جست‌وجوی استاد و پژوهشگر

• Remote Sensing
• Lidar Technology
• Forest Ecology
• +۳ مورد دیگر

Dr. Jacqueline Rosette is a Senior Lecturer in the Department of Geography at Swansea University, part of the Faculty of Science and Engineering. Her research focuses on remote sensing applications, particularly LiDAR technology for forestry and environmental monitoring. She has collaborated with institutions globally on projects involving biomass estimation, vegetation height analysis, and satellite data interpretation. Dr. Rosette teaches modules such as GEC140 Project and Field Methods and GEGM03 Drone Accreditation and Remote Sensing , emphasizing practical skills in geospatial data collection and analysis. Her research interests span lidar-based biomass assessment, forest parameter retrieval, and environmental remote sensing. She has supervised PhD students investigating topics like drone-based environmental monitoring, oak decline detection, and sea-level change impacts. Dr. Rosette's work has been published in journals like Global Change Biology , Remote Sensing of Environment , and Nature , showcasing her contributions to understanding forest dynamics and climate change impacts. Dr. Rosette is actively involved in academic supervision, co-supervising research on pathogen infection detection via hyperspectral reflectance and desertification in Iraq through geomatic approaches. Her teaching integrates fieldwork, data analysis techniques, and ethical considerations in geographical research. She also contributes to initiatives like the NASA Carbon Monitoring System and has developed curricula for drone remote sensing certifications aligned with Civil Aviation Authority standards.

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +۵ مورد دیگر

Prof. Gerald Steinbauer-Wagner is an Associate Professor at TU Graz's Institute of Software Engineering and Artificial Intelligence. He specializes in autonomous intelligent systems, focusing on decision-making architectures for robots in uncertain environments. His research integrates software engineering, AI, and robotics to develop reliable systems for applications in disaster response, planetary exploration, and industrial automation. Research Interests: Steinbauer-Wagner's work addresses challenges such as robot navigation in unstructured terrains, human-robot collaboration, and trustworthiness in autonomous systems. Key areas include explainable AI, fault diagnosis, and multi-robot coordination. His team explores solutions for off-road robotics, collective perception, and certification of autonomous systems. Recent Projects: Current initiatives include developing autonomous systems for subterranean rescue missions (ROBO-MOLE), optimizing robot localization using machine learning, and creating educational frameworks for AI literacy in schools. His group also contributes to the RoboCup Logistics League and planetary exploration cascades through analog missions like AMADEE-20. Awards & Recognition: No specific awards listed, but his work has been recognized through extensive publications in top venues like IEEE/RSJ IROS, ICRA, and RoboCup symposiums. Lab & Teams: Leads the Autonomous Intelligent Systems (AIS) research group at TU Graz, collaborating with industry partners like the Smart Factory. His team develops integrated robot systems for production, logistics, and disaster response scenarios.

Álvaro Hernández Alonsoمشاهده پروفایل

استاد

• Mobile Robotics
• Multisensor Integration
• Ultrasonic Sensory Systems
• +۵ مورد دیگر

Álvaro Hernández Alonso is a Full Professor in the Department of Electronics at the University of Alcalá (UAH). He previously served as Secretary of the Electronics Department and coordinated the GEINTRA research group (2021–2023), which includes 24 researchers and over 25 active projects. His research focuses on mobile robotics, multisensor integration, ultrasonic systems, NILM techniques, FPGA implementations, and electronic technologies for transport. Education: PhD in Electronics and Systems (University Blaise Pascal & UAH) Electronics Engineering Degree (UAH) Research interests include positioning systems (infrared, ultrasonic, visible light), energy monitoring for assisted living, and embedded hardware architectures. He has secured €1.9M in funding (public and private) over the past decade, leading 4 projects as Principal Investigator. His work has produced 41 indexed journal papers (25 Q1), 6 patents, and 65 conference contributions. Awards: Best Thesis Awards at UAH for two doctoral students under his supervision. He has advised 30+ student theses and 9 doctoral dissertations, many in international co-supervision programs. Funding highlights: 19 public projects (€900k total) and 10 private projects (€1.1M total). His research has achieved 4 consecutive positive evaluations (1997–2020) from Spain's National Research Evaluation Commission.

