Strahinja Dosen is a Professor and Head of Research Group in the Department of Health Science and Technology at Aalborg University's Faculty of Medicine. His research focuses on neurorehabilitation systems, particularly in rehabilitation engineering, robotics, and human-machine interfaces. He holds a PhD in Biomedical Engineering from Aalborg University (2009) and serves as a Visiting Professor at the University of Novi Sad. His work addresses cutting-edge topics like myoelectric control, brain-machine interfaces, artificial sensory feedback, and functional electrical stimulation. Key projects include the development of closed-loop robotic prostheses and sensory feedback systems for amputees. Dosen has led over 17 research projects, including the PERSONIFY initiative on powered ankle prosthesis control and the DexterHand bionic prosthetics platform. With 216+ publications, his research emphasizes improving prosthetic control through electrotactile/haptic feedback, 5G-enabled bionic limbs, and stroke rehabilitation robotics. He collaborates internationally on neurorehabilitation technologies and has been featured in media for innovations like thought-controlled prosthetics and robotic rehabilitation systems. Grants and collaborations include EU-funded projects and industry partnerships. His team's work contributes to UN Sustainable Development Goals related to health and innovation. Dosen advises on 6 PhD students and actively participates in academic workshops and editorial roles in haptics and prosthetics.
Mark Philip Philipsen is an Assistant Professor at the Department of Architecture, Design and Media Technology, Aalborg University. He holds a PhD (ErhvervsPhD) from 2017 to 2019. His research focuses on computer vision, robotics, and machine learning applications in environmental science, infrastructure, and industrial automation. He leads projects such as ReDoCO2 (2020–2025) addressing peatland CO2 emissions and Applications of Vision and Robotics in Meat Production (2017–2020), exploring automation in food processing. His work spans diverse areas, including semantic segmentation of underground utilities using 3D point clouds, peat mapping with graph neural networks, and anomaly detection in agricultural vehicles. Philipsen has contributed datasets like OpenTrench3D and LISA Traffic Light Dataset, advancing research in infrastructure analysis and vision systems. His publications emphasize practical applications of AI in environmental monitoring, robotics, and data-driven solutions for industry challenges. Key achievements include developing synthetic thermal human scenarios (ThermalSynth) and semi-supervised learning models for sewer systems. His research often bridges theory and real-world problems, with a focus on sustainability and automation.
Piotr Luszczek is a Research Professor and Adjunct Associate Professor at the University of Tennessee, Knoxville's Tickle College of Engineering, affiliated with the Department of Computer Science and the Innovative Computing Laboratory. He holds a Ph.D. and M.S. from the University of Tennessee, Knoxville, and a B.S. from AGH University of Science and Technology in Kraków, Poland. Affiliations : Innovative Computing Laboratory (ICL), Tickle College of Engineering. Roles : Research and teaching in high-performance computing, numerical linear algebra, and performance optimization. Research Interests focus on benchmarking, numerical linear algebra for HPC, automated performance tuning for modern hardware, and stochastic models for performance analysis. His work emphasizes scalable algorithms, GPU acceleration, and efficient use of hybrid architectures. Grants and Collaborations include projects on batched linear algebra, sparse matrix operations, and energy-efficient AI frameworks. He contributes to software libraries like PLASMA and MAGMA, optimizing for exascale computing. Labs/Teams : Active in the Innovative Computing Laboratory (ICL), developing tools for HPC benchmarking (e.g., HPCG) and parallel linear algebra libraries. Engaged in international collaborations for exascale computing initiatives.
Seyyedali Hosseinalipour is an Assistant Professor in the Department of Electrical Engineering at the University at Buffalo (School of Engineering and Applied Sciences). His research focuses on synergies between machine learning and wireless networks, with a particular emphasis on federated learning, vehicular networks, and intelligent network design. He holds a PhD in Electrical Engineering from North Carolina State University (2020), an MSc from the same institution (2017), and a BSc from Amirkabir University of Technology (2015). His research interests include federated learning frameworks for dynamic environments, UAV-assisted communication systems, and optimization of edge/cloud computing architectures. Notable areas of exploration include decentralized federated learning, non-IID data distributions, and applications in IoT and 5G/6G networks. His recent work addresses challenges such as energy-efficient resource allocation in UAV networks, latency reduction in hierarchical federated learning, and robust task scheduling over vehicular clouds. He has also explored cross-disciplinary applications like federated learning in educational analytics and medical imaging. Despite the breadth of his work, he maintains a focus on practical implementations through frameworks like HEART and GA-DRL. Dr. Hosseinalipour’s contributions bridge theoretical models and real-world deployment, emphasizing scalability, privacy, and system resilience. His research has implications for smart cities, autonomous systems, and distributed AI ecosystems.
