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Dr. Ge Gao is a researcher at the Department of Informatics, University of Hamburg, affiliated with the CV Research Group. His research focuses on 6D object pose estimation, cognitive robotic vision, and deep learning applications in robotics. He holds a PhD in Informatics from the University of Hamburg, completed in 2021. Education: PhD in Informatics (2021), University of Hamburg. Previously conducted research on occlusion-resistant object pose estimation and saliency-guided segmentation techniques. Research emphasizes robotics perception, point cloud analysis, and multimodal sensor fusion. His work spans applications from robotic grasp planning to gait analysis using dynamic vision sensors. Key contributions include CloudAAE framework for 6D pose regression and saliency-driven supervoxel segmentation. Publications (2015–2021) address challenges in 3D object localization, multimodal data processing, and robotic vision systems. Active in conferences like ICRA, ECCV, and IROS. Labs/Projects: Involved in InteGreatDrones (drone-based robotics), Crossmodal Learning (CML), ahoi digital (crossmodal sensor data collection), and MACS (machine learning applications).

• 6D Object Pose Estimation
• Cognitive Robotic Vision
• Deep Learning
• +5 more

Dr. Mien Van is a Senior Lecturer (a.k.a. Associate Professor) in Robotics and Control Engineering at Queen's University Belfast, UK. He leads multiple research projects in autonomous systems, human-robot collaboration, and underwater robotics. His work spans resilient control for autonomous vehicles, in-process manufacturing quality control, and bio-inspired robotics design. Education: Research Fellowships at National University of Singapore (2015-2017) and University of Exeter (2018-2019). Research Interests: Resilient Autonomy, Human-Robot Interaction, Underwater Vehicles, Fault Diagnosis. Awards: IET Premium Award (2017), Best Paper Awards from BK21 and ICROS. Key Projects: ORCA (Dstl/MOD-funded), Digital Twins for Underwater Operations (EPSRC), Offshore Wind Turbine Blade Monitoring (Innovate UK). Dr. Van has authored/co-authored over 75 journal papers with an h-index of 34 and >3,700 citations. He serves as Associate Editor for multiple top-tier journals including IEEE Transactions on Automation Science and Engineering.

• Robotics and Control Engineering
• Autonomous Systems
• Human-Robot Interaction
• +5 more

Alexandre Angleraud is a Postdoctoral Research Fellow at Tampere University within the Automation Technology and Mechanical Engineering department under the Faculty of Engineering and Natural Sciences. His research focuses on advancing human-robot collaboration, robotic manipulation, and sensor-based systems in industrial and manufacturing environments. Key areas include knowledge-based planning, tactile feedback learning, and cognitive semantics for dynamic task coordination. His work integrates robotics with machine learning techniques, emphasizing agile production systems, soft robotic grippers, and natural language interfaces for hierarchical task instruction. Notable contributions include innovations in multi-label annotation for visual models and exploration-exploitation mechanisms inspired by neural processes. Recent research trends highlight advancements in co-speech gesture interpretation for human-robot interaction, imitation learning frameworks leveraging sequential data, and comparative studies on sim-to-real learning controllers. His studies often bridge theoretical cognitive models with practical industrial automation challenges. No scientific awards or funded grants are explicitly listed in the provided materials. Advising activities and lab affiliations remain unspecified in the current data.

• Robotics
• Human-Robot Interaction
• Industrial Automation
• +3 more

Hugh Zhou is a Research Fellow in the Department of Mechanical & Aerospace Engineering at Monash University. His work focuses on advancing robotic harvesting systems, automation in orchards, and sensor integration for agricultural applications. He has contributed to projects such as the Monash Apple Retrieving System and Phenobot, an autodigital phenotyping tool for horticulture. His research emphasizes real-time defect detection, tactile sensing for obstacle handling, and 3D fruit detection algorithms. Collaborations span international institutions, with contributions to precision agriculture and sustainable development goals related to food production efficiency. Key publications include advancements in robotic end effectors, soft robotic actuators, and slip detection methods. His work bridges mechanical engineering, computer vision, and agricultural automation, addressing challenges in fruit harvesting efficiency and system intelligence.

