Find Academic Supervisors

• Robotics
• Mechatronics
• Micro/nano manipulation
• +14 more

Bijan Shirinzadeh is a Professor in the Department of Mechanical & Aerospace Engineering at Monash University's Faculty of Engineering. His research spans robotics, mechatronics, micro/nano manipulation, robotic surgery, and advanced manufacturing systems. He is actively involved in cutting-edge research in automation, sensing, and control. His primary research interests include: Robotics and Mechatronics Micro/nano manipulation and positioning Robotic-assisted Minimally Invasive Surgery Haptically-enabled surgical instruments Autonomous and complex robotic systems Advanced sensing and control algorithms Multi-arm manipulation and robotic fibre placement Automated tooling and fixturing His recent publications (2024–2025) demonstrate sustained research activity in precision robotics, UAV navigation, transducer design, and biomedical identification, reflecting strong interdisciplinary work in mechanical systems, control theory, and biomedical applications. These articles emphasize innovations in compliant mechanisms, piezoelectric actuation, Kalman filtering, and frequency-coupled ultrasonic devices. Bijan Shirinzadeh's scientific contributions align with UN Sustainable Development Goals in automation and manufacturing. His work has resulted in over 437 research outputs, including journal articles and conference papers. He advises students and leads research projects in robotics and automation, though specific names are not listed. His lab likely focuses on precision mechatronic systems, surgical robotics, and intelligent control. He collaborates internationally, particularly in areas of UAV systems, micro-manipulation, and transducer development.

• Security and Reliability of VR/AR Systems
• Internet of Things and Mobile Sensing
• Blockchain and Distributed Systems
• +7 more

Dr. Henry Hong-Ning Dai is an Associate Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He previously held academic positions at Lingnan University and Macau University of Science and Technology, where he advanced from Assistant to Associate Professor. He holds a Ph.D. from the Chinese University of Hong Kong and a D.Eng. from Shanghai Jiao Tong University. Education: Ph.D. in Computer Science and Engineering, Chinese University of Hong Kong (2008) D.Eng. in Computer Technology Application, Shanghai Jiao Tong University (2012) M.Eng. in Computer Science and Engineering, South China University of Technology (2003) B.Eng. in Computer Science and Engineering, South China University of Technology (2000) Dr. Dai's research focuses on security and reliability of VR/AR systems , Internet of Things , blockchain and distributed systems , federated learning , and cyber-physical systems . His work integrates AI, networking, and software engineering to address real-world security and performance challenges in emerging technologies. He has published over 300 papers in top journals and conferences such as IEEE JSAC, TMC, ICSE, INFOCOM, and AAAI, accumulating more than 24,000 citations. The 15 most recent publications (2023–2025) highlight his leadership in VR/AR security (e.g., AcouListener, Meta VR study), blockchain scalability and fairness (e.g., Porygon, Auncel, Justitia), federated and robust learning (e.g., EBS-CFL, FedDP), and edge-AI and wireless security (e.g., HARBOR, Smart Shield). His recent work also explores AI-generated art evaluation and LLM-driven manufacturing systems , showcasing interdisciplinary innovation. Scientific Awards and Recognition: Holder of 1 U.S. patent and 1 Australia innovation patent Winner of more than 17 awards Senior Member of ACM, IEEE, and EAI Dr. Dai has been Principal or Co-Investigator on over 12 research projects totaling HK$16 million, funded by UGC, NSFC, FDCT, and HKBU. He serves as an Associate Editor for IEEE Communications Surveys & Tutorials , IEEE Transactions on Intelligent Transportation Systems , and several other IEEE journals. He has chaired program committees and served on the PC of top conferences including ICSE, KDD, and INFOCOM. He is actively recruiting Ph.D. students and RAs in security, blockchain, and AI. Laboratories and Research Teams: While not explicitly named, Dr. Dai leads a research group focused on secure and intelligent distributed systems, with active projects in blockchain, VR security, and edge AI. His team has developed open-source tools such as VR-SP Detector , PrettySmart , and RLF for smart contract analysis and security assessment.