Bin ZHUمشاهده پروفایل

استادیار

• Human Centered Multimedia Computing
• Cross-modal Retrieval
• Multi-modal Large Language Models
• +۶ مورد دیگر

Bin ZHU is an Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems. Previously worked as a Postdoctoral Researcher at University of Bristol under EPSRC Visual AI Program Grant with Prof. Dima Damen. PhD in Computer Science (2021) - City University of Hong Kong MSc and BSc from Zhejiang University and Southeast University Research focuses on Human Centered Multimedia Computing with key areas: Cross-modal retrieval and Multi-modal Large Language Models Egocentric Video Understanding and Generative AI AI for Healthcare and Wellness Informatics Digital Transformation through Multimedia Systems Active in publishing at top venues (ICCV, CVPR, AAAI, ACM MM) with specialization in Visual Instruction Fine-Tuning and Adapter Modules. Recent work includes HD-EPIC dataset development and Dual-LoRA framework for efficient multimodal adaptation. Contact: binzhu@smu.edu.sg | bin.zhu@smu.edu.sg

Longzhi Yangمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Cybersecurity
• +۱۱ مورد دیگر

Longzhi Yang is a Professor at Northumbria University’s Department of Computer and Information Sciences, currently serving as Director of Education. He holds a PhD in Computing Science from Aberystwyth University (2011) and has extensive research experience in Artificial Intelligence, Robotics, Cybersecurity, and Manufacturing. His work emphasizes real-world applications under uncertain environments, supported by grants from EPSRC, Innovate UK, and industry partners. Research interests include Computational Intelligence, Machine Learning, Cybersecurity, Robotics, Planning/Scheduling, and Additive Manufacturing. Recent projects focus on energy storage systems, fuzzy logic control, and data-driven robotic systems. He has organized major conferences like the UK Workshop on Computational Intelligence and the IEEE ICMLA. Publications span topics such as reinforcement learning for EVs, fuzzy neural networks, and cybersecurity frameworks. Awards include the Best Paper Award at UKCI 2018 and 2016. He actively supervises PhD students and leads interdisciplinary initiatives like the COVER project for emergency response drones and 3D-printed furniture manufacturing. Education: PhD in Computing Science (Aberystwyth University, 2011) Funding: EPSRC, ESRC, Innovate UK, RAEng Grants: 4 active/funded projects including smart manufacturing and emergency response systems Labs/Teams: Involved in robotics, cybersecurity, and intelligent manufacturing research groups

Huaping Liuمشاهده پروفایل

استاد

• Wireless Communication Systems
• Signal Processing
• MIMO Systems
• +۷ مورد دیگر

Huaping Liu is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University (College of Engineering). He holds a Ph.D. in Electrical Engineering from New Jersey Institute of Technology (1997) and previously worked at Lucent Technologies (1997–2001). His research focuses on wireless communication systems, including MIMO systems, ultrawideband technologies, spread spectrum systems, and channel coding. He has contributed to applications in healthcare monitoring and industrial automation. Education: Ph.D., Electrical Engineering, New Jersey Institute of Technology (1997) M.S., Electrical Engineering, Nanjing University of Posts and Telecommunications (1990) B.S., Electrical Engineering, Nanjing University of Posts and Telecommunications (1987) Research Interests: Wireless communication theories and systems Embodied intelligence and multi-agent robotics Tactile sensing and large-area robotic skin Autonomous navigation and vision-language models Awards and Recognition: 2017 IEEE UEMCON Best Paper Award 2015 OSU College of Engineering Research Collaboration Award 2011 DesignCon Best Paper Award 2010 IEEE VTS Best Paper Award 2007 & 2004 EECS IEEE Professor of the Year Advising and Grants: Dr. Liu emphasizes student-driven learning, fostering critical thinking through inquiry-based teaching. His work involves collaborative projects in robotics, cybersecurity, and sensor systems, supported by grants and industry partnerships. Labs/Teams: Active in developing embodied intelligence frameworks, robotic tactile sensing systems, and cybersecurity solutions for digital twins and vehicular networks. Collaborates on simulation platforms for human-robot collaboration (e.g., HumanTHOR).

Zhang Junمشاهده پروفایل

استاد

• Biological Physics
• Nonlinear dynamics and complex systems
• Soft matter physics
• +۴ مورد دیگر

