Andrés José Piñón Pazos is a researcher at the Department of Industrial Engineering within the Ferrol Polytechnic School of Engineering at University of A Coruña (UDC). His work focuses on intelligent and advanced control, optimization and modeling of systems, and virtual and intelligent instrumentation. He teaches both required and optional courses in Industrial and Automatic Electronic Engineering, Industrial Informatics and Robotics, and Mechanical Engineering programs. Research interests include: Intelligent control systems development Industrial process optimization Virtual instrumentation design Smart monitoring systems Automation solutions Energy efficiency improvements Scientific contributions: Registered software (2014) Multiple patents (2013, 2008, 2005) Over 15 research articles International conference publications Key grants and contracts include projects with: Spanish Foundation for Science and Technology (FECYT) Instituto Tecnológico de Castilla y León (ITCL) Galician Department of Education Ministry of Science and Innovation Navantia shipyard International collaborations
Orion T. Taylor is a Visiting Assistant Professor of Mechanical Engineering at Olin College of Engineering. He holds a B.S. in Electrical and Computer Engineering from Olin College and advanced degrees in Electrical Engineering & Computer Science and Mechanical Engineering from MIT, culminating in a Ph.D. in Mechanical Engineering. B.S. Electrical and Computer Engineering, Olin College of Engineering M.S. Electrical Engineering and Computer Science, MIT M.S. Mechanical Engineering, MIT PhD Mechanical Engineering, MIT His research focuses on enhancing robotic dexterity through contact configuration regulation and dynamic manipulation systems. He contributes to applied mathematics and engineering education by teaching Quantitative Engineering Analysis, Applied Math for Engineers, and Dynamics courses. Notably, he received the Outstanding Manipulation Paper Award from the IEEE International Conference on Robotics and Automation (ICRA) in 2022 for his work on manipulation of unknown objects. His publications highlight advancements in contact regulation strategies and optimal motion planning. Orion actively engages in creating numerical simulations, visualizations, and challenging kinematics problems. He also anonymously shares engineering expertise on Reddit, supporting students beyond the classroom.
Yildirim Hurmuzlu holds the dual distinguished professorships of Altshuler Distinguished Professor and University Distinguished Professor within the Department of Mechanical Engineering at Southern Methodist University. His primary affiliation is explicitly stated with his office located in Embrey 301C, confirming active faculty status in mechanical engineering research and instruction. His research interests focus on Robotics, Control Systems, and Dynamics and Vibrations, particularly examining rigid body collision mechanics, bipedal locomotion stability, and magnetic actuation for micro-scale robotics. Key specialties include impact dynamics in kinematic chains, nonlinear control of inverted pendulum systems, haptic interface design for medical applications, and aerospace robotics for space debris mitigation. This work bridges theoretical dynamics with practical implementations in robotic inspection systems and human digital twin technologies. Recent publications (2020-2025) reveal a strategic shift toward magnetic millirobotics for industrial inspection and modular assembly, while maintaining foundational work in impact dynamics. Aerospace applications now dominate new research strands, especially human digital twins for manufacturing quality assurance and tethered satellite control for space debris removal. Medical haptics remains a consistent theme with continued development of virtual palpation systems. Awards include: Altshuler Distinguished Professor University Distinguished Professor No student advising records or grant funding details were provided in the source material. His departmental affiliation confirms leadership in robotics and dynamics research without explicit mention of labs or teams, though his work implies substantial involvement in experimental robotic systems development through repeated references to design, control, and implementation.
