Robot Operating System (ROS) Professors and Supervisors

Jocelyn SimmondsView profile

Associate Professor

Schloss Dagstuhl - Leibniz Center for InformaticsGermany

Jocelyn Simmonds is a faculty member in the Department of Computer Science at the University of Chile, Faculty of Physical and Mathematical Sciences. Her research spans software engineering, computing education, and gender diversity in STEM. She has published extensively in top-tier venues and collaborates with leading researchers in the field. PhD in Computer Science, University of Toronto, 2011 Extensive publication record from 2003 to 2025 Key collaborator: María Cecilia Bastarrica, Nancy Hitschfeld-Kahler, Francisco J. Gutierrez Her primary research interests include software engineering education , computational thinking for K-12 and vocational schools, and gender diversity and inclusion in computer science and software engineering. She has led initiatives to integrate computational thinking into teacher training and has studied the impact of affirmative action on female enrollment in CS/SE programs. Her recent publications reflect a strong trend toward computing education and social aspects of software engineering, particularly focusing on diversity, inclusion, and pedagogical methods. Earlier work was more technical, covering model-driven engineering, software process lines, and runtime monitoring of web services. Scientific Awards: No awards explicitly mentioned in the provided text. Jocelyn Simmonds has advised and collaborated with several students and researchers, including Constanza Diaz, Carlos Estay, Maíra Marques, and others, particularly in projects related to computational thinking and educational interventions. She has been involved in national training programs and initiatives to promote women in computing. Her work often involves empirical studies and systematic literature reviews, contributing both to technical software engineering knowledge and to the understanding of social dynamics in computing education. Laboratories and Research Teams: Collaborates with the research group at the Department of Computer Science, University of Chile. Active participant in international research collaborations, particularly in software engineering and computing education communities.

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Matthias TichyView profile

Professor

Ulm UniversityGermany

Prof. Dr. Matthias Tichy is a Full Professor and head of the Institute of Software Engineering and Programming Languages at Ulm University, Germany, since 2015. His research focuses on domain-specific languages (DSLs), model-driven engineering (MDE), self-adaptive software , and cyber-physical systems , with an emphasis on safety-critical applications and graph transformation formalisms. He employs empirical research methods to evaluate technical contributions and human factors in software engineering. University: Ulm University Role: Professor & Institute Head Research Interests span domain-specific languages for mechatronic systems, collaborative modeling , performance prediction in model transformations, and software evolution in industrial contexts. His work often bridges graph transformations and safety assurance for self-adaptive systems. Recent Publications highlight trends in model versioning (e.g., operation-based caching), DSL design (e.g., flowR for R code analysis), and automotive software testing (e.g., clustering test case specifications). He frequently collaborates with international institutions on topics like cyber-physical systems and IoT resilience . Key Collaborations include projects with Chalmers University, University of Gothenburg, and industrial partners like dSPACE GmbH. His grants and industry partnerships focus on automotive software , robotics , and self-healing systems .

