Antonio Candea Leite is an Associate Professor at the Department of Mechanical Engineering and Technology Management, Norwegian University of Life Sciences (NMBU). His research focuses on adaptive and robust control systems, visual servoing, robot manipulators, and agricultural robotics applications. His work emphasizes: Development of autonomous navigation systems for agricultural robots Integration of computer vision for precision agriculture tasks Control strategies for uncertain robotic systems Automation in food quality measurement and pest management Advanced sensor integration for manufacturing processes Recent research trends show strong emphasis on: CNN-based crop row detection for autonomous navigation (2024) Human-robot collaboration frameworks for fruit picking (2024) Robotics solutions for fatty acid measurement in food production (2023-2022) Precision pest control systems using smart automation (2023) No scientific awards or grants are explicitly listed in the provided information. He is actively involved in advising and developing robotic platforms for agricultural and industrial applications without specific student names mentioned here.
Emil Erik Bay Østergaard is a Postdoc researcher at the Department of Physics, Technical University of Denmark (DTU), specializing in Quantum Physics and Information Technology. His work bridges theoretical quantum computation and biomimetic fluid dynamics. His research focuses on quantum computing architectures and natural fluid-structure systems . Key areas include measurement-based quantum computing using high-dimensional cluster states, fault-tolerant photonics implementations, and biomimetic flow control mechanisms inspired by plant physiology. His interdisciplinary approach integrates quantum information theory with biological fluid dynamics. Notable scientific contributions include foundational work on 3D cluster states for optical quantum computing and investigations into how biomimetic structures manipulate fluid flow. His publications demonstrate expertise spanning quantum information processing and bio-inspired engineering solutions. During his PhD (2022-2025), he led the project Measurement based optical quantum computing using a 3D cluster state under supervisors U. L. Andersen and J. S. Neergaard-Nielsen, achieving significant results in quantum error correction and photonics implementation. He maintains active collaborations across quantum physics and fluid dynamics domains, with research impacting both quantum information science and biomimetic engineering applications.
Ivan MARRI is an Associate Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering Sciences and Methods. His research focuses on theoretical physics, materials science, and computational chemistry, with a strong emphasis on nanocrystals and low-dimensional systems. He investigates the electronic and optical properties of silicon, germanium, and their alloys, exploring applications in photovoltaics and optoelectronics. His work leverages ab initio calculations and density functional theory to study quantum confinement effects, carrier dynamics, and surface chemistry. Dr. Marri teaches courses in High Performance Computing for Advanced Physical Analysis, Physics II, and Physics of Bodies, emphasizing numerical methods, parallel computing, and fundamental physics principles. His research spans topics such as carrier multiplication in silicon nanocrystals, strain effects in GeSi core-shell systems, and work function modulation in semiconductor surfaces. His publications highlight contributions to understanding nanocrystal interactions, exciton dynamics, and the role of surface functionalization in material properties. While no specific awards are listed, his extensive body of work reflects a deep engagement with theoretical and computational materials science.
Jacqueline Scherpen is a Professor at the University of Groningen, affiliated with the Discrete Technology and Production Automation department in the Faculty of Science and Engineering. She serves as Director of Engineering and Captain of Science for the Dutch High Tech Systems and Materials (HTSM) sector. Her expertise spans nonlinear control, model reduction, and smart energy systems, with applications in electromechanical systems and networks. She holds an MSc and PhD from the University of Twente (1990, 1994) and has held roles at TU Delft and leadership positions at ENTEG (2013-2019). She is an IEEE Fellow, editor for IEEE Transactions on Automatic Control , and received prestigious awards including the Prince Friso Prize (2023) and the Automatica Best Paper Prize (2020). Her research focuses on energy-based control, passivity, and Hamiltonian systems. Recent work includes port-Hamiltonian frameworks, distributed control for smart grids, and model reduction techniques for nonlinear networks. She actively contributes to IFAC and SIAM, emphasizing interdisciplinary collaboration and sustainable development goals.