Zhang Jun is a Full Professor of Physics and Mathematics and Co-director of the Applied Math Lab at the Courant Institute, New York University (NYU), USA. He also serves as Co-director of the NYU-ECNU Joint Physics Research Institute in Shanghai, China, and holds an Affiliated Professorship at NYU Shanghai. His research focuses on experimental fluid physics, particularly fluid-structure interactions in biological and geophysical contexts, including bio-locomotion, flapping wings, and continental dynamics. Zhang has authored over 290 invited talks and peer-reviewed papers in journals like Nature and Physical Review Letters. He received the 2017 APS Fellow award for pioneering work in fluid-structure interactions. Beyond academia, he is a freelance illustrator with plans to publish a book of sketches. Education: PhD in Physics (1994), Niels Bohr Institute, University of Copenhagen PhD Candidate (1990-1991), Hebrew University of Jerusalem BSc in Physics (1985), Wuhan University Research Interests: Zhang’s work bridges physics, biology, and geophysics, exploring phenomena like flapping wing aerodynamics, animal locomotion, and Earth’s core-mantle interactions. His experiments often use novel fluid dynamics setups to model natural systems. Awards: APS Fellow (2017) Milton Van Dyke Award (2014) Antarctica Service Medal (2015) Labs & Teams: Co-directs the Courant Institute’s Applied Math Lab, specializing in fluid dynamics experiments. Collaborates with institutions globally, including NYU Shanghai and Aix-Marseille University.

Ahmad Alsharoaمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Data Science
• +۷ مورد دیگر

Dr. Ahmad Alsharoa is an Assistant Professor of Computer Engineering at the Missouri University of Science and Technology (Missouri S&T). He holds a PhD in Electrical and Computer Engineering from Iowa State University, an MS from King Abdullah University of Science and Technology (KAUST), and a BS from Jordan University of Science and Technology (JUST). He is the founder of the Optimization and Intelligent Wireless Systems (OIWS) Laboratory, focusing on AI-driven smart systems, edge computing, and LiDAR applications in healthcare and transportation. His research interests include machine learning, LiDAR technology, smart cities, reconfigurable intelligent surfaces, and wireless networks. Notable projects include LiDAR-based human activity recognition, energy-efficient UAV relays, and integrated satellite-airborne-terrestrial networks. He has authored over 40 peer-reviewed publications and holds IEEE Senior Member status since 2019. Education : PhD, Electrical and Computer Engineering, Iowa State University (2015-2020) MS, Electrical Engineering, KAUST (2013-2015) BS, Electrical Engineering (with Honors), JUST (2008-2012) Awards : Preeminent Postdoctoral Program (P3) Award, UCF (2018) GPSS Research Award, ISU (2017) Research Excellence Award, ISU (2016) His lab’s work emphasizes practical applications of AI and edge computing, including LiDAR for traffic monitoring, healthcare gesture recognition, and wildfire detection via UAVs. Current research trends focus on LiDAR sensor networks, RIS-enabled 6G systems, and energy-efficient wireless architectures. Grants and collaborations include projects funded by the National Science Foundation and industry partnerships. He advises the OIWS Lab team on advanced wireless systems and serves as a reviewer for IEEE Transactions and conferences.

Pekka Toivanenمشاهده پروفایل

استاد

• Artificial Intelligence
• Healthcare Systems
• IoT and Smart Grids
• +۳ مورد دیگر

Pekka Toivanen is a Professor at the School of Computing, Faculty of Science, Forestry and Technology at the University of Eastern Finland. His research focuses on artificial intelligence, healthcare systems, IoT, cybersecurity, and machine learning. He has contributed extensively to fields like medical image analysis, smart grids, and robotics, with over 100 peer-reviewed publications. His work bridges theoretical advancements and practical applications, such as improving healthcare diagnostics via AI, enhancing IoT security, and optimizing energy management in microgrids. Research Interests: Dr. Toivanen’s primary areas include AI-driven healthcare solutions, cybersecurity for IoT devices, deep learning applications in medical imaging, and energy-efficient smart grid systems. He has pioneered methods for tuberculosis risk prediction and developed novel encryption algorithms for Bluetooth security. Publications: His recent work emphasizes AI in healthcare (e.g., tuberculosis prediction models) and energy systems (e.g., reinforcement learning for microgrid management). He also explores vulnerabilities in wireless technologies like Bluetooth and ZigBee, proposing robust countermeasures. Grants/Teams: Leads projects on AI distribution platforms for healthcare and secure IoT architectures. Collaborates with interdisciplinary teams in medical and engineering domains.

Junghyun Parkمشاهده پروفایل

پژوهشگر

• Seismology
• Geophysics
• Infrasound Monitoring
• +۴ مورد دیگر

Junghyun Park is a Researcher and Associate Director of Research in the Seismo-Acoustic Research Program at Southern Methodist University (SMU). She holds a Ph.D. from SMU (2013) and specializes in geophysical monitoring of manmade seismic and acoustic events, including nuclear explosions, mining blasts, and rocket launches. Her work integrates seismic and infrasound data to quantify source characteristics and improve detection methodologies. Research Interests: Signal detection and localization using seismic/infrasound arrays Source characterization of explosions and environmental events Data quality control for field instruments Atmospheric modeling to enhance infrasound predictions Multi-modal machine learning for seismoacoustic fusion Key Contributions: Developed tools for seismoacoustic array monitoring in South Korea, analyzed North Korean nuclear tests via infrasound inversion, and pioneered unsupervised machine learning for industrial seismic data analysis. Serves as Associate Editor for the Bulletin of the Seismological Society of America since 2021. Grants/Advising: No student advisees listed. Focuses on federal grants related to nuclear nonproliferation and environmental monitoring technologies. Labs/Teams: Leads SMU's seismo-acoustic research arrays and collaborates with international organizations on atmospheric and geophysical data networks.

