Musa Jouaneh is a Professor in the Mechanical, Industrial and Systems Engineering department at the University of Rhode Island 's College of Engineering . His research spans Robotics, Automation, Mechatronics , and Motion Control systems, with recent work focusing on robotic rehabilitation platforms, fastener extraction, and neural network applications in disassembly processes. Education: Ph.D., Mechanical Engineering, University of California at Berkeley (1989) M.Eng., Mechanical Engineering, University of California at Berkeley (1986) B.S., Mechanical Engineering, University of Louisiana, Lafayette (1984) Research Trends in Jouaneh's recent publications emphasize robotic rehabilitation using magnetic actuation, automated fastener detection via neural networks, and trajectory optimization for servo motor systems. His work bridges mechatronic design with industrial automation , particularly in disassembly and assembly applications. Grants include projects like "Cobots for Outfitting of Hangers" (ONR, 2023) and "Device for Proprioception Training" (RI Commerce, 2024). He leads the Mechatronics Lab and Intelligent Control and Robotics Laboratory , focusing on practical automation solutions.
Biyun Xie is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Kentucky's Stanley and Karen Pigman College of Engineering. Her research focuses on kinematically redundant robots, fault-tolerant robotics, and human-robot interaction, with applications in dangerous environments and collaborative systems. Education : Ph.D. in Electrical Engineering from Colorado State University (2019), Ph.D. in Mechanical Engineering from Beijing University of Technology (2015), and B.S. in Mechanical Engineering and Automation from Beijing University of Technology (2009). Research Interests : Kinematically Redundant Robots Fault Tolerant Robots Collaborative Robots Human-Robot Interaction Publications (2025–2023) highlight advancements in real-time fault-tolerant motion planning for redundant robots, neural network-based motor health monitoring, human-like motion algorithms, and collision-free trajectory optimization. These works intersect robotics, artificial intelligence, and mechanical/electrical engineering. Contact : Biyun.Xie@uky.edu | 859-562-2557
Overview Dr. Catherine Prentice is a Professor of Marketing and Head of the Marketing Discipline at the University of Southern Queensland, Australia. She also serves as Director of the Asia Pacific Association for Gambling Studies (APAGS) and holds editorial roles across multiple top-tier journals including Journal of Business Research and International Journal of Contemporary Hospitality Management . Her research focuses on artificial intelligence, emotional intelligence, service innovation, consumer behavior, and gambling studies, with significant contributions to the tourism and hospitality sectors. Education MBA, Lincoln University (2001) PhD in Marketing, Victoria University (2009) Research Interests Dr. Prentice’s work bridges theoretical and applied research, emphasizing the practical implications of her findings. Key areas include: - The role of AI in enhancing customer engagement and loyalty - Emotional intelligence in service encounters and leadership - Consumer psychology in tourism and hospitality contexts - Strategic marketing in the gambling and gaming industries - Sustainability and innovation in service delivery Publications & Impact Her over 100 peer-reviewed articles span journals like Journal of Hospitality & Tourism Research and Tourism Management , with a focus on empirical investigations of service quality, customer loyalty, and organizational performance. Recent work explores the intersection of AI and human service interactions. Leadership & Service In addition to her academic roles, Dr. Prentice contributes to industry through: - Editorial board memberships across 12+ Q1 journals - Leadership in professional associations like NAGS and ANZMAC - Consultancy in business strategy and marketing for corporations and governments
Professor Lyudmila Mihaylova is a distinguished academic at the University of Sheffield's School of Electrical and Electronic Engineering, where she holds the position of Professor of Signal Processing and Control. She has established herself as a leading researcher in the fields of signal processing, Bayesian methods, and autonomous systems, with significant contributions to particle filtering techniques for intelligent transportation systems. Her work bridges theoretical developments with practical applications across multiple domains including transportation, healthcare, and industrial automation. Prof. Mihaylova's research interests center on nonlinear filtering, sequential Monte Carlo methods, statistical signal processing, and sensor data fusion. Her work spans both theoretical