Prof. Alin Albu-Schäffer is a Professor at the Technical University of Munich (TUM) and Director of the DLR Institute of Robotics and Mechatronics. He holds the Chair of Sensor-Based Robot Systems and Intelligent Assistance Systems. His research focuses on robot design, control, and human-robot interaction, emphasizing safe and adaptive systems for diverse applications like space exploration, healthcare, and industrial automation. Education: MS in Electrical Engineering, Technical University of Timisoara, Romania (1993) PhD in Automatic Control, TUM (2002) Key Research Areas: Robot design and control Nonlinear control systems Bio-inspired robotics Medical and surgical robotics (e.g., MIRO system) Planetary exploration robotics Awards: ERC Advanced Grant (2019) for the M-Runners project IEEE Fellow (2018) IEEE King-Sun Fu Best Paper Award (2012, 2014) Grants & Leadership: Leads the DLR Institute and a robotics research group at TUM. Pioneered the DLR Lightweight Robot and its industrial transfer to KUKA, revolutionizing lightweight robotics. Co-developed the MIRO surgical robot commercialized via Medtronic. Labs/Teams: DLR Institute of Robotics and Mechatronics MIRO Innovation Lab
Gary Nave is an Assistant Teaching Professor in Mechanical Engineering at Colorado School of Mines (2022–present), focusing on dynamics and robotics education while developing advanced courses. Previously, he held postdoctoral roles at the University of Colorado Boulder’s BioFrontiers Institute (2018–2020) and Northwestern University’s Department of Engineering Science and Applied Mathematics (2020–2022). He earned his Ph.D. in Engineering Mechanics from Virginia Tech (2018) and B.S. in Engineering Science and Mechanics from the same institution (2012). His research integrates nonlinear dynamical systems, collective behavior modeling, and fluid dynamics . Key areas include: Swarm intelligence in honeybees and fire ants Pain dynamics in sickle cell disease (SCD) Biomimetic seed dispersal mechanisms Fluid-structure interactions in biological systems Recent work includes x-ray CT analysis of honeybee swarm structures and SCD pain pattern clustering from sparse data. He has mentored students across levels, including undergraduates and high schoolers in STEM programs.
Professor Il-Min Kim is a Full Professor in the Department of Electrical and Computer Engineering at Queen's University (Smith Engineering). He leads the Wireless Artificial Intelligence Laboratory (WAI Lab), focusing on AI-driven wireless systems, IoT/IoE/IIoT, federated learning, edge computing, and 6G/V2X communications. His work integrates machine learning, signal processing, and cybersecurity with wireless infrastructure. Education: B.S. (Yonsei University, 1996), M.S./Ph.D. (KAIST, 2001). Postdoctoral research at MIT (2001-2002) and Harvard (2002-2003) preceded his faculty role at Queen's since 2003. Promoted to Associate Professor (2009) and Full Professor (2014). Research emphasizes Wireless AI , including on-device AI, federated learning, geoscience AI (Geo-AI), and secure communication protocols. Key areas: AI for 6G/V2X, energy-efficient edge computing, and robust spectrum sensing. His lab develops frameworks for distributed systems, compressive sensing, and nonlinear energy harvesting. Notable contributions include hybrid replay mechanisms for incremental learning, diffusion models for industrial IoT, and deep learning-based channel estimation. His work addresses challenges in data security, model robustness, and real-time inference under resource constraints.
Dr. Guanghui Ren is a Senior Research Fellow in the Department of Research & Innovation at RMIT University. His work focuses on advanced photonics, including integrated photonics, silicon photonics, and lithium niobate-based devices. He specializes in optoelectronics, hybrid integration, micro-nano fabrication, and optical sensors. Ren has pioneered research in photonic circuits, mode conversion, and sensing technologies using 2D materials and chalcogenide glasses. His research interests span optical biochemical sensors, ultra-wideband microwave systems, and reconfigurable photonic architectures. Notable contributions include high-Q mid-infrared ring resonators, poling-free wavelength conversion, and room-temperature gas sensors. Ren actively supervises PhD and Master's students in topics like photonics integration and materials upcycling. He holds an ORCID identifier and is a Senior Member of the IEEE. Recent work includes breakthroughs in lithium niobate-on-insulator platforms for mode switching, frequency lattices, and reservoir computing. His interdisciplinary approach bridges material science, optics, and engineering, with applications in environmental sensing, autonomous systems, and telecommunications.