• Robotics
• Agricultural Automation
• Sensor Technology
• +3 more

Roel Pieters is a Professor in Automation Technology and Mechanical Engineering, specializing in robotics and human-robot collaboration. His research focuses on advancing automation in industrial settings through innovations in robotic manipulation, sensor-based systems, and cognitive architectures. He has contributed to the development of datasets like the 6DAPose synthetic assembly dataset and the Engine Assembly Dataset, aiding advancements in pose estimation and robotic control. His work aligns with UN Sustainable Development Goals, particularly in fostering innovation and industrial efficiency. Pieters has organized events such as the IEEE Future of Robotics in Finland Seminar and serves as a reviewer for journals like IEEE Transactions on Automation Science and Engineering. His research emphasizes safety, adaptability, and human-centric design in robotics applications, including collaborative tasks and industrial automation. Key themes in his work include multimodal human-robot interaction, cognitive systems for exploration and learning, and the integration of AI with robotics. He explores topics like gesture-based commands, neural curiosity mechanisms, and the personalization of robotics for Industry 5.0. His contributions span both theoretical advancements and practical deployments in manufacturing and service robotics.

• Robotics
• Human-Robot Collaboration
• Robot Manipulation
• +8 more

Dr. Kartikeya Walia is a Lecturer in the Department of Engineering at Nottingham Trent University (NTU). His work bridges design, manufacturing, and robotics, with a strong emphasis on sustainable engineering practices. He actively engages in research projects that focus on additive manufacturing, generative design, and their applications in both industrial and medical robotics. Role: Lecturer in Engineering Key Research Areas: Design optimization, Additive Manufacturing, Robotics, Sustainable Design Funding: £2.5k (ICURe Discover, Innovate UK, UKRI, 2025), £13.5k (NTU International Partnership Fund, 2024-25), £2k (UK-RAS Network+ AdHoc Funding, 2024-25), £2.5k (Connected Everything ECR Placement Scheme, 2022-23) Kartikeya's research is at the intersection of design, manufacturing, and robotics. His projects often explore generative design methodologies, additive manufacturing techniques, and innovative approaches to reduce resource consumption in engineering practices. His work has been recognized through the NTU Open Research Award 2024, and he serves as a judge for the Robotics & Automation Awards 2025. His recent publications highlight advancements in spherical parallel manipulators, emergency response devices like low-cost ventilation systems, and robotic surgical tools. These works align with his broader goals of integrating sustainability into engineering solutions while optimizing material usage and production efficiency. Scientific Awards: NTU Open Research Award 2024, Judge for Robotics & Automation Awards 2025 Kartikeya also contributes to education by teaching 'Innovation and Engineering Solutions,' a course that fosters creativity and problem-solving skills. Students engage with tools like Autodesk Fusion 360, exploring CAD modeling, reverse engineering, and generative design principles through hands-on projects.

• Design
• Manufacturing
• Robotics
• +5 more

Rohan P. Singh is a Postdoctoral Researcher at the CNRS-AIST Joint Robotics Lab (JRL) in Tsukuba, Japan, since April 2024. Previously, he worked as a full-time Robotics Engineer (2017-2019) and Research Assistant (2019-2024) at the same lab, mentored by Fumio Kanehiro . His research bridges robotics, machine learning, and computer vision , with a focus on practical applications for humanoid robots. Education: Ph.D. in Reinforcement Learning for Humanoid Locomotion (2024), University of Tsukuba MS in 6-DoF Object Pose Estimation (2021), University of Tsukuba Research Interests include: Deep Reinforcement Learning for humanoid movement Sim-to-real transfer methods 6-DoF object pose estimation with minimal human effort Multi-contact locomotion planning Open-source robotics tools development Notable Scientific Awards : JST SPRING Fellowship (2021-2024) Excellent Master's Thesis Award (2021) Projects include: LearningHumanoidWalking: Training humanoid robots with PPO reinforcement learning RapidPoseLabels: Tool for automated 6-DoF object labeling ObjectKeypointTrainer: CNN training framework for pose estimation ANA Avatar XPRIZE team member