advancements and practical implementations, with particular focus on high-dimensional problems including vehicular traffic flow estimation, image processing, and localization in sensor networks. She has extensive experience with various image modalities such as optical, thermal, LIDAR, SAR, and hyperspectral imaging. Her group actively develops novel methods for autonomous intelligent systems focusing on sensing, tracking, decision making, and machine learning applications. Analysis of Prof. Mihaylova's recent publications reveals a strong trend toward uncertainty quantification in machine learning models, particularly for safety-critical applications. Her work increasingly integrates traditional signal processing techniques with modern deep learning approaches, with applications spanning sewer inspection robotics, medical diagnostics (particularly sleep apnea detection), UAV swarm tracking, industrial manufacturing, and autonomous vehicle systems. A significant portion of her recent research focuses on developing robust methods that can handle incomplete or outlier-corrupted data while providing reliable uncertainty estimates. Among her notable professional achievements: President of the International Society of Information Fusion (ISIF) Senior member of the IEEE Signal Processing Society Associate Editor for IEEE Transactions on Aerospace and Electronic Systems Associate Editor for Elsevier Signal Processing Journal Prof. Mihaylova has successfully mentored numerous PhD students and postdoctoral researchers, many of whom have gone on to prominent academic and industry positions. Her research has been supported by major funding bodies including EPSRC, EU, MOD/DSTL, and industry partners, with recent projects including 'Protecting Environments with UAV Swarms' (InnovateUK, 2022-2024), 'ShiRAS: Towards Safe and Reliable Autonomy in Sensor Driven Systems' (NSF-EPSRC, 2019-2023), and 'Confident safety integration for Cobots' (Lloyd's Register Foundation, 2019-2020). Her research group follows a collaborative approach with the philosophy 'We share knowledge, we grow.' Prof. Mihaylova maintains active research collaborations with institutions worldwide and has held previous academic positions at Lancaster University (2006-2013) and University of Bristol (2004-2006), along with research visiting positions at the University of Ghent, Katholic University of Leuven, and the Bulgarian Academy of Sciences.
David Daney is a Senior Researcher (Directeur de recherche) at Inria and HDR-qualified academic, currently serving as Head of Science for the Inria Center at the University of Bordeaux since July 2024. He is the team leader of the Auctus research group, focusing on robotics, cobotics, and human-robot interaction. He is affiliated with Inria and the École Nationale Supérieure de Cognitique (ENSC) at the University of Bordeaux, within the College of Engineering and the Department of Robotics. His research interests include Robotics, Cobotics, Human-Robot Interaction, Human Posture Analysis, Cable-driven Robots, Parameters Identification, Calibration, Interval Analysis, and Haptic Guidance. His work bridges theoretical robotics with industrial applications, particularly in aerospace, automotive, and sustainable agriculture. He has led and participated in numerous industrial collaborations with Airbus, Stellantis, Solvay, AKKA, and Farm3. His recent publications (2023–2025) demonstrate a strong focus on human-robot physical interaction, including real-time capacity estimation (Pycapacity), haptic guidance, model predictive control for dynamic environments, and musculoskeletal modeling for collaborative robotics. These works appear in top-tier journals such as IEEE Transactions on Robotics, Journal of Biomechanical Engineering, and Robotics and Autonomous Systems. HDR (Habilitation à Diriger des Recherches) Principal Investigator of ANR Pacbot Head of Science for Inria Center at University of Bordeaux Erdös number = 3 David Daney supervises multiple PhD students, including Alicia Barsacq, Ahmed-Manaf Dahmani, and Alexis Boulay. He has been principal investigator in several research projects such as LiChIE and ANR Pacbot, focusing on satellite production and human-robot collaboration. He also leads the SHAARE associate team with KAIST’s IRiS lab, advancing shared haptic control. His team develops tools for teleoperation, ergonomic analysis, and robot calibration, with applications in industrial and assistive robotics. He leads the Auctus team at Inria, which develops control and analysis techniques for human-robot physical interaction. The team collaborates with KAIST (SHAARE), ONERA, Pprime Institute, and industrial partners. The MOVER project studies human motor variability for ergonomics, and the Farm3 collaboration explores teleoperated vertical farming robotics.
