Invited Scholars are leading researchers in the areas of knowledge related to IFRoS, who are invited for short stays of 2 weeks up to 3 months, to teach advanced seminars. They may also supervise coursework and student’s projects. If you want to apply as an invited scholar for the coming semesters please contact email@example.com .
Ing. Matouš Vrba received his Master's degree from the Faculty of Electrical Engineering at the Czech Technical University in Prague and is now pursuing a PhD in robotics in Martin Saska's Multi-Robot Systems group. His main research interest is autonomous micro aerial vehicles with a focus on machine learning, computer vision and robotic perception for drone detection and localization.
As part of his studies, he participated in the prestigious MBZIRC 2020 robotics competition as part of the winning team CTU-UPENN-NYU and in the DARPA SubT competition as part of the CTU-CRAS-NORLAB team. He also co-developed the MRS UAV system for self-localization, planning and control of autonomous aerial vehicles. Matouš Vrba has authored 6 journal publications (3 as lead author) and 5 conference publications (1 as lead author).
Kristian Hengster-Movrić is a docent (~an associate professor) of technical cybernetics and his focus is on mathematical theory of distributed control, consensus problem and optimal control.
Kristian received his Ph.D. degree from University of Texas Arlington, USA, in 2013, having been supervised by Prof. Frank Lewis. For his thesis he was awarded N.M. Stelmakh Prize. At Czech technical University in Prague (CTU) he is currently giving lectures within a graduate course on dynamics and control of networks and a doctoral course on distributed control. He supervises a few doctoral and master students. He also serves as an administrator of the CTU participation in the double-degree Spacemaster (Erasmus Mundus) program.
Dr. Marc Masias received his PhD degree from the University of Girona in 2014 for his research on automatic object detection in astronomical images. He also holds a B.Sc. degree in Computer Science (2010) and a M.Sc. degree in Industrial Computing (2011) from the same university. His research interests include object segmentation, detection and classification in different fields.
He is currently working (and partnering) at Opsis Vision Technologies as a computer vision software engineer. Additionally, he is a lecturer at the University of Girona teaching subjects related to computer vision and machine learning.
Dr. Angelos Mallios received his PhD degree (2014) on computer vision and robotics at Universitat de Girona, in the field of underwater sonar based localization and mapping, and has received numerous awards including 3 Marie Skłodowska-Curie Actions. He specializes in the design of underwater vehicles and sensory technology with a focus on autonomy, accessibility and efficiency. He has been in marine research for over two decades and held researcher appointments in high profile institutes such as the Hellenic Centre of Marine Research in Greece, Universitat de Girona in Spain, and Woods Hole Oceanographic Institution in the US. He has participated in a number of research and innovation projects and cruises all over the world, including H2020, NSF, NASA, and NOPP.
He currently serves as Technical Director and co-founder of PLOATECH, based in Girona Spain, a marine technology consulting company that provides advanced scientific and customized engineering services covering remote sensing, instrumentation R&D, robotics and data processing.
Dr. Gerard Canal is a Royal Academy of Engineering (RAEng) UK IC Postdoctoral Research Fellow at the Department of Informatics, King's College London. His research interest are in the application of AI planning and reasoning techniques to the field of assistive and service robotics.
In March 2020, he completed his PhD in Robotics at the Institut de Robòtica i Informàtica Industrial under the supervision of Dr Guillem Alenyà and Professor Carme Torras. In 2013, he received his bachelor's degree in Computer Science from the Facultat d’Informàtica de Barcelona, part of the Universitat Politècnica de Catalunya. Later, in 2015, he obtained a master's degree in Artificial Intelligence from Universitat Politècnica de Catalunya, Universitat de Barcelona and Universitat Rovira i Virgili.
Dr. Michael Cashmore is Chancellor's Fellow at the University of Strathclyde (Computer and Information Sciences). He is a member of the Human-Centric AI group and leader of the Strathclyde Doctoral School in Explainable AI for Industrial Decision Support.
His research focuses on the challenges of integrating AI Planning and Scheduling in robotics and human-AI teaming. Through a series of projects he has developed the ROSPlan framework for embedding AI Planning tools in ROS.
Dr Enrique Fernández received the PhD degree with distinction from the University of Las Palmas de Gran Canaria in 2013 for his contributions to Ocean Gliders Path Planning. He previously received the BSc degree in Computer Engineering and MSc degree in Intelligent Systems and Numeric Applications in Engineering from the University of Las Palmas de Gran Canaria in 2008 and 2009. Enrique joined PAL Robotics in 2013 and was part of the Navigation Department. In 2015 he moved to Canada to join Clearpath.
He is currently working at OTTO Motors division developing perception systems for self-driving industrial vehicles. His research interests include Simultaneous Localization And Mapping and Computer Vision.
Dr Carles Matabosch, obtained his PhD in Industrial Engineering at the University of Girona. He previously worked as Technical Director at AQSENSE and he is now Manager Software Engineering at the multinational Cognex, in Girona.
In both cases, he developed industrial vision products and projects, especially in the field of three-dimensional Machine Vision. He is author of a patent related to 3D Machine Vision processing procedures and several research articles and conferences.
He is also a member of the Sectorial Advisory Council of the Robotics Campus of the UdG.
Dr. Josep Bosch received the Ph.D. degree with distinction from the University of Girona in 2018 for his research focused on omnidirectional vision applied to underwater robotics. Previously he received the B.Sc. degree in industrial engineering and a M.Sc. degree in information technologies from the University of Girona in 2012 and 2014. He has authored several peer-reviewed articles and participated in many national and international research projects and conferences.
He is currently working on IQUA Robotics developing mapping software for imaging sonars. His research interests include underwater robotics and optical and acoustic mapping.
Dr Oliver Díaz is Associate Professor at the University of Barcelona (Faculty of Mathematics and Computer Science) and senior member at the Barcelona Artificial Intelligence in Medicine Laboratory. He holds a PhD in Electronic Engineering from the University of Surrey, UK (2013) and was a Marie Skłodowska-Curie Postdoctoral Fellow (2015-2017). Dr Díaz has 10+ years international research experience in the field of biomedical data analysis and has participated in 20 research projects (H2020, FP7, EIT Health, ...).
His current research is focused in the development of trustworthy artificial intelligence (AI) algorithms to support clinical decisions in the healthcare sector.
Sebastian Lapuschkin received the Ph.D. degree with distinction from the Berlin Institute of Technology in 2018 for his pioneering contributions to the field of eXplainable Artificial Intelligence and interpretable machine learning. From 2007 to 2013 he studied computer science (B. Sc. and M. Sc.) at the Berlin Institute of Technology, with a focus on software engineering and machine learning. Currently, he is a tenured researcher and head of the Explainable AI Group at Fraunhofer Heinrich Hertz Institute (HHI) in Berlin. He is recipient of multiple awards, including the Hugo-Geiger-Prize for outstanding doctoral achievement and the 2020 Pattern Recognition Best Paper Award. His research is focused on computer vision, (efficient) machine learning and data analysis, data and algorithm visualization, and the interpretation, analysis and rectification of machine learning system behavior.