• Robotics
• Reinforcement Learning
• Humanoid Locomotion
• +4 more

Francis Engelmann is an incoming Assistant Professor at the University of Lugano (USI) Faculty of Informatics, currently completing his postdoctoral research at Stanford University working with Prof. Leonidas Guibas and Prof. Jeannette Bohg. Prior to Stanford, he was a postdoctoral research fellow at ETH Zurich with Prof. Dr. Marc Pollefeys and conducted his PhD in Computer Vision, Machine Learning and 3D Scene Understanding at RWTH Aachen University under Prof. Dr. Bastian Leibe. His research focuses on advancing 3D scene understanding through computer vision, machine learning, and robotics. Engelmann's work explores open-vocabulary 3D scene understanding, functional scene analysis, 3D reconstruction, and semantic segmentation. He has made significant contributions to open-vocabulary 3D instance segmentation, 3D scene graph construction, and language-augmented 3D vision. His research bridges theoretical computer vision with practical robotics applications, particularly in scene understanding for robotic manipulation. Analysis of his recent publications reveals a strong trajectory in developing methods for open-vocabulary 3D scene understanding, with increasing focus on functional understanding, language integration, and practical robotics applications. His work spans from foundational 3D representation learning to applied robotics systems, with a consistent emphasis on making 3D scene understanding more accessible, scalable, and semantically rich. ETH Zurich Career Seed Award (2022) Outstanding Reviewer for CVPR 2024 (top 2%) Top Reviewer for NeurIPS 2023 Best Paper Award at ICRA'24 MOMA.v2 workshop Multiple oral presentations at top-tier conferences (ICCV, CVPR, ECCV) Engelmann actively mentors PhD students and postdocs, with notable collaborations including Valentin Bieri, Rui Huang, Elisabetta Fedele, and Ayca Takmaz. He has received an NVIDIA Academic grant and serves as an area chair for major computer vision conferences including CVPR'25, WACV'26, and 3DV'25. He co-organizes the annual Open-Vocabulary 3D Scene Understanding Workshop, now in its fourth iteration at CVPR'25.

• Computer Vision
• 3D Scene Understanding
• Machine Learning
• +4 more

Mariano Alvarez is a researcher at the Research Centre in Digitalization and Intelligent Robotics (CeDRI) at the Polytechnic Institute of Bragança (IPB), with a focus on control and automation systems in industrial and educational contexts. His academic background includes a Bachelor's degree in Electronic Engineering from National Technological University - Cordoba Regional Faculty (UTN-FRC) and a Master's in Industrial Engineering - Electrotechnical Branch from IPB. Education National Technological University - Cordoba Regional Faculty (UTN-FRC), Electronic Engineering Polytechnic Institute of Bragança (IPB), Master's in Industrial Engineering - Electrotechnical Branch Mariano's research interests span Control and Automation , Robotics , and their applications in Industrial Engineering and Intelligent Robotics . His work on the STC 4.0 HP project aims to innovate stoneware tableware production using Ceramic 4.0 technologies and high-pressure casting robot work cells. Recent publications highlight trends in robotics for educational technology, including Force Feedback Actuators , 3D Surface Laser Engraving , and Educational Manipulator Robot Development . These works emphasize interdisciplinary approaches bridging automation, control systems, and robotics education. As part of CeDRI, Mariano contributes to advancing digitalization and intelligent robotics in manufacturing. No scientific awards or supervisees are documented in the available information.