Bradley Schmerl serves as a Principal Systems Scientist in the Software and Societal Systems Department (S3D) within Carnegie Mellon University's School of Computer Science. His research advances software engineering practices for modern challenges in distributed heterogeneous systems, self-adaptation, and cyber-physical integration. He leads the ABLE research group and actively mentors students in the Masters in Software Engineering program while teaching core courses like Software Architecture and Software Engineering Practicum. Dr. Schmerl's work addresses critical challenges in composing continuously evolving software systems, including components from untrusted third parties and on-the-fly recomposition for environmental changes. His research develops reusable, analyzable tools for software composition with emphasis on model-based adaptation, uncertainty management, and cross-language integration. Key projects include Rainbow for runtime architecture reflection, Acme for formal architectural foundations, and Cyber-physical Systems research linking software models with physical dynamics. Analysis of his 2023-2025 publications reveals intensifying focus on robotics software architecture (particularly ROS-based systems), explainable AI for architectural tradeoff analysis, and configuration management in adaptive systems. Trends show growing integration of machine learning for auto-tuning, empirical studies of misconfigurations, and dimensionality reduction techniques for visualizing design spaces—consistently bridging theoretical rigor with practical tool development for real-world applications. Scientific Awards: No specific awards were documented in the source materials. Dr. Schmerl serves as Practice Area Lead and mentor in CMU's Masters in Software Engineering program, guiding client projects including Rainbow UI for self-adaptive framework interfaces, CoBot UI for telepresence robots, and Educational Telepresence Tasking Language development. His research receives support through ABLE group projects funded by grants targeting software architecture foundations, adaptation mechanisms, and cyber-physical system validation. As a core member of the ABLE research group, he directs investigations into architecture-based self-adaptation with active projects spanning Rainbow (runtime architecture models for dynamic adaptation), Acme (formal architectural styles and tools), and Cyber-physical Systems (software-physical model integration). The group also maintains legacy work in End-User Architecting, Architecture Evolution, and service-oriented platforms for intelligence analysis through SORASCS.
Dr. Uwe Grünefeld is a Visiting Professor at the Faculty of Computer Science , Institute for Computer Science and Business Information Systems (ICB) of the University of Duisburg-Essen. He has been actively contributing to Human-Computer Interaction research through multiple publications in 2025-2022 focusing on Virtual Reality , Augmented Reality , and Robotics . Research Interests span across immersive technology applications for health behavior change (situated artifacts, weight visualization mirrors), haptic feedback systems (EMS for weight perception, vibrotactile directional cues), and behavioral biometrics (hand tracking identification, gaze-based user recognition). His work addresses cross-reality system design , collaborative robotics , and human-in-the-loop simulation methodologies . Key Publications demonstrate significant contributions to VR/AR user engagement, with particular focus on Physical activity promotion through situated artifacts Advanced haptic feedback techniques for immersive environments Behavioral biometric identification systems Robot motion intent communication Cross-reality transition visualization His research often employs mixed-method approaches combining technical implementations with user studies involving quantitative and qualitative data collection.
