جستجوی استاد راهنمای دانشگاهی

• Knowledge Engineering
• Ontology-based Systems
• Human-Centric Systems
• +۶ مورد دیگر

Dr Flavio Pileggi is a Senior Lecturer in Computer Science at the University of Technology Sydney (UTS), Australia, since July 2023. Previously, he served as Lecturer in Computer Science (2021–2023) and Information Systems (2017–2021) at the same institution. Education: Ph.D. in Computer Networks (Cum Laude), Universitat Politècnica de València, Spain (2011) M.Sc. in Computer Engineering, Università della Calabria, Italy (2005) As a specialist in Knowledge Engineering and Ontology-based Systems, his research focuses on human-centric socially sustainable solutions, particularly socio-technical systems, sustainable development, and climate change. His work bridges technical innovation with socio-economic and environmental value creation. Recent publications explore uncertainty in clustering algorithms, AI ethics, digital twins with ontologies, and socio-technical impacts of AI in education. His 15 most recent articles (2021–2025) span topics like self-reported data risks, smart technology adoption in rural regions, and pandemic resilience metrics. Scientific Awards: Best Paper Award at ICWMC 2006 Teaching Awards from AEMG Education (2022, 2024) He actively supervises PhD/Masters students and participates in 10+ funded collaborative research projects, including grants from UTS MCR Research Capabilities Development Initiative (2025) and CSIRO Next Generation Graduates Program (2024–2027). Currently, he serves on the editorial board of Sustainability (MDPI).

Martin J. Hayesمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Wireless Communications
• +۵ مورد دیگر

Professor Martin J. Hayes serves in the Department of Electronic and Computer Engineering at the University of Limerick's Faculty of Science and Engineering. His institutional affiliation includes campus location ERB2-021 and contact details: email Martin.J.Hayes@ul.ie and phone +353 (0)61 202577. His research concentrates on Artificial Intelligence and Computer Vision applications within Smart Manufacturing and Autonomous Vehicles . Key specialties include deep learning for defect detection, visual question answering systems, and real-time failure monitoring in industrial environments. He also investigates interoperable IoT security frameworks and private 5G network implementations for Industry 4.0. Analysis of recent publications (2023-2025) reveals dominant themes in AI-driven manufacturing solutions and autonomous driving technologies. His work consistently addresses data-constrained training environments and real-time performance requirements, with growing emphasis on human-machine interaction patterns and subjective evaluation frameworks for vision systems. Scientific Awards: No scientific awards were documented in available sources Advising and Grants: While specific student advisement records and grant details were not provided, Professor Hayes' extensive publication output across manufacturing automation, autonomous systems, and wireless communications indicates active leadership in multiple research initiatives. His involvement in the REEdI (Rethinking Engineering Education in Ireland) project demonstrates commitment to educational innovation alongside technical research.

Maria Del Rio-Chanonaمشاهده پروفایل

استادیار

• Network Science
• Machine Learning
• Large Language Models
• +۱۱ مورد دیگر

Maria Del Rio-Chanona is an Assistant Professor in the Department of Computer Science at University College London, where she conducts interdisciplinary research at the intersection of economics, computer science, and complex systems. Her academic journey began with a BSc in Physics from UNAM, Mexico, followed by a DPhil in Mathematics from the University of Oxford, where she was part of the Complexity Economics group at the Institute for New Economic Thinking at the Oxford Martin School. Her research spans multiple critical domains including network science, machine learning, large language models, and agent-based modeling, with applications to the future of work, net-zero transition economics, and the economic impacts of both AI and the Covid-19 pandemic. She has developed innovative methodologies that integrate economic and epidemic models, created data-driven network models of labor markets, and pioneered the use of large language models for economic analysis and historical benchmarking. Dr. Del Rio-Chanona's recent work demonstrates a clear trajectory toward increasingly sophisticated applications of AI in economic modeling, with significant contributions to understanding how generative AI reshapes freelance markets, how LLMs can model financial market behavior, and how to assess AI's capabilities through historical knowledge benchmarks. Her research shows consistent growth in methodological sophistication, moving from traditional economic modeling toward cutting-edge AI applications. JSMF Research Fellow at Complexity Science Hub, Vienna Visiting Scholar at Harvard Kennedy School's Growth Lab Collaborator with International Monetary Fund and International Labour Organisation She actively supervises PhD students in computer science with research projects focused on AI, networks, and economic modeling. Her work has been supported by multiple research grants, including projects modeling well-being impacts of natural disasters and analyzing employment dynamics during rapid decarbonization. She maintains active research collaborations across institutions including the Complexity Science Hub Vienna, Harvard Growth Lab, and Oxford Martin School.