• Control and Automation
• Robotics
• Industrial Engineering
• +3 more

Roles and Affiliations: Dhaminda Abeywickrama is a Research Fellow in Autonomous Systems at the University of Manchester's Department of Computer Science. He leads assurance research for robotics and autonomous systems (RAS), focusing on safety, ethics, and security. His work is part of CRADLE, a center developing technologies for high-stakes industries like space and energy. Previously, he held roles at the University of Bristol (UKRI TAS Node in Functionality) and University of Warwick (agent-based norms research). He completed ERCIM and Marie Curie fellowships at VTT (Finland) and Fraunhofer FOKUS (Germany), with a focus on autonomic systems. Education: PhD in Software Engineering, Monash University (2010) First Class Honours in Computing, Monash University (2004) Research Interests: His expertise spans assurance engineering, autonomous systems, formal verification, multi-agent systems, and responsible AI. He develops frameworks for trustworthy robotics through model-driven design and dynamic assurance techniques. Key themes include emergent behavior analysis, sociotechnical risk modeling, and ethical decision-making in human-agent collectives. Publications: His work emphasizes cross-disciplinary approaches to assurance in robotics, with recent focus on swarm verification and trustworthiness specifications. Over 35 publications include peer-reviewed articles and conference papers, with 32 as first author. Key topics include robotic swarm validation, ethical AI, and self-adaptive system architectures. Awards and Grants: EU Marie Curie Fellowship (2013–2014) ERCIM Fellowship (2013–2017) Best Paper Award at WETICE’14 IBM Award at ICSOC’08 PhD Symposium Labs and Collaborations: CRADLE (University of Manchester), UKRI TAS Node (Bristol), and collaborations across academia and industry (e.g., Jaguar Land Rover, Volkswagen AG). Research integrates formal methods with real-world applications in robotics, safety-critical systems, and autonomous vehicle coordination.

• Autonomous Systems
• Assurance Engineering
• Formal Verification
• +7 more

Katie Driggs-Campbell is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Coordinated Science Laboratory. She holds affiliate appointments in the Computer Science Department, Center for Digital Agriculture, and Discovery Partners Institute. Her research focuses on human-centered autonomy, integrating robotics, AI, and control theory to enable safe and effective human-robot collaboration in real-world environments. Education: PhD in Electrical Engineering and Computer Sciences, UC Berkeley (2017) MS in Electrical Engineering and Computer Sciences, UC Berkeley (2015) BSE in Electrical Engineering, Arizona State University (2012) Research Interests: Dr. Driggs-Campbell develops autonomous systems that operate safely alongside humans, emphasizing explainability in AI, human-robot interaction, and optimization-based control strategies. Her work spans robotics in agriculture, assistive technologies, and urban environments, leveraging interdisciplinary methods from machine learning and systems theory. Awards: 2023: IEEE RAS Early Academic Career Award 2023: George N. Saridis Best Transactions Paper Award 2022: NeurIPS Best Paper Award for Explainable Autonomy 2023: Bruning Family Faculty Fellowship Advising & Grants: Leads the Human-Centered Autonomy Lab, supervising graduate students in robotics and autonomy. Recent grants include USDA funding for agricultural robotics autonomy and IBM collaboration on trustworthy AI systems. Courses taught include ECE 470 (Introduction to Robotics) and ECE 484 (Principles of Safe Autonomy). Labs/Teams: Director of the Human-Centered Autonomy Lab (HCAL), which pioneers interdisciplinary robotics solutions at UIUC’s Coordinated Science Lab. Collaborates with industry partners like IBM on cutting-edge autonomy challenges.

• Autonomous Robotics
• Human-Robot Interaction
• Optimization
• +3 more

Prof. Charlie C.L. Wang is a Professor of Smart Manufacturing at the University of Manchester, holding an EPSRC Fellowship in Field Computation Based Kernel for Vector 3D Printing. Previously, he served as Professor and Chair of Advanced Manufacturing at Delft University of Technology (2016) and held academic roles at the Chinese University of Hong Kong from 2003. He also held a visiting position at the University of Southern California (2011). His expertise spans Digital Manufacturing, Additive Manufacturing, Soft Robotics, and Geometric Computing. He holds a B.Eng. from Huazhong University of Science and Technology (1998) and a Ph.D. from HKUST (2002). Research Interests: His work focuses on computational design, additive manufacturing techniques, soft robotics kinematics, and mass personalization. He contributes to UN Sustainable Development Goals through innovations in smart manufacturing and sustainable technologies. Key areas include 3D printing optimization, bioprinting systems, and geometric computing for robotics. Key Projects: Current projects include SORO-MADE (soft robotic mannequin design), decomposition-based process planning for CNC machining, and automated knitting code generation. He leads initiatives in multi-axis additive manufacturing and field computation for 3D printing. Awards: Notable honors include the ASME CIE Excellence in Research Award (2016), Fellow of ASME (2013), and ISSMO/Springer Prize (2019). He has received nine Best Paper Awards and multiple teaching and project-oriented accolades. Grants & Activities: Active in research grants totaling over £multi-million. Engages in invited talks on topics like soft robotics and computational design, and chairs the Solid Modeling Association’s Executive Committee (2021–2024).