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Robert HaschkeView profile

Professor

Bielefeld UniversityGermany

Dr. Robert Haschke serves as a Professor and Responsible Investigator in the Cognitive Systems and Social Interaction Group at Bielefeld University's Faculty of Engineering. He is affiliated with the Center for Cognitive Interaction Technology (CITEC) and serves on the Examination Board for the Intelligent Interactive Systems Master's program. His office is located at CITEC 2-035, and he can be reached at rhaschke@techfak.uni-bielefeld.de or +49 521 106-12122. Professor Haschke's research spans multiple domains of robotics and artificial intelligence, with particular emphasis on tactile sensing systems, robotic manipulation, and human-robot interaction. His work explores advanced methods for enabling robots to perceive their environment through touch, with applications in assistive robotics and industrial automation. He investigates how machines can learn from human interactions and adapt their behavior through reinforcement learning and sensor fusion techniques. His research bridges theoretical advances with practical implementations, focusing on transferring knowledge from simulation to real-world robotic systems. Analysis of Professor Haschke's recent publications reveals a strong trajectory toward more sophisticated tactile perception systems and their integration with language and vision for natural human-robot collaboration. His work consistently addresses the simulation-to-reality gap, developing methods for transferring control policies from virtual environments to physical robots. The research shows increasing integration of multimodal sensing (tactile, visual, linguistic) to enable more capable and adaptable robotic manipulation in unstructured environments. As an educator, Professor Haschke teaches advanced courses including Robot Manipulators (39-Inf-RM), Advanced Artificial Intelligence (39-M-Inf-AI-adv_a), Advanced Artificial Intelligence (focus) (39-M-Inf-AI-adv-foc), and Basics of Artificial Intelligence (39-M-Inf-AI-bas). His teaching reflects his research expertise, providing students with both theoretical foundations and practical skills in robotics and AI. Professor Haschke is an integral member of Bielefeld University's Cognitive Systems and Social Interaction Group within CITEC. His work contributes significantly to the university's Socio-Technical World research area, particularly in developing capabilities that enable agents (humans, robots, and AI systems) to act, communicate, and learn in complex environments. His research group focuses on creating robotic systems that can interact naturally with humans through advanced perception and adaptive control mechanisms.

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Anıl Gökhan GöktaşView profile

Researcher

Işık UniversityTurkey

Anıl Gökhan Göktaş is a Research Assistant at Işık University's Faculty of Engineering and Natural Sciences, specializing in Mechanical Engineering. His work focuses on robotics, sensor technologies, and computer-aided design. Current PhD candidate at Yıldız Technical University, Mechatronics Engineering Master's degree in Mechanical Theory and Control from Yıldız Technical University (2023) Bachelor's degree in Mechanical Engineering from Aydın Adnan Menderes University (2020) His research interests include: Sensor Technologies Computer-Aided Design Robotics Control Systems Notable work includes research on 3D printed delivery mobile robots and path planning algorithms. He is actively involved in academic projects and proceedings presentations.

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Dennis KrupkeView profile

Researcher

University of HamburgGermany

Dennis Krupke is a Researcher at the Department of Informatics, University of Hamburg, affiliated with the Human-Computer Interaction (HCI) group and the Technical Aspects of Multimodal Systems (TAMS). His work bridges robotics, virtual reality, and human-computer interaction, focusing on natural interfaces for human-robot cooperation. Education: Diploma in Informatics (2014), University of Hamburg Research Interests: Human-Robot Interaction (HRI) Bio-inspired Robotics and Sensor Systems Modular Robotics and Low-cost Prototyping Mixed Reality for Immersive Scenarios Scientific Awards: Finalist, IROS KROS Best Paper Award on Cognitive Robotics (2018) Highly Commended Paper, Industrial Robot Innovation Award (2017) CLAWAR Association Best Technical Paper Award (2015) Best Innovative Robot Award, CLAWAR (2014) Publications & Projects: Co-developed a printable modular robot with Florens Wasserfall Contributed to ROS-Unity integration for VR-based robotics Explored locomotion techniques for modular robots using reinforcement learning

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Puze LiuView profile

Researcher

University of MannheimGermany

Puze Liu is a Senior Research Scientist & Deputy Head at the Systems AI for Robot Learning (SAIROL) group within the German Research Center for Artificial Intelligence (DFKI) . He earned his Ph.D. from the Intelligent Autonomous Systems group at Technische Universität Darmstadt (TU Darmstadt) , supervised by Prof. Jan Peters . Research Interests Robotics Robot Learning Safe Reinforcement Learning Control and Optimization Human-Robot Interaction Machine Learning Recent Publications focus on safe reinforcement learning, constraint manifold theory, and real-world robotic applications, with papers accepted at ICML 2025 , RSS 2025 , CoRL 2024 , and T-RO 2024 . His work addresses safety in high-dimensional robotic tasks and real-time motion planning under constraints. Scientific Awards IROS Student Travel Award (2022) Best Paper Award Finalist at CoRL 2021 Best Entertainment and Amusement Paper Award Finalist at IROS 2021 Selected as R:SS Pioneers 2025 Collaborations include work with researchers like Jan Peters , Davide Tateo , and Kuo Zhang , focusing on robotics safety, exploration algorithms, and practical implementations for manipulation, navigation, and interaction tasks.