• Cloud orchestration at the level of applications
• Cloud native application development
• Edge-fog-cloud systems management
• +۷ مورد دیگر

Professor Tamas Kiss is a distinguished academic at the University of Westminster, serving as Professor of Distributed Computing at the School of Computer Science and Engineering. He holds dual leadership roles as Director of the Research Centre for Parallel Computing and Director of Research and Knowledge Exchange at his School. Since 2020, he has been Editor in Chief of the Journal of Grid Computing published by Springer Nature. His research focuses on cloud orchestration at the application level, cloud native application development, and edge-fog-cloud systems management. He has developed significant solutions including the MiCADO cloud orchestrator for microservices-based applications, the CloudSME and CloudiFacturing platforms for manufacturing companies, and the PITHIA e-Science Centre for space physics research. These innovations have been adopted by over 100 companies, generating substantial economic impact. Professor Kiss has secured over £65 million in research funding and led more than 20 European and UK-funded projects. His publication record includes over 150 scientific papers in top journals and conferences. Current major projects include STEP-UP (UKRI EPSRC), Swarmchestrate, ARCAFF, HARPOCRATES, and PITHIA-NRF. His research outputs demonstrate a clear progression from foundational grid computing work to current focus on cloud-edge continuum orchestration and industry 4.0 applications. The most recent publications (2023-2025) emphasize decentralized application frameworks, privacy-preserving machine learning at the edge, and interoperable data analytics for digital twin manufacturing. Professor Kiss actively supervises doctoral researchers working on cutting-edge topics including swarm-based orchestration, federated learning in resource-constrained environments, and NFC implementation in industrial IoT systems. His leadership extends to directing the Centre for Parallel Computing, which focuses on cloud computing, distributed computing, high performance computing, and cloud-based simulation for manufacturing.

• Textile Design
• Sustainable Design
• Material Science
• +۴ مورد دیگر

Brigitt Antonia Egloff serves as Lecturer and Deputy Head of Textile Design at Lucerne University of Applied Sciences and Arts (HSLU) within the School of Design, Film and Art. With continuous teaching since 1999 in the BA Textile Design program and from 2012-2018 in the Master's program, she maintains active research and teaching roles while leading international collaborations with institutions including National Institute of Design (India), Beijing Institute of Fashion Technology, and Sichuan School of Fine Arts (China). Her research centers on sustainable material strategies, specializing in textile recycling systems, natural fiber applications, and innovative color systems for solar photovoltaics. She pioneers the cross-disciplinary integration of textile design methodologies into non-textile domains—particularly solar energy systems—while emphasizing the symbiotic relationship between research and pedagogy. Current projects explore circular economy frameworks, sustainable medical textiles, and architectural solar integration. Recent publications reveal strong thematic focus on circular textile design (33% of recent output), solar-textile integration (27%), and sustainable manufacturing processes (20%), with growing emphasis on medical applications and cross-cultural design pedagogy. Her work consistently bridges theoretical research with industrial implementation through Innosuisse projects. Egloff's artistic contributions have earned significant recognition: Berlin Studio Fellowship for Artistic Work (2017) Chicago Studio Fellowship for Artistic Work (2017) Artistic Work Grant (2008) Artistic Work Grant (1998) She directs multiple interdisciplinary research initiatives including CIMProW (Circular Innovation: Medical Protective Wear), Solar Design Tools, and Textile Recycling 4.0, collaborating with EMPA, SUPSI, and textile industry partners. Her leadership extends to the Textile Design program's Examination Board and supervision of student research in sustainable material innovation. Current projects like Circle Up Textiles 2 and SpinnLab demonstrate her commitment to closing textile waste loops through industrial-academic partnerships. As Deputy Head of Textile Design since 2010, Egloff shapes curriculum development and research strategy within HSLU's Textile Design Lab, fostering student engagement with real-world sustainability challenges through projects like Viscosilab and TESS (Textile Eco System Sleep). Her 'Design and Sustainability' framework informs both pedagogy and industry collaborations.