Sumeet S. Aphale is a Professor and Academic Line Manager at the School of Engineering, University of Aberdeen, where he also leads the Electrical and Electronic Systems research group. He holds a Personal Chair and is actively involved in research, teaching, and academic leadership. He is the Programme Leader for the MSc in Robotics & Artificial Intelligence and MSc in Industrial Robotics. Education: BEng Electrical Engineering, University of Pune, India (1999), First Class with Distinction MS Electrical Engineering (Robotics and Control), University of Wyoming, USA (2003) PhD Electrical Engineering (Robotics and Control), University of Wyoming, USA (2005) His research focuses on control systems, mechatronics, robotics, nanopositioning, soft robotics, and vibration control. He leads the Artificial Intelligence, Robotics and Mechatronic Systems (ARMS) group, emphasizing practical, implementable solutions for complex engineering problems. His work spans applications in MEMS, drill-strings, biomedical systems, and renewable energy. The 15 most recent publications reflect a strong trend in advanced control strategies, including fractional-order, sliding-mode, and AI-based control, applied to nanopositioning, soft actuators, and industrial systems. Key themes include precision enhancement, dynamic modeling, and real-time performance optimization. Scientific Awards: Principal's Excellence Award for Outstanding Postgraduate Research Supervisor (2023) Best Paper Award, AsiaSim (2017) Best Paper Award Finalist, Advanced Intelligent Mechatronics (2008) Tau Beta Pi - Engineering Honors Society (2003) Top 5 UG GPA (1999) Dr. Aphale has supervised numerous PhD students to completion and currently mentors several doctoral candidates in areas such as soft robotics, motor optimization, and unconventional control. He has secured over £2.7M in research funding from EPSRC, SFC, Innovate UK, and international sources, and has led industrial consultancies with BP, Aramco, Aker, and LeapAI. He is actively involved in knowledge exchange through KTP projects and industrial collaborations. He teaches courses in signals, systems, and advanced control engineering and serves as a personal tutor and examination officer. He leads the ARMS research group and collaborates with institutions in Spain, China, India, France, Australia, and the USA. His editorial roles include Associate Editor for IEEE Control Systems Letters and Frontiers in Mechanical Engineering.
Francisco Javier Cuadrado Aranda is a faculty member in the Department of Naval and Industrial Engineering at the Ferrol Engineering Polytechnic School, University of A Coruña (UDC), Spain. His academic work spans teaching, research, and industrial collaboration, with a focus on mechanical engineering, multibody dynamics, and biomechanics. His research interests include: Multibody System Dynamics Computational Kinematics and Dynamics Biomechanics of Human Motion Gait Analysis and Orthosis Design Machine and Maintenance Engineering Simulation and Numerical Integration His recent publications (2021–2025) reflect a strong trend in applying multibody dynamics to biomechanics and robotics, particularly in human gait simulation, exoskeletons, assistive devices, and industrial applications. The research combines modeling, optimization, real-time simulation, and sensor integration, often with industrial or medical applications in automotive, maritime, and rehabilitation sectors. He has secured significant research funding from national (MINECO, Xunta de Galicia), European (EU), and industrial sources (GKN Driveline, NAVANTIA, Pixee Medical), and has directed multiple final-year and master’s theses. He is also involved in patents and software development through collaborations with Tecnalia and spin-offs like ABLE Human Motion. He leads the Laboratorio de Ingeniería Mecánica, where he supervises student projects and conducts applied research. His teaching includes Machine Design, Maintenance Engineering, Theory of Machines, and Biomechanics across Mechanical, Industrial, and Podiatry programs.
Majken Kirkegård Rasmussen is an Associate Professor at Aarhus University in the Department of Digital Design and Information Studies, School of Communication and Culture. Her research and teaching focus on innovative human-computer interaction techniques, particularly in physical and kinesthetic design. Her research interests include Interaction Design, Physical Computing, Human-Computer Interaction, Robotics, and Shape-Changing Interfaces. She explores how users interact with dynamic and tactile technologies, emphasizing embodied and sensory experiences in design. Her recent publications show a strong trend in designing interactive systems that merge physical form with digital functionality, especially in robotics and adaptive interfaces. These works frequently appear in premier venues like CHI and DIS, highlighting contributions to haptic feedback, social robotics, and design methods. She has received several scientific awards, including: Gitte Lindgaard Award (2017) Honorable Mention Award (2014) Honourable mention award (2022) She is actively involved in research funding and supervision. Currently, she leads or co-leads two major research projects—ACUTE and DARE—funded by the Independent Research Fund Denmark, focusing on domestic and assistive robotics. She also teaches the course 'IT Produktdesignprojekt' and has collaborated with researchers across Europe, including at Eindhoven University of Technology. She is affiliated with active research teams working on social robotics, assistive technologies, and interactive design, contributing to both academic and practical advancements in the field.