• Digital Manufacturing
• Computational Design
• Additive Manufacturing
• +3 more

Dr. Onaizah Onaizah is an Assistant Professor at McMaster University’s Department of Computing and Software and a cross-appointed member of the School of Biomedical Engineering and the Department of Mechanical Engineering. She leads the Hardware at the millimetre-scale for healthcare (HeART) Lab, focusing on developing miniature magnetic robots for biomedical applications. Her research spans robotics, magnetics, manufacturing, and clinical integration. BSc, University of Toronto (2013) MSc, Western University (2015) PhD, University of Toronto (2019) Dr. Onaizah’s work revolves around magnetic soft robots, emphasizing design, fabrication, and control for medical use. She explores programmable magnetization, real-time feedback systems, and material characterization to enhance precision in minimally invasive procedures. Her expertise includes mechatronics, vision sensing, and localization for microscale devices. Her recent publications highlight advancements in 3D-printed magnetic robots, autonomous endoscopy, and surgical tools. Key trends include the integration of machine learning for design optimization, closed-loop control for dynamic environments, and pandemic-adapted clinical protocols. Scientific recognition includes a $5.2M SSHRC and CFI grant (2024) for her research. She teaches graduate courses in microrobotics and medical robotics, emphasizing interdisciplinary collaboration between engineers, clinicians, and scientists. At the HeART Lab, she leads a multidisciplinary team of roboticists, engineers, and clinicians, addressing challenges in healthcare through hardware innovation. The lab focuses on tetherless devices, programmable materials, and integration into clinical workflows.

• Microrobotics
• Soft Continuum Robots
• Medical Robotics
• +6 more

Dr. Jiaming Fu is an Assistant Professor in the Department of Mechanical Engineering at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He is actively involved in teaching and research, focusing on robotics and dynamic systems. Education: Ph.D. in Technology (Robotics Track), Purdue University, 2024 M.S. in Mechanical Engineering, Columbia University, 2020 B.S. in Mechanical Engineering, Florida Institute of Technology, 2017 Dr. Fu's research centers on robotics, particularly collaborative and soft robotics, variable stiffness mechanisms, compliant design, grasping, control, and AI in mechanical systems. His work emphasizes safety and adaptability in human-robot interaction, with applications in manufacturing and healthcare. He has published extensively in high-impact journals such as ASME Journal of Mechanisms and Robotics and IEEE conferences including ICRA and ReMAR. His recent publications (2021–2024) highlight innovations in variable stiffness actuators, force sensing, rehabilitation robotics, and intelligent control. He holds multiple pending patents in robotic grippers and rehabilitation tools. Dr. Fu teaches Dynamic Systems and leads the BattleBots Enterprise Project, fostering hands-on learning. Scientific Awards: ASME Top Senior Award Dr. Fu actively contributes to the academic community as a reviewer for IEEE Transactions on Biomedical Engineering, IEEE Transactions on Circuits and Systems for Video Technology, ASME Journal of Mechanisms and Robotics, and conferences like IEEE BioRob, ICRA, and IDETC-CIE. He mentors students through research and project-based learning, though specific advisees are not listed. He has not received explicit grant mentions in the text, but his patent activity and publication record suggest funded research. He is involved in enterprise teams like BattleBots, promoting student innovation in robotics.

• Robotics
• Collaborative Robotics
• Soft Robotics
• +12 more

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

• Intelligent and advanced control
• Optimization and modeling of systems
• Virtual and intelligent instrumentation
• +3 more