Konstantinos A. Tsintotasمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Computer Vision
• +۹ مورد دیگر

Konstantinos A. Tsintotas is an Assistant Professor at the Department of Information and Electronic Engineering, International Hellenic University. His research focuses on artificial intelligence, robotics, computer vision, and their applications in smart cities, healthcare, and manufacturing. He is actively involved in advancing AI-driven systems for critical infrastructure management, robotic vision, and embedded device technologies. His work spans theoretical advancements and practical implementations, including projects like SLAM algorithms for autonomous navigation, deep learning models for medical diagnosis, and IoT-integrated smart supply chains. Tsintotas also explores ethical implications of AI in human action recognition and contributes to neuromorphic computing through spiking neural networks. Key technical contributions include ReJSHand (real-time hand pose estimation), fall detection systems for embedded devices, and visual place recognition frameworks. His interdisciplinary approach bridges computer science, electrical engineering, and biomedical applications, reflecting a strong commitment to innovation at the hardware-software interface. Notable trends in his publications emphasize AI ethics, multimodal perception for robotics, and low-power embedded solutions. Ongoing work includes advancing digital twin technologies for supply chains and refining bio-inspired neural architectures for robotics applications.

• Robotics
• Human-Robot Interaction
• Control Systems
• +۵ مورد دیگر

Michael Hofbaur is a full Professor at the University of Klagenfurt, where he works in the Institute for Intelligent Systems Technologies within the Faculty of Technical Sciences. His office is located at Lakesidepark Haus B04, Ebene 2, Raum B04.2.206, and he can be contacted at michael.hofbaur@aau.at. Professor Hofbaur has established himself as a leading researcher in robotics with particular expertise in human-robot collaboration, safety systems, and formal verification methods for robotic applications. His research interests focus on the intersection of robotics, safety engineering, and human factors. Professor Hofbaur has made significant contributions to the field of robot safety, particularly in developing methods for safe human-robot collaboration without physical barriers. His work spans multiple dimensions of robotics including kinematic analysis, motion planning, sensor integration, and formal verification techniques to ensure system reliability. He has published extensively on topics such as obstacle avoidance strategies, proximity perception systems, and methods to enhance flexibility in collaborative workspaces while maintaining safety standards. Analysis of his recent publications reveals a clear trend toward integrating formal verification methods with practical robotics applications, particularly focusing on safety-critical aspects of human-robot interaction. His research increasingly incorporates advanced sensing technologies like radar and capacitive proximity sensors to create more intelligent and responsive robotic systems. The work demonstrates a progression from theoretical kinematic analyses toward practical implementations in industrial and collaborative settings, with a consistent emphasis on safety assurance throughout. Professor Hofbaur's research portfolio includes numerous projects related to robotic safety, formal verification, and human-robot collaboration, though specific awards directly attributed to him are not listed in the available materials. His work appears to have significant practical applications in industrial automation and collaborative robotics settings. While specific information about his students and advising activities isn't provided in the available materials, his extensive publication record spanning over two decades suggests he has likely supervised numerous graduate students and postdoctoral researchers. His research activities indicate involvement in both theoretical and applied projects, potentially including collaborations with industry partners given the practical nature of many of his publications. Based on his departmental affiliation and research focus, Professor Hofbaur is likely associated with robotics laboratories at the University of Klagenfurt that specialize in human-robot interaction, safety systems, and formal verification of robotic workflows. These facilities likely include experimental setups for testing collaborative robots, sensor integration systems, and simulation environments for verifying robotic behaviors before physical implementation.

• Human Factors Engineering
• Ergonomics
• Virtual Reality in Training & Education
• +۵ مورد دیگر