Prof. Michele Germani is a Full Professor at the Polytechnic University of Marche, Department of Industrial Engineering and Mathematical Sciences. His research focuses on ergonomics, sustainability, and human-centered design, with particular emphasis on industrial automation, wearable technologies, and circular economy principles. He leads projects on ergonomic risk assessment, environmental impact modeling, and smart manufacturing systems. Academic Background: Holds a position in the Faculty of Engineering, contributing to both teaching and research. His work integrates machine learning, sensor-based systems, and virtual reality to address challenges in manufacturing, healthcare, and sustainable design. Research Interests: Prof. Germani explores topics such as design for disassembly, eco-design tools, and the application of advanced technologies (e.g., exoskeletons, cobots) to enhance workplace safety and efficiency. His studies often bridge engineering and environmental science, aiming to reduce carbon footprints through innovative design methodologies. Key Projects: Development of decision support systems for fall risk detection, sensor-based ergonomic evaluation tools, and frameworks for circular economy implementation. He also investigates the impact of Industry 4.0 technologies on workforce dynamics and operator training via mixed reality simulations. Grants & Collaborations: Engaged in interdisciplinary collaborations focusing on sustainable manufacturing, healthcare technology, and smart systems. His research has led to tools like Durabot for durability analysis and Greenbuild for green building design. Labs & Teams: Oversees labs developing eco-design strategies, human-robot collaboration systems, and ergonomic assessment protocols, with a focus on real-world industrial applications.
Fahad Khan is a Researcher at Cranfield University's Centre for Robotics and Assembly, part of the Aerospace department. He holds an MSc in Robotics Engineering (Cranfield University) and a B.Tech in Mechatronics (NMIMS University). Currently employed full-time as a Research Assistant and part-time PhD candidate, his work focuses on intelligent robotics systems, human-robot collaboration (HRC), and adaptive automation technologies. Education: MSc Robotics Engineering, Cranfield University (UK) B.Tech Mechatronics Engineering, NMIMS University (India) Current Projects: Smart Cobotics (ISCF) project: Developing adaptive HRC systems using physiological and contextual data. EPSRC-funded research on facial emotion recognition for manufacturing robots. Research interests include IoT integration, motion control, and machine learning applications in robotics. He has published on HRC gesture design, emotion recognition systems, and ROS 2-based industrial frameworks. Awards: None explicitly listed. Grants: Supported by Engineering and Physical Sciences Research Council (EPSRC) through the Made Smarter Innovation project. Technical expertise spans ROS, OpenCV, MATLAB, and PLC programming. His LinkedIn and GitHub profiles showcase contributions to robotic systems and machine learning projects.
Pedro Roque is a Postdoctoral Researcher at KTH Royal Institute of Technology in Stockholm, affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP) and associated with the Division of Decision and Control Systems (DCS). He obtained his Ph.D. in 2024 from the same division under the supervision of Prof. Dimos Dimarogonas, Prof. Mikael Johansson, and Prof. Jana Tumova. His research focuses on practically applicable theoretical results in robotics and control, with emphasis on space and aerial systems. Dr. Roque is particularly interested in developing algorithms that directly contribute to system performance and enhanced capabilities. He currently leads the setup of a Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project. He is an advocate for open-source software and hardware, contributing to NASA Astrobee and PX4 projects, with his research tested on the International Space Station and indoor flight arenas. Dr. Roque's work demonstrates a clear progression from theoretical foundations to practical implementation in space environments. His recent publications show an increasing focus on multi-agent coordination in microgravity, with significant contributions to model predictive control for space robotics applications. The research spans from fundamental control theory to complete system implementation, reflecting his commitment to bridging theory and practice. ICRA 2022 Outstanding Coordination Award for work on decentralized model predictive control for collaborative UAV bar transportation Dr. Roque actively mentors Master's students in Space Robotics, Control, and Vision, with supervision details available on his personal website. He has collaborated extensively with NASA Astrobee and PX4 projects, and his DISCOWER project involves collaboration with 3 Ph.D. students, 2 Master's students, 6 Professors, and one Post-doc. He also completed a 4-month internship at JPL within the Maritime and Multi-Agent Systems group. He leads the Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project, which has already demonstrated capabilities to Digital Futures, SAAB AB, SAAB Inc., and Purdue scholars. The laboratory focuses on weightless robotics, collaborative robotics (Space Cobot), and exploration robotics (MoonHopper), with practical testing on the International Space Station.