Steve Eugene Watkins is a Professor in the Department of Electrical and Computer Engineering at Missouri University of Science and Technology . He serves as the Director of the Applied Optics Laboratory (APOL) and has held leadership roles including Interim Department Chair (2020-2022), IEEE-HKN President (2018), and IEEE Education Society Vice-President (2019-2022). Education: PhD (1989) and MS (1985) in Electrical Engineering from University of Texas at Austin and University of Missouri–Rolla respectively. Research Interests: Smart sensor systems, UAV instrumentation, fiber optic sensing, structural health monitoring, and pre-college engineering outreach. Awards: ASEE Meritorious Service Award (2023) SPIE Fellow (2018) IEEE-HKN Distinguished Service Award (2021) Toastmasters Presidential Citation (2003) Professional Activities: Advisor to IEEE-HKN and Tau Beta Pi, co-coordinator of S&T Pre-college Robotics Summer Camp, and inventor of a U.S. Patent (7,603,004) for neural network demodulation in optical sensors.
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).
Dr. Elena Kakoulli is a Lecturer in Information Systems and Coordinator of the MSc in Information Systems and Digital Innovation at the University of Nicosia. She holds a Ph.D. in Computer Engineering from Cyprus University of Technology (2015), following a Master’s in Computer Science (2009) and B.Sc. (2007) from the University of Cyprus. Her research focuses on computer architecture, photonics-based interconnection networks, cybersecurity, and AI-driven educational technologies. Notable contributions include work on resilient NoC architectures, distributed storage systems (OctopusFS), and silicon photonics integration for high-performance computing. Dr. Kakoulli’s research interests span network-on-chip (NoC) design, IoT security, and adaptive learning frameworks. She has collaborated on projects such as distributed tiered storage for cluster computing with Dr. Herodotou. Recognitions include awards from the University of Cyprus and Marfin Laiki Bank Foundation for academic excellence during her postgraduate studies. She has also contributed to teaching roles as a Teaching Assistant at the University of Cyprus and lecturer at Ctl Eurocollege, covering courses like computer architecture, compilers, and operating systems. Her publications highlight advancements in cybersecurity models, AI-integrated education tools, and next-generation computing architectures. She actively participates in academic conferences, including the 21st European, Mediterranean, and Middle Eastern Conference on Information Systems (EMCIS 2024), and has served as a Technical Program Committee member.
Alejandro Secades Rodriguez is a Doctoral Student and Project Employee at the Management Center Innsbruck (Mechatronics Department) since 2016, transitioning to the Industrial Engineering Department in 2024. He holds a Master's in Mechatronics & Smart Technologies (2017) and a Bachelor's in Aerospace Engineering (2014). His expertise includes CFD , Multiphysics Simulation , Multibody Dynamics , and Advanced CAD Design . Education : Doctoral Programme in Engineering Sciences (University of Innsbruck, since 2024) MSc in Mechatronics & Smart Technologies (MCI, 2017) BSc in Aerospace Engineering (Universidad Alfonso X el Sabio, 2014) Research Focus : Dynamic interaction of off-road heavy-duty vehicles with terrain Energetic optimization in industrial heat transfer systems Digital Twin integration for automotive and mechanical systems UAV propulsion and aerodynamic efficiency Multiphysics modeling (hydraulics, electrical, mechanical, aerodynamics) Scientific Awards : 2018: First place for best Master's thesis (Mechatronics Platform Austria) Teaching Activities : 2022-2024: Multibody & Multiphysics Simulation (Master's level) 2023: Supervision of Bachelor's thesis on point cloud volume analysis
Prof. Dr.-Ing. Jörg Franke is a Professor at the Department of Mechanical Engineering, Friedrich-Alexander University Erlangen-Nürnberg, leading the Institute for Factory Automation and Production Systems (FAPS). His research spans manufacturing systems, production technologies, and sustainable industrial practices, with a strong focus on electric mobility and data-driven production optimization .
Pieter Pauwels is an Associate Professor at Eindhoven University of Technology's Department of the Built Environment and a Guest Professor at Ghent University's Department of Architecture and Urban Planning. His research focuses on integrating semantic web technologies, linked building data (LBD), and AI to improve decision-making in architecture and construction. He leads projects on BIM, digital twins, and interoperability between static/dynamic building data. Education includes a PhD in Civil Engineering (Architecture) from Ghent University (2012) and postdoctoral roles at the University of Amsterdam (2012–2014) and Ghent University (2014–2017). He develops ontologies like ifcOWL and contributes to initiatives such as the W3C Linked Building Data Community Group. His work emphasizes practical applications, including robot navigation using building digital twins, IoT-BIM integration, and automated code compliance checking. Projects like LBDserver and ConSolid address federated data ecosystems in construction. He teaches courses on BIM fundamentals, parametric design, and digital built environments. Research spans semantic web applications in construction, design thinking, and AI-driven material performance assessment. Key collaborations include BuildingSMART and the EU's READY4SmartCities initiative. His ontologies and tools are widely used in the AEC industry, fostering interoperability and innovation.
