean and naval architectural engineering program and, in 2003, was named a Tier 1 Canada Research Chair in Offshore and Underwater Vehicles Design in the Faculty of Engineering and Applied Science. Dr. Bose received an honorary degree from the Nikola Vaptsarov Naval Academy, the oldest technical educational institution in Bulgaria. Dr. Bose obtained his B.Sc. in Naval Architecture and Ocean Engineering from the University of Glasgow in 1978 and his PhD, also from Glasgow, in 1982. Dr. Bose was appointed to the NRC Council in June 2018.

Autonomous Underwater Vehicle Applications in Marine Pollution

Abstract: Marine pollution is a global problem that has severe adverse environmental and socio-economic impacts. Oil spills are one form of pollution, chemical run-off and plastics in the ocean are others. Climate change and severe degradation of our ecosystem are some of the outcomes from this pollution. Information about pollution in the water column is critical to the understanding of its subsurface behavior which in turn enables timely and effective mitigation. Following the Gulf of Mexico blowout, autonomous underwater vehicles (AUVs) were successfully used to characterize submerged oil that was trapped at a depth of approximately 1200 m and provide a more comprehensive analysis of the impacted parts of the water column. In our research, AUV capabilities are being advanced specifically for the understanding of marine pollution and response. Innovative adaptive mission planning approaches for discontinuous and patchy plumes made up of bubble or droplet clouds or other potential items of interest such as micro-plastics, are being researched to improve performance of AUVs and their onboard sensors in delineating subsurface plumes. Using adaptive sampling, the AUV is designed to autonomously modify its mission path in real-time based on features of the plumes detected by on-board sensors. Hence the AUV path is concentrated within areas of interest and in information-rich areas identified by the sensors, optimizing the AUV response. Existing autonomous underwater vehicles and sensors (e.g. gliders, ARGO floats and larger AUVs) provide ocean data. This sensed data has been limited primarily to physical oceanographical health and the expansion of the global ocean observing system. More people have become knowledgeable about and trained in their use and vehicles are becoming much more reliable and cheaper. So there are opportunities to expand AUV use, increase their energy storage and endurance, and enabling their use as sentinels on continuous watch for pollutants in coastal waters, open ocean and more extreme climate locations such as long term operation in iced waters. Vehicles can be developed to actually collect pollutants, such as to skim oil after an oil spill disaster or using trawls to collect micro-plastics in the ocean and larger plastics in estuaries. A key advantage is the ability of AUVs to sense and act at depth, not just at the water surface. The target communities of our research includes regulators, marine pollution agencies, oil spill response organizations, industry, AUV manufacturers, operators, oceanographers and other scientists.



Prof. Fabio Tosti
University of West London, UK

Fabio Tosti (IEEE M’17–SM’19) received the M.Sc. and Eng. degrees (cum laude) in Infrastructure and Transportation Engineering from Roma Tre University, Rome, Italy, in 2010, and the Ph.D. degree in Civil Engineering with European Doctorate Label (excellent rating) from Roma Tre University, in 2014. A registered Chartered Engineer, he is a Professor of Civil Engineering at the School of Computing and Engineering, University of West London (UWL), London, U.K., and the Director of “The Faringdon Research Centre for Non-Destructive Testing and Remote Sensing” at UWL. His research interests include the development of new algorithms, methodologies, and models for geoscience applications and the non-destructive and satellite remote sensing assessment, repair, and maintenance of civil infrastructure and greenspace. He has authored/co-authored over 210 research publication records in international journals, conferences, and books and delivered numerous keynote and invited lectures. Prof. Tosti was a recipient of the ECSs Award by the European Geosciences Union (EGU) in 2017 and several Best Paper Awards at International Conferences, including the 2021 IEEE Asia–Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS2021) and the IEEE 2020 43rd International Conference on Telecommunications and Signal Processing (TSP2020). He was the General Co-Chair of the 3rd and 2nd International Workshop on Signal Processing Techniques for Ground Penetrating Radar Applications in 2022 and 2020 (TSP—IEEE Conf. Record 49548), respectively, and he served as the main organiser, scientific committee member and chair of technical sessions in 50+ international conferences and workshops. He served as the managing guest editor for various journals. He is the Editor-in-Chief of NDT (MDPI), and an Associate Editor of the International Journal of Pavement Engineering (IJPE), Remote Sensing (MDPI), Frontiers in Remote Sensing, Geoscientific Instrumentation, Methods and Data Systems (GI), and the Journal of Railway Engineering.  


Prof. Danica Kragic
Royal Institute of Technology, KTH, Sweden

Danica Kragic is a Professor at the School of Computer Science and Communication at the Royal Institute of Technology, KTH. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University, Brown University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems. Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is a member of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Engineering Sciences and Young Academy of Sweden. She holds a Honorary Doctorate from the Lappeenranta University of Technology. She chaired IEEE RAS Technical Committee on Computer and Robot Vision and served as an IEEE RAS AdCom member. Her research is in the area of robotics, computer vision and machine learning. She is a recipient of ERC Starting and Advanced Grants. Her research is supported by the EU, Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research and Swedish Research Council. She is an IEEE Fellow.