Prof. Dr. Sarah Dégallier Rochat is Head of the strategic thematic field 'Humane Digital Transformation' at Bern University of Applied Sciences (BFH). She holds a joint appointment as Professor at the School of Engineering and Computer Science and serves as co-leader of the Computer Perception and Virtual Reality Lab (cpvrLab) within the Institute for Human-Centered Engineering. Her educational background includes: Ph.D. in Robotics from École Polytechnique Fédérale de Lausanne (EPFL) Master's in Mathematics from EPFL Teaching Diploma in Mathematics from Haute École Pédagogique de Lausanne Psychology studies at University of Lausanne Her research focuses on human-centered technological development with emphasis on: Designing inclusive human-machine interfaces through participatory approaches Developing upskilling strategies for industrial workforce adaptation Examining how techno-narratives shape societal perceptions of technology Creating collaborative robotic systems for agile manufacturing (Cobotics) Exploring mixed reality interfaces for worker augmentation Her publications demonstrate strong interdisciplinary focus on robotics and human-centered AI, with recent works exploring human augmentation in industry, ethical AI implementation, and participatory robot programming. The trajectory shows increasing emphasis on socio-technical systems and workforce empowerment. Significant awards include: Industry 4.0 Shapers Award (2019) CHIRA Best Paper Award (2023) She leads multiple research projects funded by Innosuisse, SNF, and EU programs, including: CODIMAN (Cobotics and workplace humanization) Agile Robotics for High-Mix Low-Volume Production Upskill at Work (digital literacy initiatives) Augmented workers with mixed reality interfaces As founder of Auto-Mate Robotics, she develops flexible robotic cells for industrial applications. She co-leads the Computer Perception and VR Lab and serves on advisory boards including the Swiss Cobotics Competence Center and EUA Task Force on AI.
Dr. Mohamed Gharib is an Instructional Associate Professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University's College of Engineering. He also serves as Program Coordinator for Multidisciplinary Engineering Technology and holds affiliated faculty status in Multidisciplinary Engineering. His roles include teaching, research leadership, and academic program development. Educational Background: Ph.D., Mechanical Engineering, Southern Methodist University (2011) M.S., Aerospace Engineering, Cairo University (2007) B.S., Aerospace Engineering, Cairo University (2002) Research Interests: Dr. Gharib focuses on advanced engineering systems and education innovation. His technical work spans vibration control , robotics systems design , and impact mechanics , with notable contributions to drill string vibration suppression and novel damping technologies. In education, he pioneers STEM outreach programs and curriculum development, including initiatives like the Awesome STEM Lab and e-STEM programs . His COBOTICS Lab integrates robotics research, undergraduate training, and community engagement. Research Impact: Recent work addresses dexterous robotics (via NSF's HAND ERC), adaptive control algorithms for drilling systems, and advanced composite coatings for tribological applications. His publications emphasize real-world applications in oil well operations, structural acoustics, and educational technology. Awards: Francisco José de Caldas Award for Sustainable Excellence (2021) Excellence in STEM Implementation Award (ASME, 2020) Outstanding Graduate Student Awards (2010) Labs & Programs: Director of the COBOTICS Lab , which develops robotic systems, control technologies, and STEM education tools. Active in multidisciplinary projects like the NSF-funded Human Augmentation via Dexterity (HAND ERC) collaboration.