Shuchi Deb is an Associate Professor of Industrial, Manufacturing, and Systems Engineering at the University of Texas at Arlington, where she has served since 2019 and was promoted to Associate Professor in September 2024. She directs an active, grant-funded research program that blends human-factors engineering, virtual & augmented reality, and transportation safety to improve human-system interaction across manufacturing, education, and public-safety domains. Education: Ph.D. in Industrial & Systems Engineering, Mississippi State University, 2017 M.S. in Industrial and Management Engineering, Montana State University, 2014 B.Sc. in Industrial and Production Engineering, Shahjalal University of Science & Technology (Bangladesh), 2006 Research & Innovation: Deb’s scholarship focuses on human-centred design of complex socio-technical systems. She exploits immersive technologies—virtual, augmented and mixed reality—to study and enhance safety, training transfer, and user experience in contexts ranging from automated-vehicle interactions and cyclist–infrastructure compatibility to additive-manufacturing education and police reality-based training. Her work repeatedly integrates psychophysiological sensing (EEG, eye-tracking, facial-expression analysis) with usability engineering to create adaptive, trustworthy human-machine interfaces. Recent federally supported projects include an NSF grant to build a bilingual VR platform for additive-manufacturing education ($837 k), a USDOT project developing a driver-readiness monitor for prolonged automated driving, and a Department of Justice award with the Fort Worth Police Department to create VR-based reality training scenarios ($269 k). These grants exemplify her translational approach: coupling rigorous human-factors experimentation with deployable technological solutions. Scientific Recognition: Outstanding Contribution & Mentorship Award, UT Arlington (2024) Best Graduate Student Paper, Mississippi State University (2017) IIE/FlexSim Simulation Competition Winner (2016) SEMS Best Student Paper, IISE (2016) Annual Ergonomics Design Competition, Auburn University (2015) Advising & Grant Leadership: Deb has chaired or served on more than a dozen Ph.D. and M.S. thesis committees and mentored over twenty undergraduate researchers. Since 2019 she has attracted > US $2.3 million in external funding as PI or Co-PI, supporting a broad cohort of graduate researchers who disseminate their work annually at ASEE, IISE, HFES, TRB, and AHFE conferences. Labs & Teams: She founded and advises the Human Factors Lab at UT Arlington, a shared facility equipped with VR headsets, motion-capture systems, driving and cycling simulators, and psychophysiological recording suites. The lab collaborates with industry (Fort Worth Police, local manufacturers) and across campus (Computer Science, Mechanical & Aerospace Engineering) to provide interdisciplinary training to students.

Omid Maghazeiمشاهده پروفایل

استادیار

• Digital Transformation
• Manufacturing Technologies
• Emerging Technologies in Industry
• +۳ مورد دیگر

Omid Maghazei is a Lecturer (Assistant Professor) at the University of Bath's School of Management, with affiliations to the Centre for Future of Work, The Foundry: Centre for Digital, Manufacturing & Design, Smart Warehousing and Logistics Systems, and Information, Decisions & Operations. He holds a Doctor of Science in Management, Technology, and Economics from ETH Zürich (2016–2021). His research focuses on digital transformation, emerging technologies in manufacturing (e.g., drones, mixed reality), Industry 4.0, and servitization. He explores topics like technology piloting frameworks, human-technology cooperation, and supply chain innovation through case studies in sectors like healthcare and construction. His work contributes to UN Sustainable Development Goals related to industry, innovation, and infrastructure. He is actively advising doctoral students and contributes to academic communities via conference proceedings and peer-reviewed journals. Education: PhD in Management, Technology & Economics (ETH Zürich, 2021) Affiliations: Centre for Future of Work, The Foundry, Smart Warehousing Systems Research interests prioritize practical applications of cutting-edge technologies in manufacturing processes, emphasizing digital transformation strategies, human-centric factory design, and agile development methodologies. His work bridges theory and practice through collaborative projects with industry partners like IKEA and piping system manufacturers. Publications highlight themes like drone adoption in warehouses, mixed reality applications on shop floors, and frameworks for human-technology collaboration. He advocates for innovative pilot testing approaches to ensure scalable technology integration. Advising and grants: Accepting doctoral candidates focusing on emerging technologies and manufacturing systems. No specific grants listed but engaged in cross-disciplinary research initiatives. Labs/Teams: Part of interdisciplinary teams at The Foundry and Smart Warehousing, collaborating on digital manufacturing and logistics innovations.

Yu Baiمشاهده پروفایل

استاد

• Composite structures
• Modular construction
• Fiber-reinforced materials
• +۴ مورد دیگر

Professor Yu Bai is a Professor in Structural Engineering at Monash University's Department of Civil and Environmental Engineering, part of the Faculty of Engineering. He holds a B.E. and M.E. from Tsinghua University and a Ph.D. from the Swiss Federal Institute of Technology Lausanne (EPFL). His research focuses on composite materials, modular construction, robotics in construction, and structural resilience under extreme conditions. He directs the Smart Structures and Construction research theme and leads the Laboratory of Robotic Construction. Key research pillars include: Composite materials for lightweight structures Modular design and manufacturing Construction automation and robotics Prof. Bai has secured major grants including an ARC Discovery Early Career Researcher Award and leads projects in sustainable construction, fire dynamics of composites, and robotic fabrication. He collaborates internationally and has over 290 peer-reviewed publications. Teaching responsibilities include courses on structural design and bridge engineering. His labs integrate cutting-edge facilities for structural testing and robotic systems. Awards include recognition for advancing prefabricated housing and low-carbon construction technologies. Current initiatives include the ARC Training Centre for Advanced Manufacturing of Prefabricated Housing and Building 4.0 CRC for smart construction innovations.