• Digital Photogrammetry
• Computer Vision
• Geospatial Imaging
• +10 more

Dr. Jackson David Cothren is a Professor in the Department of Geosciences at the University of Arkansas, where he also serves as the Leica Geosystems Chair in Geospatial Imaging. He holds dual leadership roles as Director of the Center for Advanced Spatial Technologies (CAST) and the Arkansas High Performance Computing Center (HPCC). His academic affiliations are deeply rooted in geospatial science, computer vision, and high-performance computing, bridging engineering and environmental applications. Ph.D. in Geodetic Science and Surveying, The Ohio State University M.S. in Geodetic Science and Surveying, The Ohio State University B.S. in Applied Mathematics, United States Air Force Academy Dr. Cothren's research spans digital photogrammetry, computer vision, UAV-based geospatial monitoring, and spatial archaeometry. He investigates non-traditional sensor modeling, feature extraction, surface generation, and integration with enterprise geospatial systems. His work increasingly incorporates deep learning, transformer models, and AI-driven analytics for applications in renewable energy, autonomous systems, and environmental sustainability. His recent publications highlight innovations in solar PV profiling, aerial image segmentation, and fairness-aware domain adaptation. The trends in his recent scholarly output reflect a strong shift toward machine learning and AI in geospatial analysis, particularly using transformer architectures for high-resolution imaging and cross-domain adaptation. His work integrates Lidar, GPS, and InSAR for deformation monitoring and leverages HPC for large-scale data processing. Applications span archaeology, agriculture, transportation, and energy infrastructure. Dr. Cothren has received numerous competitive grants from NSF, NEH, and USDA, supporting interdisciplinary research in geospatial analytics, smart transportation, and cultural heritage. His projects emphasize data-driven decision-making, community engagement, and workforce development in geospatial technologies. Principal Investigator, NSF E-RISE Rll: Arkansas Smart Transportation Research Incubator (2025–2029) Lead, RII Track-1: DART – Data Analytics that are Robust and Trusted (NSF, 2020–2025) Director, OPEN-GATE: Expanding Geospatial Education (NSF, 2016–2020) He mentors a broad interdisciplinary team and leads collaborative research initiatives involving computer vision, environmental science, and archaeology. His labs and research centers—CAST and HPCC—serve as hubs for innovation in spatial technologies, high-performance computing, and data-intensive research across the university and beyond. These centers support large-scale projects in archaeo-geophysics, UAV monitoring, and enterprise GIS integration.

Saddam Hussain WahlaView profile

Researcher

• Agricultural Engineering
• Climate Change
• Precision Agriculture
• +4 more

Saddam Hussain Wahla is a Researcher at the University of Florida , specializing in water management , GIS , remote sensing , and UAV-based crop health surveillance . His work integrates advanced technologies with agricultural practices to optimize resource use and enhance climate resilience. University: University of Florida Role: Researcher (mapped from Research Associate) Research Interests His expertise spans precision agriculture , irrigation systems , and climate change adaptation , with a focus on leveraging satellite data and unmanned aerial vehicles (UAVs) for crop monitoring. Recent Publications His recent studies include applications of machine learning for leaf area index predictions, micronutrient optimization in agronomy, and robotic automation for hydroponic systems. These works highlight trends in data-driven agriculture and climate stress response .

Kevin LuView profile

Teaching Professor

• Optical Networks
• Telecommunications R&D
• Internet of Things (IoT)
• +7 more

Kevin Lu is a Teaching Professor and Associate Dean for Undergraduate Studies at the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology . He holds a D.Sc. in Systems Science and Mathematics from Washington University in St. Louis and has over 40 years of experience in telecommunications R&D, academia, and standards development. Lu's career spans roles at Bellcore/Telcordia, Broadcom, and Stevens Institute of Technology. IEEE Life Senior Member since 1980 2018 transition from industry to academia after 28 years at Bellcore/Telcordia 2024 recipient of IEEE Standards Association Distinguished Service Award Research Interests: Focus on optical networks , telecommunications infrastructure , and Internet of Things education. His work explores network survivability , data integrity in AI systems , and passive optical network deployment . Current teaching includes courses on Digital System Design and Internet of Things . Standards Leadership: Lu chairs the IEEE Standards Board Industry Connections Committee and has served on multiple IEEE SA committees since 2005. His 2024 award recognized governance leadership in industry-standard development processes. Academic Contributions: Lu transitioned to full-time academia in 2018 after serving as Adjunct Professor at Stevens since 2015. His teaching philosophy emphasizes lifelong learning and soft skill development alongside technical knowledge. He received Stevens' Henry Morton Distinguished Teaching Professor Award and departmental teaching/service awards.