Christine Jeoffrion is a Professor of Occupational Psychology at Université Grenoble Alpes, where she directs the Doctoral School of Human Sciences and leads the "Risk and Change Accompaniment" axis at the Inter-university Psychology Laboratory. With extensive international engagement through organizations like EAOHP and IAAP, her work bridges occupational health, organizational psychology, and psychosocial risk prevention. Key affiliations: Université Grenoble Alpes, Université de Tours, INRS, CNAM Leadership roles: Doctoral School Director (2024+), CNU member (2024-2028), HCERES expert (2023+) Her research focuses on workplace psychological and physical health, examining organizational factors affecting well-being through 15+ funded projects like ANR PacBot (€670k) and CDP BOOT (€850k). Current PhD students explore virtual reality interventions, prison worker coping mechanisms, and organizational transformations for meaningful work. Recent publications analyze cobot impacts on work quality, telework dynamics, and bullying consequences. She has co-edited special issues for International Journal of Environmental Research and Public Health and Psychologie du travail et des Organisations . Her 2023 Légion d'honneur recognition underscores her field leadership. As a thesis advisor, she has directed 34+ doctoral candidates across France and Gabon, including works on intercultural competence, healthcare worker stress, and managerial innovation. She contributes to European research networks through symposium organization and journal editorial boards.
Dr. Eike Schneiders is a Lecturer at the School of Electronics and Computer Science, University of Southampton. He holds a PhD in Computer Science from Aalborg University and is a recipient of the UKRI Trustworthy Autonomous Systems Hub Early Career Researcher Award. His research focuses on autonomous and AI-infused systems, investigating how to ensure their trustworthiness and responsible interaction with humans and other agents through interdisciplinary collaborations across art, law, and medicine. His recent work explores the societal impact of Generative AI, particularly examining its influence on legal services accessibility for non-experts through the REGALS project (Principal Investigator) and its effects on creative communities via the ART-I project (Co-Investigator). Dr. Schneiders emphasizes public engagement to enhance AI literacy and employs both qualitative and quantitative methods to study human-computer interaction and ethical implications. Dr. Schneiders teaches courses including COMP6251 (Web and Cloud Application Development), ELEC6259 (Research Methods and Project Preparation), and ELEC6200 (Group Design Project). His pedagogical approach integrates foundational technical skills with critical research methodologies. He has led several interdisciplinary projects including ARTificial Intelligence: Show Me a Story about AI (ART-I) and Responsible Employment of Generative AI for Legal Services (REGALS), and contributes to the Agents, Interaction and Complexity research group. His Cat Royale project received the 2024 Webby Award for Best Integrated Experience. Honors include the Best Paper Award at ACM CHI 2024, multiple Honourable Mentions at CHI and TAS Symposiums, and membership in the Foundation for Science and Technology's Future Leaders Programme.
Teresa Vidal-Calleja is an Associate Professor and Research Director at the Robotics Institute, University of Technology Sydney (UTS). She holds a Deputy Head of School (Research) role in the School of Mechanical and Mechatronic Engineering. Her research focuses on robotics perception, alternative sensing, inertial fusion, SLAM, and applications in manufacturing, agriculture, mining, and construction. Education: B.Sc. Mechanical Engineering (UNAM, 2000), M.Sc. Electrical Engineering (CINVESTAV-IPN, 2002), Ph.D. Automatic Control (Polytechnic University of Catalonia, 2007). Postdoctoral Experience: LAAS-CNRS (France), Australian Centre for Field Robotics (Sydney). Research Interests: Teresa’s work spans robotics perception, sensor fusion, autonomous navigation, and collaborative robotics. She leads projects on next-gen infrastructure robotics (ARC Discovery Grant) and is co-lead of the Australian Cobot Centre. Her innovations target hazardous environments, infrastructure maintenance, and human-robot collaboration. Funded Research: Includes grants for robotic sensors, satellite docking systems, and multi-robot collaboration. Recent projects involve Navantia, the NSW Space Research Network, and industry partnerships. Professional Roles: IEEE Senior Member, Treasurer of the Australian Robotics and Automation Association, and Associate Editor for IEEE Transactions on Robotics and other journals. She chairs conferences like the Australasian Conference on Robotics and Automation. Labs/Teams: UTS Robotics Institute, collaborating with global institutions like ETH Zürich and DLR. Her work integrates robotics with industries such as agriculture and construction, emphasizing sustainability and safety.