Ros Giralt, Lluis is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mechanical Engineering and the CRG - Grup de Robòtica Computacional . His primary roles include academic research and teaching in robotics, with a focus on computational kinematics, dynamic motion planning, and singularity analysis in robotic systems. He holds a Doctorate in Industrial Engineering from UPC. Research Interests: His work centers on advanced robotics topics such as trajectory optimization for constrained systems, singularity-aware control, and motion planning for parallel and closed-chain robots. Key contributions include collocation methods for trajectory optimization and algorithms for singularity avoidance in complex mechanisms. Recent Research Trends: Recent publications emphasize trajectory optimization techniques (e.g., Legendre-Gauss pseudospectral methods), randomized kinodynamic planning for closed-chain robots, and cable-driven parallel robot control. His work bridges numerical computation and practical robotic applications, often involving collaboration with industry partners. Awards: Honorary Mention for the Planets Project (2017), Best Final Year Engineering Project (1991-1992). Advising & Grants: Advised PhD students like Ricard Bordalba and Carlos Rosales. Involved in projects like Synthesis of Optimally Agile and Graceful Robot Motions (2022) funded by competitive R&D grants. Labs/Teams: Leads the CRG - Computational Robotics Group , collaborating with institutions like the Institut de Robòtica i Informàtica Industrial (CSIC-UPC). Active in developing the CUIK Suite , a tool for analyzing multibody system motion.
Thomas Henderson is a Professor of Computer Science at the University of Utah, specializing in robotics, artificial intelligence, and computer vision. His work emphasizes multisensor data fusion, autonomous navigation, and industrial automation. He has contributed to foundational algorithms in constraint satisfaction and robotic manipulation. Research interests include 3D object representation, sensor integration, and system architecture design for industrial applications. Notable contributions span wireless sensor networks, neural controller evolution for mobile robots, and safety-critical simulations of fire/explosion scenarios. Collaborations include projects with Nanyang Technological University and industry partners in manufacturing automation. His publications (over 200 cited works) demonstrate interdisciplinary impact across robotics, computer vision, and AI. Current focus areas include strategic conflict management for unmanned aircraft systems (UAS) and resilient networked robotics solutions.
Sylvaine Tuncer is a Lecturer in Work, Interaction & Technology at King’s Business School, King’s College London. She specializes in qualitative sociological research focusing on work practices, collaboration with technologies, and video-based ethnographic methods. Her work spans human-robot interaction, healthcare technology, auction sales dynamics, and urban mobility studies. She actively contributes to interdisciplinary research and innovation in data collection methodologies. Dr. Tuncer teaches at both undergraduate and graduate levels, leading modules such as Communication in Organisations and Work Practice & Technology. She currently serves as Deputy Programme Director for the Business Management BSc. Her research group, Work, Interaction & Technology (WIT), explores video-based studies of social interaction in collaborative settings. Notable projects include studies on hybrid auction sales adaptation and the role of frontline workers in digital strategy. Her recent publications emphasize human-robot interaction design, trust dynamics in hybrid environments, and the interplay between technology and social practices. She is involved in organizing international workshops on healthcare and technology, reflecting her commitment to fostering academic exchange and applied research.