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Pedro RibeiroView profile

Lecturer

University of YorkUnited Kingdom

Pedro Ribeiro is a Lecturer at the Department of Computer Science , University of York. His research focuses on formal specification and verification of cyber-physical and autonomous systems, particularly using model-based approaches with domain-specific languages like RoboChart. His work addresses heterogeneous formal semantics to capture complex system behaviors, including timing, concurrency, and continuous dynamics. Recent publications highlight verification of robotic autonomous systems, safety assurance frameworks, and algebraic models for concurrency. Quantum computation Formal verification Concurrency theory Model-driven engineering He contributes to the development of tools like RoboTool and RoboStar, enabling combined proof, simulation, and testing for robotics applications.

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Thorsten BergerView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Thorsten Berger is a Professor and Head of the Chair of Software Engineering at Ruhr University Bochum, Germany. His office is located at MC 4.101 on the RUB campus, with contact details including phone (+49 (0) 234 32 25975) and email (thorsten.berger@rub.de). He's an active researcher with extensive service in the software engineering community, serving on program committees for major conferences including ICSE, FSE, ASE, and SPLC. Professor Berger's research primarily focuses on software engineering with specialization in variability management, software product lines, and robotics software engineering. His work bridges theoretical foundations with practical applications, particularly in behavior trees for robotic systems, configuration management, and domain-specific language engineering. His interdisciplinary approach connects software engineering with control theory and machine learning applications. Analysis of his recent publications reveals a strong trend toward robotics software engineering, with increasing focus on behavior trees, test-case specification, and runtime verification for robotic systems. His work also shows growing interest in machine learning integration with traditional software engineering practices, particularly in model integration and asset management for ML-enabled systems. The research demonstrates consistent evolution from foundational work in variability management toward more applied domains. His scientific achievements have been recognized with numerous awards: Multiple Most Influential Paper Awards (SLE 2024, VaMoS 2023, VaMoS 2020) Wallenberg Academy Fellowship VR Starting Grant from Swedish Research Council (2016) Best Paper Awards at Modularity (2015) and CSMR (2013) Distinguished Reviewer Awards from ASE, ICSE, and SPLC conferences ERC Starting Grant finalist (2019, 2020) Professor Berger has secured substantial research funding as Principal Investigator for multiple projects including Novel Techniques for Data-Driven Root-Cause Analysis and Variability Management (Volkswagen Infotainment), Properties and Verification Techniques for Behavior Trees (Phoenix Contact Foundation), and PrivacyE2E framework for AI-enabled systems (Federal Ministry of Education and Research). His Wallenberg Academy Fellowship and VR Starting Grant demonstrate his capacity to attract competitive early-career funding. He leads the Virtual Platform project funded by the Swedish Research Council and participates in EU-funded initiatives like CO4ROBOTS. As Head of the Chair of Software Engineering at Ruhr University Bochum, he leads a research group focused on advanced software engineering techniques with particular emphasis on variability-intensive systems. His team actively participates in international research collaborations including the Wallenberg Autonomous Systems Program (WASP) and has organized significant events like the Dagstuhl seminar 19191 on 'Software Evolution in Time and Space: Unifying Version and Variability Management.'