Dr. Christopher Renton is a Senior Lecturer in the School of Engineering at the University of Newcastle, Australia. His expertise spans control systems, robotics, and machine vision. He holds a PhD and Bachelor of Engineering (Mechatronics) from the University of Newcastle. Education: Doctor of Philosophy, University of Newcastle Bachelor of Engineering (Mechatronics)(Honours), University of Newcastle Research Interests: Dr. Renton focuses on dynamical systems, medical robotics, and Bayesian estimation. His work integrates nonlinear control theory, optimization, and machine vision for applications in robotics, automotive systems, and marine vehicles. Current projects include extended target tracking, autonomous navigation, and robust estimation algorithms. Grants & Funding: Total funding: $612,183 AUD. GPS Compromised Navigation ($158,701, Boeing Defence Australia) Robust Autonomous Systems ($411,299, Boeing Defence Australia) Maritime RobotX Challenge - University of Newcastle ($26,654, US Office of Naval Research) Advising & Labs: Principal supervisor for two current PhD students researching Bayesian methodologies in SLAM and state estimation. Part of the Priority Research Centre for Complex Dynamic Systems and Control, focusing on nonlinear systems and robotics.
Professor Jie Bao is a Process Control expert specializing in dissipativity/passivity-based control, particularly for complex industrial systems. He leads the Process Control Research Group at the School of Chemical Engineering, University of New South Wales (UNSW), and directs the ARC Research Hub for Integrated Energy Storage Systems. His research focuses on distributed control systems, energy storage technologies (e.g., flow batteries), aluminum smelting processes, and big data-driven control methodologies. Education: PhD (Process Control) from the University of Queensland, BE and ME from Zhejiang University. Research Grants: Over AUD 18 million in competitive funding, including ARC Discovery Projects, Industry Hubs, and CSIRO collaborations. Notable projects include: ARC Research Hub for Integrated Energy Storage Solutions (AUD 3.189M, 2019–2025) ARC Research Hub for Smart Process Design and Control (AUD 5.312M, 2023–2027) Long Duration Energy Storage Solutions via Vanadium Flow Batteries (AUD 1.815M, 2023–2026) Research Interests: Dissipativity theory, networked control systems, behavioral systems theory, and applications in energy storage, aluminum smelting, and membrane systems. Leadership & Service: Associate Editor for Journal of Process Control and Journal of Franklin Institute . ARC College of Experts member. Serves on the IFAC Technical Committees for Chemical Process Control and Mining/Metal Processing. Teaching: CEIC3006 Process Dynamics and Control, CEIC8102 Advanced Process Control, and mentor for design projects (CEIC4000).
Paola Vivo is a Professor in the Department of Materials Science and Environmental Engineering at Tampere University. Her research focuses on advanced materials for photovoltaics, particularly perovskite-inspired semiconductors and their applications in solar energy systems. She leads projects addressing material stability, environmental impact, and optoelectronic performance in low-toxicity photovoltaic materials. Her work emphasizes perovskite solar cells, halide vacancy engineering, and eco-friendly alternatives to traditional photovoltaic materials. Key contributions include developing stable hole-transport materials, optimizing charge transport in bismuth-based systems, and assessing sustainability of materials for indoor/outdoor photovoltaic applications. Dr. Vivo has published over 100 peer-reviewed articles and contributed to datasets like the 3D-printed cell holder for materials testing. She actively reviews for top journals such as Nature , Advanced Materials , and Journal of the American Chemical Society . Her research aligns with UN Sustainable Development Goals related to affordable clean energy and responsible consumption. Education: Doctor of Science (Technology) in Biotechnology (Tampere University, 2010).
Dr. Linda Hirst is a Professor in the Department of Physics at the University of California, Merced. Her research focuses on the intersection of soft matter physics, active matter, and materials science, with particular emphasis on liquid crystals, nanoparticle assembly, and biological physics. She holds an office in Biomedical Sciences and Physics Building room 161 and can be reached at lhirst@ucmerced.edu. Her work explores complex systems such as self-assembly of quantum dots using liquid crystal phase transitions, dynamics of active nematics with topological defects, and colloidal behavior in anisotropic media. She also investigates biological systems like microtubule-based active fluids and their interactions with motor proteins. Recent projects include controlling chaos in active fluids through boundary engineering and studying the impact of e-cigarette additives on lipid membrane structures via X-ray scattering. Key research themes involve understanding how microstructural features (e.g., ligand-functionalized nanoparticles, phase boundaries) govern macroscopic material properties. Her contributions span experimental, theoretical, and computational approaches, addressing topics from nanoparticle transport mechanisms to the rheology of active fluids. While no specific awards are listed, her extensive publication record reflects a prolific and impactful career in soft condensed matter physics. Her research has implications for novel material design, biophysical systems, and nanotechnology applications.