Daniel Duberg is a Researcher and PhD candidate at the Division of Robotics, Perception and Learning (RPL) within the School of Electrical Engineering and Computer Science at Kungliga Tekniska Högskolan (KTH). His research focuses on autonomous exploration and real-time 3D mapping using unmanned aerial vehicles (UAVs), emphasizing onboard processing for indoor environments. He has contributed to frameworks like UFOMap, which address dynamic environments and efficient data structures. His work integrates probabilistic modeling, sensor fusion, and real-time algorithms to enhance UAV navigation and decision-making. Notable projects include dynamic-aware mapping (DUFOMap) and exploration strategies guided by formal methods like Signal Temporal Logic. Duberg teaches engineering courses in robotics and collaborates on open-source tools for autonomous systems. His research trends emphasize scalability, robustness in uncertain conditions, and adaptive planning for long-term autonomy. He has published widely on exploration algorithms, volumetric mapping, and UAV navigation challenges, with applications in both static and dynamic environments. Duberg’s academic contributions span over a decade, with early work on tele-operation safety and recent advancements in semantic mapping and multi-sensor fusion. His research bridges theoretical foundations with practical implementations for deployable robotic systems.
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.
Enrico Masala is Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, where he also serves as Deputy Coordinator of the College of Computer, Film and Mechatronics Engineering. He is a member of the Internet Media Group (IMG) and the Interdepartmental Center for Service Robotics (PIC4SeR), and actively contributes to multimedia systems research and education. His research interests include multimedia communications, video coding, digital image processing, and media quality assessment, with a strong focus on AI and machine learning applications. His work spans algorithm development for quality optimization in multimedia transmission over packet networks, including wireless and cloud-based systems. The recent publications highlight a strong trend in leveraging deep learning and AI to model human perception in multimedia quality assessment. Topics include artificial observers, modeling of subjective scoring behavior, and individualized quality prediction—indicating a shift toward more personalized and human-aligned evaluation frameworks in multimedia systems. Elsevier Audioslides competition (2013) ScienceDirect TOP25 Hottest Articles (2012) Fellow - IEEE (2014–) IEEE Senior Member Enrico Masala has served as Scientific Manager for multiple commercial research projects, including the Radio 3.0 streaming platform and V-POP multimedia transmission project. He has also acted as evaluator for CHIST-ERA and the European Commission. He teaches core courses such as Internet Video Streaming and Web Applications , and has delivered international lectures and keynote talks, including at BUPT in China and CONIELECOMP in Mexico. He leads the JEG-Hybrid project within the Video Quality Experts Group (VQEG) and is active in international research networks related to next-generation multimedia networking and cloud-based media delivery.
Fulvio Giovanni Ottavio Risso is a Full Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, where he is a member of the NETGROUP Computer Networks Research Group and leads research in cloud, edge, and software-defined networking. He is the Scientific Advisor of the European EIT Digital Partnership and serves as a representative for Politecnico di Torino in EIT Digital. He teaches core courses in Computer Engineering, including Cloud Computing Technologies, Enterprise Network Technologies, and Software Networking, and supervises several PhD students in advanced distributed systems. His research focuses on cloud computing, edge computing, network functions virtualization (NFV), software-defined networking (SDN), and high-speed packet processing. He has pioneered work in eBPF-based network functions through the Polycube framework and in computing continuum orchestration via the Liqo project. His interests extend to Kubernetes networking, real-time data plane optimization, and privacy-preserving infrastructure. He has led numerous EU, national, and industry-funded projects, including FLUIDOS (PNRR), NEWTON, RESTART, TOSHI, ASTRID, and NFV@EDGE. His recent work emphasizes liquid computing, borderless data spaces, and secure, scalable network services for 5G/6G. The recent publications reflect a strong trend in edge-to-cloud orchestration, secure and efficient data plane processing, and real-time performance optimization. Key themes include the use of reinforcement learning for scheduling in the computing continuum, Kubernetes-based edge orchestration, eBPF for in-kernel networking, and energy-aware task distribution. Projects like Liqo and Polycube are central to his vision of a programmable, fluid infrastructure. The integration of machine learning, real-time monitoring, and open-source frameworks underscores a commitment to practical, scalable solutions in modern distributed systems. Scientific Awards and Recognitions: No explicit awards listed in the provided text. Advising and Grants: Fulvio Risso supervises multiple PhD students including Attilio Oliva, Daniele Cacciabue, Davide Miola, Jacopo Marino, Stefano Galantino, Carlos Mateo Risma Carletti, and Federico Parola, whose research spans cloud-edge continuum, vehicular micro-clouds, and Kubernetes networking. He has led over 30 competitive and commercial research projects, including EU-funded initiatives (H2020, EIT), national PRIN projects, PNRR missions, and industry contracts with Rakuten Mobile. These grants focus on network programmability, edge computing, 5G/6G observability, anomaly detection, and secure orchestration, reflecting strong industry-academia collaboration. Labs and Research Groups: He is a key member of the NETGROUP - Computer Networks Group (DAUIN) and leads research activities in LAB 9 - Research Laboratory (DAUIN). He is also associated with the Interdepartmental Center PIC4SeR - PoliTO Interdepartmental Center for Service Robotics. His work is deeply integrated with open-source development, particularly through Liqo and Polycube, which are actively used in both research and industrial deployments.
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