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Edmund R HuntView profile

Senior Lecturer

University of CumbriaUnited Kingdom

Dr. Edmund R Hunt is a Senior Lecturer in Robotics at the University of Bristol, working within the School of Engineering Mathematics and Technology and the Department of Engineering Mathematics. Since 2021, he has held a prestigious Royal Academy of Engineering Research Fellowship. His research group, the Hunt Lab, focuses on deploying robot swarms into real-world environments for practical applications, particularly in environmental monitoring. Education: PhD in Complexity Sciences (2012-2016), University of Bristol MPhil in Economics (2007-2009), University of Oxford BSc in Physics with Theoretical Physics (2004-2007), Imperial College London Dr. Hunt's research bridges collective animal behavior and swarm robotics, developing bioinspired approaches for real-world robot deployments. His work emphasizes smaller-scale swarms (4-10 robots) using sophisticated ROS-based systems that can navigate complex environments. Key research themes include multi-robot patrolling, trust in human-robot teams, behavioral plasticity in swarms, and environmental monitoring applications. His group conducts experiments both indoors on campus and in outdoor locations including Bristol's harbourside and Fenswood Farm. Analysis of Dr. Hunt's recent publications reveals a strong focus on practical swarm robotics applications, particularly in environmental monitoring and security. His work increasingly integrates human-robot teaming concepts, trust modeling, and bioinspired algorithms. The research shows progression from theoretical swarm concepts toward field-deployable systems with real-world applications in atmospheric measurement, biodiversity monitoring, and security patrolling. Scientific Awards: British Science Festival 2021 Award Lecture Winner for Digital Innovation 3rd Place in EPSRC Photography Competition 2018 EPSRC Doctoral Prize Fellow (2017) UK Intelligence Community Postdoctoral Fellow (2019-2021) Royal Academy of Engineering Research Fellow (2021-2026) Dr. Hunt actively supervises multiple PhD students working on diverse aspects of swarm robotics, including multi-robot patrolling, atmospheric electricity measurement, and behavioral plasticity. His current research is supported by significant grants including the £1.2M EPSRC-funded 'Satisficing Trust in Human-Robot Teams' project (2023-2026) and the T-B PHASE Prosperity Partnership with Thales. He previously held research fellowships from EPSRC and UK Intelligence Community funding. The Hunt Lab operates across multiple Bristol facilities including the Bristol Robotics Laboratory on UWE campus, field testing at Fenswood Farm in Long Ashton, and day-to-day operations on the Clifton campus. The lab works with various robot platforms including Leo Rovers for field experiments and has previously used Kilobots for conceptual swarm research. Current projects explore heterogeneous swarms incorporating different robot types for specialized environmental monitoring tasks.

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Pengcheng LiuView profile

Associate Professor

National Research Institute for Mathematics and Computer ScienceNetherlands

Pengcheng Liu is an Associate Professor in the Department of Computer Science at the University of York, holding this position since January 2020. He maintains active memberships in IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS), and the International Federation of Automatic Control (IFAC), while serving on the IEEE Technical Committee for Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. His research spans robotics, machine learning, automatic control, and optimization, with specialization in humanoid robotics, rehabilitation systems, agricultural applications, and human-computer interaction. Key focus areas include developing lightweight neural networks for embedded agricultural systems, bionic-companionship frameworks for service robots, EMG-controlled rehabilitation devices, and precise control of robotic manipulators using ROS/Gazebo. His work consistently bridges theoretical control systems with practical implementations in healthcare and precision agriculture. Analysis of his publication trends reveals strong emphasis on applying machine learning to real-world robotics challenges, particularly in resource-constrained environments (e.g., agricultural robotics with efficient neural networks) and human-centered applications (e.g., rehabilitation gloves and brain-computer interfaces). Recent work demonstrates increasing integration of computer vision with control systems for autonomous operation. His notable scientific awards include: Global Peer Review Awards from Web of Science (2019) Outstanding Contribution Awards from Elsevier (2017) Dr. Liu has secured and managed research funding through major programs including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, and NSFC. He serves as a regular reviewer for EPSRC, NIHR, and NSFC grant panels while reviewing for over 30 flagship journals and conferences in robotics, AI, and control systems. His editorial roles include Associate Editor for IEEE Access and PeerJ Computer Science, where he has edited 17 publications. Though specific lab affiliations aren't detailed, his research in agricultural robotics, rehabilitation systems, and humanoid platforms suggests active collaboration with York's robotics and AI research groups, particularly in developing practical implementations of control algorithms and machine learning models for real-world deployment.