Rikke Vestergaard Matthiesenمشاهده پروفایل

دانشیار

• Advanced Manufacturing Technologies
• Lean Production
• Healthcare Operations
• +۳ مورد دیگر

Rikke Vestergaard Matthiesen is an Associate Professor at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University. Her research focuses on Advanced Manufacturing Technologies, Lean Production, Healthcare Operations, and Machine Learning Applications. She leads and participates in projects addressing topics like surgical duration prediction, Industry 4.0 capabilities, and quality management in healthcare laboratories. Key projects include 'TEFFIC: Transforming Educational Programmes For Future Industry 4.0 Capabilities' (2018–2021) and 'Optimization of Quality Management Systems in Hospital Laboratories' (ongoing). She has collaborated on the 'International Manufacturing Strategy Survey 2013' and contributed to understanding Lean transformation challenges in multinational companies. Her research outputs span over 29 publications, including studies on machine learning applications in healthcare and manufacturing strategy formation. Recent work explores the I4 technology-performance link and operational efficiency in surgery planning. She is actively involved in academic activities, workshops, and media engagements, emphasizing the practical implications of technological adoption without overpromising outcomes. Labs and teams include the Center for Industrial Production and the FoCHO (Healthcare Operations) initiative. Current research emphasizes data-driven decision-making in healthcare and manufacturing, with a focus on employee satisfaction and quality improvement.

Matteo Rinaldiمشاهده پروفایل

استاد

• Micro/Nanoelectromechanical Systems (M/NEMS)
• Piezoelectric and Ferroelectric Materials
• Nanoscale Sensors
• +۵ مورد دیگر

Matteo Rinaldi is a Professor in the Department of Electrical and Computer Engineering at Northeastern University's College of Engineering and serves as Director of the Institute for NanoSystems Innovation. His work focuses on advanced micro/nanoelectromechanical systems (M/NEMS) for sensing and communication applications. Ph.D. in Electrical and Systems Engineering, University of Pennsylvania (2010) M.Sc. and B.S. in Electronic Engineering, University of Rome Tor Vergata (2007, 2004) Research Interests: Rinaldi's research spans fundamental and applied aspects of piezoelectric nanomaterials, with emphasis on Aluminum Nitride (AlN) and Scandium Aluminum Nitride (ScAlN) based NEMS Plasmonically enhanced infrared and chemical sensors Low-power reconfigurable radio communication systems Integration of MEMS/NEMS with electronics Nanomaterials for harsh environments Publications & Research Trends: Rinaldi's recent work explores high-frequency resonators, infrared detection systems, and zero-power sensing technologies. Key trends include plasmonics for energy-efficient devices, ScAlN integration for improved performance, and machine learning applications in nanoscale device design. Scientific Recognition: 2025 IEEE IFCS Walter G. Cady Award 2024 Northeastern Global Network Accelerator Award Optica Fellow IEEE Sensors Council Early Career Award DARPA Young Faculty Award NSF CAREER Award Advising & Funding: Rinaldi advises graduate researchers like Antea Risso. His lab secures major grants from DARPA, NSF, DOE, and the Bill & Melinda Gates Foundation, focusing on next-generation sensing technologies and 6G communication systems. Research Infrastructure: Leads the Northeastern Sensors & Nano Systems Laboratory (NS&NS Lab) and co-directs the bicoastal Institute for NanoSystems Innovation with Boston and Oakland campuses, advancing nanoscale semiconductor technologies.