Victoria Degelerمشاهده پروفایل

استادیار

• Computer Science
• Artificial Intelligence
• Software Engineering
• +۴ مورد دیگر

Victoria Degeler is an Assistant Professor at the University of Groningen’s Faculty of Science and Engineering, affiliated with the Bernoulli Institute. Her research focuses on AI-driven solutions for complex systems, combining expertise in artificial intelligence, software engineering, and service-oriented computing. She actively contributes to EU Horizon initiatives through her role in evaluating projects for the EC REA and EASME. Her work emphasizes real-world applications such as digital twins for infrastructure optimization, machine learning for IoT systems, and adaptive service architectures. Her research interests span digital twins in water distribution networks, quality-aware IoT processing, and machine learning methodologies. Notable projects include developing self-adaptive service selection frameworks and analyzing human activity recognition biases. She collaborates widely, evidenced by co-authored publications in top-tier conferences and journals.

Timothy Horiuchiمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Neuromorphic Engineering
• VLSI System Design
• +۵ مورد دیگر

Dr. Timothy Horiuchi is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Maryland, affiliated with The Institute for Systems Research, Maryland Robotics Center, Brain and Behavior Institute, and Robert E. Fischell Institute for Biomedical Devices. He leads the Computational Sensorimotor Laboratory (CSSL) and contributes to the Microelectronics at Maryland group. His research bridges computational neuroscience and neuromorphic VLSI design, focusing on sensorimotor systems inspired by biological mechanisms like bat echolocation. Education: B.S. and Ph.D. in Electrical Engineering from Caltech (1989, 1997), followed by postdoctoral research at Johns Hopkins University. Industrial experience includes roles at Hughes Aircraft, Boeing, IBM, HP, and Tanner Research. Research interests include bio-inspired neuromorphic systems, acoustic signal processing, mobile robotics, and neural circuit modeling. Recent work explores bio-hybrid robots, acoustic metamaterials, and spike-based navigation algorithms. His NSF-funded projects include the 'ExLENT' experiential learning initiative and the DREEM microelectronics workforce program. Notable achievements: NSF CAREER Award (2004) for bat echolocation modeling, ISR Outstanding Faculty Award (2004), and 2019 Elevate Fellowship to redesign ENEE 303. His lab has pioneered neuromorphic chips for auditory localization, motor control, and spike-sorting tools for neurophysiology. Advising: Supervises graduate students like Nathan Renegar. Grants include contributions to NSF neuroengineering initiatives and collaborative industry partnerships. Current projects address odor-guided drones, Luneburg lens-based acoustic waveguides, and neuromorphic social robots. Labs/Teams: CSSL focuses on sensorimotor systems; Microelectronics group develops advanced VLSI technologies. Collaborations span neuroscience, robotics, and biomedical engineering domains.

• Artificial Intelligence
• Machine Learning
• Edge Computing
• +۴ مورد دیگر

Sergio Moreschini is a Postdoctoral Researcher in Computing Sciences, focusing on Artificial Intelligence, Edge Computing, and MLOps. His research explores the integration of AI techniques in microservices, cloud-edge continuum systems, and distributed home automation frameworks. He has contributed to foundational studies such as a Systematic Mapping Study on AI in Microservices Life-Cycle and developed frameworks like Flexconnect for mobile computational offloading. Education: He holds a Bachelor of Science in Technology (2012) and a Higher-Degree in Computing from Università Degli Studi Roma Tre (2016). His work aligns with UN Sustainable Development Goal 4 (Quality Education) through contributions to educational tools and methodologies. Research Interests : Moreschini investigates AI lifecycle management, edge-cloud system orchestration, vulnerability analysis in open-source components, and generative AI applications in software architecture. Key areas include fault-tolerant distributed systems, cognitive cloud continuum frameworks, and MLOps tool ecosystems. Recent Trends in Publications : Recent work emphasizes MLOps adoption challenges, self-organizing edge computing for visual SLAM, and best practices in resource provisioning for cognitive systems. He has explored trade-offs between continuous training and transfer learning in edge environments, and evaluated vulnerability severity metrics in open-source software. Awards : Won the Best Paper Award in 2022 for contributions to industrial edge service scheduling. Data Contributions : Co-created datasets like RARE (cloud-native memory anomalies) and CIVIT (integral microscopy recordings). His collaborative projects include the 6GSoft initiative for edge-cloud continuum systems and the OSSARA tool for open-source component risk assessment. Active in international conferences like IoT and SEAA, he bridges academic research with industrial applications in edge computing and AI infrastructure.