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Emmanuel GrolleauView profile

Professor

National Graduate School of Mechanics and AerotechnicsFrance

Emmanuel Grolleau is a Full Professor at ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechique) specializing in real-time systems. He is affiliated with the LIAS laboratory (Laboratoire d'Ingénierie des Applications de la Sensorique) where he leads the Real Time Team. His work bridges theoretical scheduling principles with practical embedded system implementations across multiple domains. Professor Grolleau's primary research interests include: Real-Time Scheduling: uniprocessor, multiprocessor, and distributed scheduling with practical considerations like transactions and precedence constraints Model-Based Systems Engineering (MBSE): developing bridges between UML-MARTE and AADL to real-time scheduling tools Unmanned Aerial Vehicles (UAVs): autopilot architecture design and optimization Energy Systems: co-heading the LabCom ANR Laboratoire d'Insertion des Énergies Nouvelles et d'Optimisation des Réseaux (LIENOR) His publication record demonstrates a clear progression from fundamental scheduling theory to applied work spanning avionics, drone technology, and power systems. Recent work shows strong focus on UAV autopilot architectures, model-based frameworks for real-time systems, and energy management in power distribution networks. Professor Grolleau serves on multiple prestigious program committees including Real-Time Networks & Systems (RTNS) since 2012, ACM/SIGAPP Symposium On Applied Computing (SAC) since 2015, DETECT since 2018, and DroneSE in 2023. He has led significant research projects such as PIA CORAC Panda and FUI WARUNA, which developed the Time4Sys pivot meta-model to connect theoretical scheduling with practical implementation. His collaborative work extends across multiple institutions and industries, with publications spanning real-time scheduling theory, UAV systems, energy management, and avionic architectures. The consistent thread through his work is the practical application of real-time scheduling principles to solve complex engineering problems in safety-critical systems.

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Reiner MarchthalerView profile

Professor

Esslingen University of Applied SciencesGermany

Prof. Reiner Marchthaler is a Professor at Esslingen University of Applied Sciences within the Faculty of Computer Science and Information Technology. He serves as Deputy Director of the Institute for Intelligent Systems (IIS), Scientific Director of the Green IT 2026 Conference, and Liaison Lecturer for the Friedrich Ebert Foundation. His academic leadership spans autonomous systems research and educational initiatives in embedded technologies. His research centers on Embedded Systems and Sensor Data Fusion, with pioneering work on Kalman filters for autonomous systems. He maintains the authoritative resource kalman-filter.de and has developed real-time capable SLAM algorithms, camera-based reference systems, and parking space detection frameworks. His expertise extends to entropy-based safety evaluation in autonomous driving and semantic segmentation using mixed real/synthetic data. Analysis of his 2020-2025 publications reveals dominant trends in autonomous driving systems, emphasizing real-time sensor fusion, deep learning for perception, and safety validation. Key subfields include adaptive Kalman filtering (ROSE-Filter), landmark-based navigation, neural network training with synthetic data, and maximum entropy safety frameworks. His work bridges theoretical innovation with automotive applications, particularly in model vehicle testing environments. Prof. Marchthaler leads research at the Institute for Intelligent Systems, directing the Green IT 2026 initiative and advising the Friedrich Ebert Foundation. His team develops ROS-based validation environments for autonomous algorithms and maintains the Kalman filter knowledge portal. Current projects focus on connected traffic systems using conventional infrastructure landmarks and entropy-optimized safety protocols for production vehicles.

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