Professor Lei Su at the School of Engineering and Materials Science, Queen Mary University of London , specializes in photonics with applications spanning healthcare, energy, and security . His work integrates optical devices, optoelectronic materials , and artificial intelligence to advance sensing, imaging, and communication technologies. His research explores multimode fiber optics , perovskite materials , and deep learning-driven photonic systems , focusing on challenges like shape sensing , soliton dynamics , and stability enhancement in optoelectronic devices. Key trends include biomimetic photonics , scalable manufacturing , and AI-enabled signal processing . Professor Su has secured substantial funding from EPSRC , BBSRC , and Innovate UK for projects such as Clock-Chips and Wearable ultrasound sensors . His collaborations emphasize interdisciplinary innovation , bridging materials science , nanotechnology , and biomedical engineering .
Panos J. Antsaklis is the H. Clifford and Evelyn A. Brosey Professor of Electrical Engineering at the University of Notre Dame, with concurrent appointments in the Department of Computer Science and Engineering and the Department of Applied and Computational Mathematics and Statistics. He is a leading figure in systems and control theory, with a sustained focus on autonomy, cyber-physical systems, and networked control. His research interests center on Cyber-Physical Networked Embedded Systems, hybrid and discrete event dynamical systems, and the quest for autonomy in engineered systems. He investigates control strategies for complex, intelligent, and reconfigurable systems using mathematical models and data, with applications in transportation, manufacturing, power systems, and communication networks. His recent work emphasizes passivity, dissipativity, and passivity indices as foundational tools for robust and resilient design. The 15 most recent publications highlight a strong trend in decentralized and distributed control of networked systems, particularly vehicular platoons and supply chains, using dissipativity-based methods and topological co-design. There is a growing integration of machine learning (e.g., graph neural networks) and formal methods (e.g., signal temporal logic) with classical control theory, reflecting the interdisciplinary nature of modern cyber-physical systems. His scientific awards include: IEEE Fellow (1991) IFAC Fellow (2010) AAAS Fellow (2011) IEEE Third Millennium Medal (2000) Brown University Engineering Alumni Medal (2006) University of Lorraine Honorary Doctorate (2012) Notre Dame Faculty Award (2013) Notre Dame Research Achievement Award (2020) Antsaklis has played a pivotal role in the control systems community, serving as Editor-in-Chief of the IEEE Transactions on Automatic Control (2010–2017) and President of the IEEE Control Systems Society (1997). He has supervised numerous PhD students and authored over 600 publications, including foundational textbooks on linear and hybrid systems. He has also been involved in high-level advisory roles, such as on the NSF Cyber-Physical Systems PI Meeting and the President’s Council of Advisors for Science and Technology (PCAST). He leads the Antsaklis Group at Notre Dame, which focuses on autonomy, control, and resilience in networked systems. The group is active in both theoretical development and practical applications, contributing to national initiatives on control for societal-scale challenges.
Dr Nikolaos Athanasopoulos is a Senior Lecturer at Queen's University Belfast, affiliated with the School of Electronics, Electrical Engineering and Computer Science within the Faculty of Engineering and Physical Sciences. His research focuses on systems and control theory, particularly hybrid systems using set-based methods, with applications in cyber-physical systems, robotics, and edge computing. Research interests include cyber-physical systems control, hybrid systems analysis, reachability analysis, and systems subject to communication, computation, and physical constraints. He actively supervises PhD students in these areas and leads projects such as the 'Trans-National Smart Manufacturing Education Hub' and 'Industrial IoT-driven Remote Path Planning (IIoT-REPLAN)'. His recent publications emphasize safety-critical control strategies, trajectory planning for robotic systems, and resilience against cyber-attacks. Notable awards include a Best Paper Award finalist (2018) and a Mathematics category award (2018). He collaborates on interdisciplinary projects, including smart manufacturing, edge robotics, and resource allocation in dynamic networks. His work integrates theoretical advancements with practical applications, aiming to enhance system safety and efficiency in complex environments.