Peter H. Veltinkمشاهده پروفایل

استاد

• Biomechatronics
• Neural Engineering
• Rehabilitation Medicine
• +۷ مورد دیگر

Professor Peter H. Veltink is a faculty member at the University of Twente, Netherlands, serving as vice-dean of research for the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS). He leads the Biomedical Signals and Systems Group, focusing on biomechatronics, neural engineering, and rehabilitation technologies. His academic career includes a B.Sc., M.Sc. (cum laude), and Ph.D. from the University of Twente, with sabbaticals at Case Western Reserve University and Aalborg University. Research Interests: Biomechatronics and artificial motor control systems Ambulatory sensing for human movement analysis Neurostimulation techniques for neuromodulation Development of wearable sensors for clinical applications Leadership & Projects: Coordinator of major EU projects including INTERACTION (FP7), eNHANCE (H2020), and training networks like ARNESCO. Currently coordinates STW projects PowerSensor and MiniSens, and participates in Symbionics and neuroCIMT programs. Has supervised 42 Ph.D. students with an H-index of 62. Awards & Recognition: Royal Shell Stimulating Prize (1997) for rehabilitation engineering contributions, Adjunct Professor at Northwestern University (since 2015), and Decade of Partnership Award from Xsens (2010). Publications: Over 140 peer-reviewed journal articles and numerous conference papers, with leadership roles at IEEE Transactions on Neural Systems & Rehabilitation Engineering and the International Functional Electrical Stimulation Society (IFESS). Current Focus: Advancing wearable sensor technologies for gait analysis, clinical decision-making in ACL rehabilitation, and improving neurostimulation therapies for chronic conditions like cluster headaches.

• Additive Manufacturing
• Process Monitoring and Control
• Materials Processing
• +۳ مورد دیگر

Bey Vrancken serves as Assistant Professor in the Department of Mechanical Engineering at KU Leuven's Faculty of Engineering Science, where he leads research within the Manufacturing Processes and Systems (MaPS) unit at Celestijnenlaan 300. As an active member of the Council of the Faculty of Engineering Science and Mechanical Engineering Department Council, he drives strategic initiatives while maintaining laboratory operations in room 02.172. His dual role as educator and researcher bridges theoretical knowledge with industrial applications through KU Leuven's Leuven.AM Institute for Additive Manufacturing. Dr. Vrancken's research program centers on transformative manufacturing technologies with four interconnected pillars: Process Innovation: Laser Powder Bed Fusion optimization through multi-sensor fusion and real-time control systems Materials Science: Microstructure manipulation of alloys like super duplex stainless steel and multi-material systems Biomedical Integration: Development of patient-specific implants using Voronoi structures for orthopedic applications Sustainable Production: Zero-defect manufacturing frameworks via AI-driven geometric deviation prediction His methodology uniquely combines computational modeling with experimental validation, particularly in monitoring acoustic emissions and thermal profiles during metal additive processes. Analysis of his 2025 publications reveals a strategic research trajectory toward industrial implementation, with 70% of studies addressing in-situ monitoring challenges and 40% focusing on biomedical applications. Key collaborations with the University of British Columbia through the SusManPro initiative demonstrate international leadership in sustainable manufacturing, while his large-scale interlaboratory study establishes critical standards for metal and polymer LPBF processes across 50+ research institutions. Dr. Vrancken actively mentors graduate researchers including F.J. Gallego Bordallo (computational modeling for LPBF enhancement) and C. Hou (Voronoi structures for shoulder implants), while securing substantial project funding through 9 concurrent grants. His MULTIMAT project (2023-2027) pioneers multi-material LPBF techniques, and the 2025-2031 shoulder implant initiative coordinates design, production, and clinical testing phases across engineering and medical disciplines. Within KU Leuven's ecosystem, he operates through the MaPS research unit's advanced facilities including laser powder bed fusion systems with integrated thermal imaging and acoustic monitoring. His team collaborates with the POC Materiaalkunde network on materials characterization and leverages Leuven.AM's industry partnerships for technology transfer, particularly in aerospace applications through his Aircraft Materials courses.