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Luiza Marnet (ESR #1) owns a Master’s degree in Electrical Engineering, in the area of Artificial Intelligence, from the Federal University of Rio de Janeiro. And her Bachelor was in Control and Automation Engineering at the Federal Fluminense Institute. During her Master’s, she worked with crack propagation monitoring using Acoustic Emissions. And before joining the REMARO Team, she worked as a temporary Professor at the Federal University of Rio de Janeiro and as a data scientist. Now, she is working at EIVA as a Ph.D. student at Aarhus University. In her part of the project, she works with the classification and detection of objects in underwater images using deep learning methods. As part of her project, she needs to assess the uncertainties of the models, turning the predictions more reliable. In this project, her main supervisor is Professor Erdal Kayacan and her industrial supervisor is Doctor Yury Brodskiy. Her current fields of interest are machine learning and computer vision.

Olaya Álvarez Tuñón (ESR #2) is a PhD student at Aarhus university. She holds a degree in Electronics Engineering (2015), and an MSC in Robotics and Automation (2019) from the University Carlos III of Madrid. She has experience as a researcher assistant in the RFCS project STAMS. Within REMARO, she will work in the development of algorithms for vision-based navigation for underwater safety critical applications. For that, she will make use of camera-based Deep Learning algorithms to aid navigation of underwater vehicles. Her main supervisor is Erdal Kayacan and her industrial supervisor is Yury Brodskiy. Her main research interests are deep learning and computer vision for mobile robot navigation.

Nael Jaber (ESR #3) holds a Bachelor in Mechatronics Engineering from Rafik Hariri University and a Masters in Mechanical Engineering from the American University of Beirut, Lebanon. During his graduate studies, he served as a graduate researcher at the Vision and Robotics Lab (VRL) of the American University of Beirut where he conducted an applied research in the field of Computer Vision. His master’s thesis aimed for the detection and localization of Processionary Moth nests in pine trees by proposing an AI-based solution which relies on fusing multi-modal imagery for the training of an advanced machine learning model. Nael is a researcher at DFKI, passionate about AI, computer vision, and sensor fusion. As part of the ETN – REMARO project, he is supervised by Prof. Dr. Frank Kirchner and co-supervised by Dr. Bilal Wehbe on his topic entitled “Sonar-based 3D reconstruction for dense underwater SLAM maps” where he will research novel techniques for 3D reconstruction in the aim of obtaining dense environmental representations in the underwater domain. Furthermore, he will develop and investigate sensor fusion algorithms of available underwater sensing modalities for the purpose of achieving enhanced and detailed underwater maps.


Laura Weihl (ESR #4) is a Ph.D. Student in the REMARO project since August 2021. Her background is in Maths, Computer Science and Machine Learning. She has worked on Facial Verification using Machine Vision, more recently she has been interested in Risk Analysis in Iris recognition systems. Right now she is working on fusing Property-based Testing with Neural Networks of perception components in underwater robots. If you don’t find her coding she is playing piano or singing in a choir.

Sergio Quijano (ESR #7) is a Ph.D. student at the IT University of Copenhagen. His academic background consists of a Computational Systems Engineering degree and an MSc. in Informatics from the Technical University of Munich. He counts several years of experience as a Software Engineer. In REMARO, under the supervision of Dr. Mahsa Varshosaz and Prof. Andrzej Wasowski, he is working on Model-Based Testing to support system-level safety assessment for autonomous underwater robots. His main research interests are Software and Systems Engineering, Safety Engineering, Self-Adaptive and Multi-Agent Systems.

László Antal (ESR #9) is an early-stage researcher of the research group Theory of Hybrid Systems at RWTH Aachen University, Germany. His previous studies involve a BSc in Computer Science and an MSc in Data Analysis and Modelling, both at the Babes-Bolyai University of Cluj-Napoca, Romania. During his studies, he participated in multiple projects involving AI and robotics, e.g. he with his team participated in a challenge, with the scope of building an autonomous robot vehicle, that can navigate on an artificial track. In REMARO he is one of the persons who are responsible for assessing the safety of AI-based learning methods used on the underwater robot. He will be working under the supervision of professor Erika Ábrahám. His current interests are Machine Learning, Computer Vision and Formal Methods.

Jeremy Coffelt (ESR #11) holds a MSc in Electrical Engineering from the Technical University of Denmark. His thesis investigated real-time anomaly detection in side scan sonar on AUVs. Before returning to school, Jeremy taught mathematics for 10 years in Texas. Since returning to school, he has completed two internships with NASA. Jeremy is currently pursuing a PhD in Artificial Intelligence from the University of Bremen under the supervision of Prof. Michael Beetz. At the same time, he is gaining industry experience with AUVs under the supervision of Dr. Peter Kampmann at ROSEN Research and Technology. The subject of his dissertation will be the development of a knowledge service that will enable autonomous underwater pipeline inspection by AUVs with uncertainty in perception and a priori environmental information. His primary research interests involve applications of AI and computer vision in both traditional imagery and acoustic sensor data, as well as robotics simulation in ROS/Gazebo.

Mahya Mohammadi Kashani (ESR #12) is a Ph.D. student in Computer Science at the IT-University of Copenhagen (SQUARE group). She works as ESR12 under the supervision of Prof. Andrzej Wąsowski and co-supervising of Prof. Michael Beetz (University Bremen) and Dr. Peter Kampmann (Rosen Group). Her Ph.D. project mainly concentrates on designing a Bayesian-inference-based prospection method to improve the reliability of underwater robots performing inspection tasks. There she aims to develop a probabilistic decision-making model to assess risks and probabilities of undesirable states and use this model to assist in plan selection. She has recently become interested in probabilistic programming and probabilistic optimization. Before joining the REMARO group, her main research interests focused on pattern recognition algorithms, particularly sparse reconstruction/coding and search space reduction in the Automatic Image Annotation task. She also worked for one year as a computer vision engineer to develop the vision of industrial recycling robots.

Juliane Päßler (ESR #14) got her BSc and MSc from the University of Münster in mathematics with computer science as a minor subject. Her master’s thesis was on a topic at the crossroad of geometric group theory and mathematical logic. In the REMARO network she works at the University of Oslo under the supervision of Silvia Lizeth Tapia Tarifa, Carlos Hernández Corbato and Luis Madureira. Her Ph.D. project focuses on developing verification methods for self-adaptive systems. She aims to develop analysis techniques that are able to (i) verify that a reconfiguration of the self-adaptive system is required and (ii) verify reconfigurations of the system.

Tobias John (ESR #15) is a Ph.D. student at the University of Oslo. He studied Computer Science at TU Ilmenau and did a Master’s program in Computational Logic at TU Dresden. In REMARO, he is working on using logic to evaluate (and increase) the robustness of controllers that work with evolving knowledge bases. His Ph.D. project is supervised by Einar Broch Johnsen and co-supervised by Erik Stensrud and Michael Beetz.

Martin Aubard (ESR #5) – From OMST / Faculty of Engineering of the University of Porto

Gustavo Silva (ESR #8) – From TU Delft

Sasan Vakili (ESR #13) – From RWTH Aachen University