Michaela Klauck holds a PhD in computer science and has a background as a research associate at Saarland University, specializing in quantitative verification. Her main research focus lies in the verification of planning and decision-making in autonomous systems. She has been featured in 30 scientific articles so far available online and her PhD thesis "On the Connection of Probabilistic Model Checking, Planning, and Learning for System Verification" is available online.

Michaela is a leading member of the CONVINCE project, leveraging her expertise in model-checking robotic deliberation and autonomous driving behaviour to enhance the robustness of autonomous robots. Her organizational skills, attention to detail, and inspiring work ethic are essential elements contributing to the anticipated success of the CONVINCE project in the future.

Outside of her professional pursuits, she finds joy in playing musical instruments like the saxophone, violin, and guitar, as well as engaging in long-distance runs and travelling. Fun fact about Michaela- she is a research engineer who doesn’t like coffee and can ride a unicycle!

Michaela enjoys the interdisciplinary nature of her work, particularly when building bridges between model checking, planning, and learning during her PhD by investigating the quality of neural networks for autonomous navigation with the help of statistical model checking. Now, she is inspired by understanding the needs and challenges of the robotic community to find solutions in formal methods that benefit all parties involved. Additionally, Michaela enjoys the challenges of her work, especially in finding ways to make robotic systems more robust through formal verification methods. When looking towards the future of AI, she is most excited about the potential for AI to revolutionize automation and human-robot interaction, opening new dimensions in our daily lives.

Michaela Klauck holds a PhD in computer science and has a background as a research associate at Saarland University, specializing in quantitative verification. Her main research focus lies in the verification of planning and decision-making in autonomous systems. She has been featured in 30 scientific articles so far available online and her PhD thesis "On the Connection of Probabilistic Model Checking, Planning, and Learning for System Verification" is available online.

Michaela is a leading member of the CONVINCE project, leveraging her expertise in model-checking robotic deliberation and autonomous driving behaviour to enhance the robustness of autonomous robots. Her organizational skills, attention to detail, and inspiring work ethic are essential elements contributing to the anticipated success of the CONVINCE project in the future.

Outside of her professional pursuits, she finds joy in playing musical instruments like the saxophone, violin, and guitar, as well as engaging in long-distance runs and travelling. Fun fact about Michaela- she is a research engineer who doesn’t like coffee and can ride a unicycle!

Michaela enjoys the interdisciplinary nature of her work, particularly when building bridges between model checking, planning, and learning during her PhD by investigating the quality of neural networks for autonomous navigation with the help of statistical model checking. Now, she is inspired by understanding the needs and challenges of the robotic community to find solutions in formal methods that benefit all parties involved. Additionally, Michaela enjoys the challenges of her work, especially in finding ways to make robotic systems more robust through formal verification methods. When looking towards the future of AI, she is most excited about the potential for AI to revolutionize automation and human-robot interaction, opening new dimensions in our daily lives.

Dr Masoumeh Iran Mansouri holds a PhD in Computer Science from Örebro University and is currently an Associate Professor in the School of Computer Science at the University of Birmingham. Her professional focus includes Knowledge Representation and Reasoning (KR&R) for Robotics, with a particular emphasis on hybrid methods that integrate various aspects such as automated task and motion planning, scheduling, and temporal and spatial reasoning. Additionally, she is interested in the ethical and social implications of technology, specifically in robotics/AI, and areas where cultural studies intersect with robotics. Dr. Mansouri has significantly contributed to the field of robotics, featuring in numerous scientific publications. Her leadership and expertise are vital in driving the advancements in the CONVINCE project.

As one of the leading members of the CONVINCE project, Masoumeh’s team tackle a range of tasks, including developing rapid and reliable planning for simulations, behaviour refinement, developing adaptable coverage planners to enhance motion planning, and real-time motion-level verification systems. Their objective is to devise planning methods for refining tasks while considering uncertainties in the environment and dynamic objects. This includes creating algorithms to pinpoint the root causes of unexpected events and adjusting behaviours to accommodate new actions required for unforeseen circumstances. These developments will aid in shaping the CONVINCE deliberation system.

Beyond her academic pursuits, Masoumeh enjoys expressing her creativity through painting and music. She likes to use watercolor as her medium because she finds it more liberating and expressive. Along the same line, she enjoys playing the drums, particularly in the realm of jazz music because it is more spontaneous and allows for more creativity and improvisation than other genres. She is also an avid runner, currently training for her first marathon.

Masoumeh's journey into AI and robotics started with her passion for programming and technology. She has always been a skilled programmer, but found programming a robot was more interesting and engaging than working with software on a 2D screen. The dynamic and interactive nature of robotics, combined with the ability to see the physical manifestation of her programming efforts, made it a more appealing field for her to pursue. Hence, she naturally finds excitement in the interdisciplinary nature of her work, particularly in building bridges between different areas of research. Collaborating with fellow researchers and exploring innovative solutions to real-world challenges enhances her enthusiasm for the field. Masoumeh also finds joy in discussing ideas with her team and making meaningful contributions to the project. Looking forward, Masoumeh is most excited about the potential of AI to revolutionize healthcare and address critical issues such as cancer treatment. She sees AI as a powerful tool for driving innovation and improving lives, and she's eager to contribute to advancements in the field.

Razane Azrou completed her Engineering degree from Sorbonne University in France. Her expertise lies in AI technology and solutions, with a specialization in Situation Awareness for robots. Razane has contributed to various projects, including:

Roborongeur: A project initiated during her first year of college, Roborongeur aimed to develop a robotic adaptation of a workstation to aid individuals with disabilities. Partnering with Sorbonne University's Disability Mission, they developed a robotic adaptation of a workstation. This initiative was inspired by a lab technician's chronic illness, exacerbated by repetitive tasks. The project led to the creation of a rotating and automated platform designed to reduce physical strain. Later, Polytech Sorbonne students enhanced the platform, developing a second version with advanced automated features and a digital interface for better data collection.

Soil Tracker for Sony CSL: As part of her second-year Industrial project, Razane, alongside her peers, worked on automating a soil weeding robot developed by collaborators. Her primary mission was to enhance the robot's functionality by automating its actions to follow the profile of the soil. Razane's contributions included investigating weight variables for automation and implementing changes in engines for improved performance.

Razane is currently part of the CONVINCE team that is leading the research on Situation Awareness and Learning in autonomous robots. Their main goal is to develop a tool for better situation understanding and enhance robots with cognitive capabilities to detect and interpret discrepancies between predictions and observations. This tool will be able to accurately identify the relevant information of the surrounding environment and feed it to the situation understanding module when an anomaly occurs. This relevant information will then be presented as a knowledge base for future reasoning.