• Human-Computer Interaction
• Affective Computing
• Multimodal Interaction
• +۴ مورد دیگر

Overview Gualtiero Volpe is a Professor affiliated with the Department of Informatics at the University of Genoa, Italy. His research focuses on Human-Computer Interaction (HCI), Affective Computing, and Multimodal Interaction, with particular emphasis on analyzing social interactions, embodied cognition, and expressive movement qualities in contexts such as music performance and education. He has collaborated extensively with researchers like Antonio Camurri, contributing to interdisciplinary projects that bridge computer science, cognitive science, and the arts. Research Interests Analysis of human movement and affect through computational methods Design of multimodal interactive systems for education and healthcare Investigation of laughter and social dynamics in human interactions Development of technologies for music performance and collaborative creativity Key Contributions Volpe's work spans over 140 publications in top-tier venues such as IEEE Transactions on Affective Computing, ACM Conference on Human Factors in Computing Systems (CHI), and International Conference on Multimodal Interaction (ICMI). His research has led to innovations in: Automated analysis of movement qualities using machine learning Sonification platforms for exergames and rehabilitation Embodied interaction frameworks for children's education Computational models of group cohesion and synchronization Recent Trends in Publications Recent studies emphasize the integration of cognitive science principles into movement analysis and the application of multimodal systems to address challenges in post-pandemic social interaction (e.g., digital commensality). His work on 'Embodied Multisensory Training' and 'Hybrid Co-Working in Industry 5.0' highlights a growing focus on real-world applications of HCI research. Awards & Grants No specific awards or grants are explicitly mentioned in the provided data, though his prolific publication record and leadership in collaborative projects suggest sustained academic recognition and funding support. Labs & Teams Volpe is part of the EyesWeb XMI research group at the University of Genoa, developing open-source platforms for real-time multimodal interaction analysis. He collaborates with institutions like the University of Trento and Goldsmiths, University of London on projects related to music technology and social robotics.

• Composite Materials
• Additive Manufacturing
• Finite Element Analysis
• +۳ مورد دیگر

Joris J.C. Remmers is an Associate Professor of Composite Materials at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI High Tech Systems and leads the Mechanics of Materials research group. His academic journey includes a MSc in Aerospace Engineering (TU Delft, 1998) and a PhD in Computational Mechanics (TU Delft, 2006). Remmers' research focuses on composite materials and additive manufacturing, particularly the relationship between manufacturing processes, microstructure, and mechanical properties. He employs advanced numerical techniques to study multi-physics phenomena across scales. Research Themes: Composite materials and fiber-reinforced systems 3D printing and additive manufacturing processes Numerical methods (e.g., finite element analysis, model order reduction) Micromechanical modeling of material behavior Grants and Projects: Project Manager for Innovation test bed for development and production of nanomaterials for lightweight embedded electronics (2019–2023) Awards: Emerging DMD Based Systems and Applications Best Paper Award (2025) Teaching: Leads courses on advanced manufacturing, computational mechanics, and data-driven approaches in engineering, including Advanced and Additive Manufacturing and AI-assisted innovation in portable plasma technology . Labs/Teams: Active in the Mechanics of Materials group, collaborating on multi-scale mechanics, damage modeling, and material failure analysis.

Xiaodong Chengمشاهده پروفایل

استادیار

• Control Systems
• Optimization
• Machine Learning
• +۵ مورد دیگر

Xiaodong Cheng is an Assistant Professor at the Mathematical and Statistical Methods (Biometris) group in the Department of Plant Science at Wageningen University & Research. His research focuses on control systems, optimization, and machine learning, with applications in agricultural and energy systems. He holds a Ph.D. (cum laude) from the University of Groningen, under Prof. Jacquelien Scherpen, and prior roles include Research Associate at the University of Cambridge and Postdoctoral Researcher at Eindhoven University of Technology. Education: B.S. and M.E. from Northwestern Polytechnical University, China (2011, 2014) Ph.D. (cum laude) in Engineering from the University of Groningen, Netherlands (2018) Research Interests: Data-driven modeling, dimensionality reduction, learning-based control, system identification, and applications in agriculture and energy. He emphasizes practical implementations through tools like SYSDYNET and Bayesian neural ODEs for greenhouse systems. Key Contributions: His work spans model reduction for network systems, fault-tolerant control, and stochastic MPC for greenhouse production. Recent trends in his publications highlight advancements in resilient microgrid control, precision agriculture via drone-based sensing, and Bayesian methods for dynamic systems. Awards: Automatica Paper Prize Award (2017–2019) IEEE Transactions on Control Systems Technology Outstanding Paper Award (2020) Labs/Teams: Leads the Biometris group's efforts in integrating control theory and machine learning for sustainable systems. His work often collaborates with agricultural and energy sector stakeholders for real-world impact.