Cristiana Mirandade Farias is a postdoctoral researcher at the Intelligent Autonomous Systems (FG-IAS) group, Department of Computer Science, Technische Universität Darmstadt. Her work focuses on data-efficient robotic grasping, manipulation, and integration of multimodal sensory data with uncertainty handling. PhD in Robotics from University of Birmingham (Extreme Robotics Lab) MSc and BSc in Control and Automation Engineering from University of Brasilia Her research combines tactile sensing, active perception, and geometric methods to enhance robotic manipulation capabilities. Publications emphasize dual quaternion algebra, spectral analysis, and functional mapping techniques. Article trends show consistent contributions to robotic grasping (data efficiency, deformable objects, partial observability), visual servoing, and geometric modeling, with a focus on cross-modal integration and mathematical formalisms like dual quaternions. Current work addresses challenges in grasping unknown/moving objects using tactile exploration and uncertainty-aware pipelines.
João Carvalho is a Postdoctoral Researcher at the Intelligent Autonomous Systems (IAS) group within the Technische Universität Darmstadt . He obtained his PhD in Computer Science from TU Darmstadt in 2025, advised by Jan Peters, following a MSc in Computer Science from Albert-Ludwigs-Universität Freiburg and a Master's in Electrical and Computer Engineering from Instituto Superior Técnico (University of Lisbon). His work focuses on developing machine learning and reinforcement learning algorithms for robot manipulation, particularly in motion planning, grasping, and contact-rich tasks like insertions. Education: PhD in Computer Science, TU Darmstadt (2025) MSc in Computer Science, Albert-Ludwigs-Universität Freiburg Master's in Electrical and Computer Engineering, Instituto Superior Técnico (University of Lisbon) His research integrates generative models for motion planning and grasping, reinforcement learning for contact-rich tasks, and policy gradient methods with variance reduction. Recent publications highlight applications of diffusion models and tensor planning in robotics, with a focus on spatial symmetry and efficient policy generation. Key contributions include work on Motion Planning Diffusion , Grasp Diffusion Networks , and Model Tensor Planning . He actively supervises thesis students in areas related to robot learning , generative models , and residual reinforcement learning .
Oziel Rios is a Senior Lecturer in the Department of Mechanical Engineering at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. He holds a PhD and MS in Mechanical Engineering from The University of Texas at Austin and a BS from The University of Texas Pan American. PhD, Mechanical Engineering, The University of Texas at Austin, 2008 MS, Mechanical Engineering, The University of Texas at Austin, 2005 BS, Mechanical Engineering, The University of Texas Pan American, 2002 His research focuses on the modeling, design, and control of robotic systems, with emphasis on kinematics and dynamics of machines and computer-aided geometric design. His work provides analytical foundations for improving robotic manipulator performance through energy efficiency, gain distribution, and acceleration modeling. The publications span the year 2009 and center on advanced analytical techniques in robotic mechanism design, particularly in serial chain systems. Key themes include kinetic energy ratios, actuator gain distributions, and geometric transformation-based acceleration models, reflecting a cohesive research agenda in robotic dynamics and control theory. Scientific Awards and Honors: Outstanding achievement award, mechanical engineering award, University of Texas-Pan American Best student paper award, The Society of Plastics Engineers Annual Technical Conference (SPE-ANTEC) South Texas fellowship Cullen M. Crain endowed scholarship in engineering George J. Heuer, Jr. PhD endowed graduate fellowship Oziel Rios advises graduate students in mechanical engineering research, though currently not accepting undergraduate researchers. While no specific grants are listed, his work appears supported by academic fellowships during his training. His contributions lie in foundational mechanical design methodologies for robotic systems. He is actively engaged in teaching and research within the Mechanical Engineering program at UT Dallas, contributing to both curriculum and research in robotics and dynamic systems.
Álvaro Jesús López López is a researcher at the Instituto de Investigación Tecnológica (IIT) and a professor at the Higher Technical School of Engineering (ICAI), both part of Comillas Pontifical University. He holds the position of Associate Research Fellow and serves as a principal investigator at the Chair of Smart Industry, where he leads applied research on digital technologies such as generative AI, computer vision, and synthetic data generation. He also directs executive programs in generative artificial intelligence for professionals at Comillas Onexed. His research interests include Artificial Intelligence, Reinforcement Learning, Generative AI, Smart Industry, and Railway Systems . His work focuses on applying advanced AI techniques to industrial and transportation challenges, particularly in energy efficiency and automation. He has published extensively in high-impact journals such as Engineering Applications of Artificial Intelligence , Applied Intelligence , and Transportation Research Part C . The recent articles highlight a strong trend toward applied AI in industrial and robotic systems , with a focus on sim-to-real transfer, keyphrase extraction, and reinforcement learning enhanced with semantic knowledge. His work bridges the gap between theoretical AI and real-world industrial applications. Scientific Awards: Honorable Mention from the Industry 4.0 Observatory (2021) Honorable Mention at the 6th Connected Industry Promotion Award Erasmus Teaching/Research Staff Training Grant (2014) He has advised multiple PhD students and leads several industry-funded research projects with organizations such as Ferrovial, Endesa, Metro de Madrid, and the European Commission. He has also organized scientific events and delivered numerous invited talks on AI and digitalization. His research has led to practical applications, including a patent on utilizing regenerative braking energy in railways. He completed a research stay at the Royal Institute of Technology (KTH) in Stockholm and has contributed to books and policy reports on digitalization in industry.
Stanimir Yordanov Yordanov is an Associate Professor at the Department of Automation, Information and Control Technology within the Faculty of Electrical Engineering and Electronics at Technical University - Gabrovo. With a Doctorate in Technical Sciences and over 30 years of professional experience since 1993, he has established himself as a leading researcher and educator in control systems and automation. His educational background includes a Master of Engineering from VMEI - Gabrovo (1992) with specializations in Computer Engineering, Management Technologies, and Pedagogy, followed by a Doctorate (2006) and Associate Professor qualification (2010) in specialized technical fields. His teaching portfolio encompasses System Programming, Operating Systems, Digital Control Systems, and Industrial Robotics, among others. Professor Yordanov's research focuses on automated control systems, intelligent management of technological processes, industrial system monitoring, and object/system modeling. His work demonstrates a consistent trajectory toward increasingly sophisticated control algorithms and applications across diverse domains from electrohydraulic systems to environmental monitoring. The recent publications reveal a strong emphasis on advanced control techniques including neuro-PID regulators, model predictive control, and applications of artificial intelligence in industrial contexts. His extensive project portfolio includes 22 significant research initiatives, ranging from national projects like the 'Competence Center for Intelligent Mechatronic Systems' to international collaborations such as the 'MechMate' project focused on European SME growth. These projects demonstrate his ability to secure funding and lead research teams across various technical domains. Professor Yordanov has mentored six PhD students to completion, with several successfully defending dissertations on topics including intelligent energy systems, embedded real-time operating systems, and robotic systems. His academic leadership extends to serving as an academic mentor for over 600 student internships. His laboratory work centers on electrohydraulic control systems, robotic manipulation, and intelligent monitoring applications, with recent projects developing smart dispensers, beehive monitoring systems, and low-cost health monitoring devices for pregnant women, demonstrating practical applications of his theoretical research.
Philipp Cimiano is a Professor at Bielefeld University, Germany , with a prolific research record in Artificial Intelligence, Semantic Web, Natural Language Processing, Knowledge Graphs, Explainable AI, Clinical Decision Support Systems, Ontology Engineering, and Federated Learning . His work bridges theoretical AI concepts with practical applications in healthcare and robotics. Key research themes include dialogue-based XAI for user understanding, federated learning for healthcare data privacy, and LLM-driven robotics for embodied commonsense reasoning. Recent publications analyze dynamic explanatory interactions , perspectivized argumentation frameworks , and benchmarks for robot manipulation using large language models. His collaborations span institutions in Germany and Europe, with frequent co-authorship on topics like counterfactual generation , stakeholder group analysis , and lexicalization in QALD systems .