Rune Hylsberg JacobsenView profile

Professor

• Energy Systems
• Drone Technology
• Blockchain Applications
• +12 more

Rune Hylsberg Jacobsen is a Professor at the Department of Electrical and Computer Engineering, Aarhus University. His work bridges energy systems, drone technology, and blockchain applications, with a focus on smart grids, autonomous systems, and decentralized infrastructure. Research interests include: Security frameworks for prosumer-driven energy systems using blockchain mmWave and LEO satellite communication protocols Homomorphic encryption for smart meter privacy Cooperative drone swarm navigation and infrastructure inspection Earth observation via CubeSats for climate research His recent publications highlight advancements in: Zero trust security models for renewable energy certificates Transport protocol optimization in satellite networks AI-driven charging window scheduling for drone fleets Decentralized identity management in Web3 infrastructure Key projects include: DISCO-2: Student CubeSat for Arctic climate monitoring Drones4Safety: Safety-critical inspection systems VPP4SGR: Virtual Power Plant networks

Staffan BergwikView profile

Professor

• History of Science
• Cultural History
• Temporalities
• +4 more

Staffan Bergwik , Professor at Stockholm University 's Department of Culture and Aesthetics , specializes in the cultural history of modern natural sciences . His research intersects themes of temporality , science-society dynamics , and visual-sensory epistemologies . 2025-2027: Leading Temporalities of Science project funded by Riksbankens Jubileumsfond 2024: Published Terranauterna on aerial exploration technologies 2022: Co-edited Times of History, Times of Nature with Anders Ekström His methodological innovations include teaching theory/practice courses for humanities and STEM students, while anthology work redefines temporal analysis frameworks. Current focus on postwar scientometric policies reveals how measurement systems shaped scientific futures. Google Scholar publications (2014-2025) demonstrate chronotopic expertise across: Scientific emotion studies Expeditionary visualization Interdisciplinary temporal analysis Historiographic methodology Science education evolution As Science and Modernization program participant (2013-2018), he connected STS frameworks to engineering pedagogy while maintaining 100% data ownership research ethics.

Ramin MoghaddassView profile

Associate Professor

• Predictive Analytics
• Machine Learning
• Industrial Engineering
• +4 more

Ramin Moghaddass is an Associate Professor in the Department of Industrial Engineering at the University of Miami's College of Engineering. He serves as Director of both the Industrial Research and Assessment Center and the Building Training, Research, and Assessment Center. His work bridges machine learning with industrial engineering to solve complex system monitoring and maintenance challenges. University of Miami, College of Engineering Director, Industrial Research and Assessment Center Director, Building Training, Research, and Assessment Center His research focuses on: Deep state-space modeling for dynamic systems Graph neural networks for smart grid and network anomaly detection Thermal-RGB sensor fusion for manufacturing plant efficiency Image processing for vegetation risk analysis in power networks Bayesian filtering techniques with stochastic neural networks Recent publications highlight trends in sensor-driven system modeling (2025), thermal-RGB fusion for HVAC optimization (2025), anomaly detection in smart grids (2025), and adaptive inspection protocols for large-scale networks (2024). His work combines recurrent neural networks with dynamic Bayesian layers for predictive analytics while exploring graph topology integration. Contact: rxm991@miami.edu | (305) 284-9505

Yves BühlerView profile

Researcher

• Remote Sensing
• Snow and Avalanche Research
• Alpine Mass Movements
• +3 more

Dr. Yves Bühler is a leading researcher at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) , heading the Alpine Remote Sensing group within the Alpine Environment and Natural Hazards unit. His work focuses on remote sensing applications for snow and avalanche research, rock-ice avalanches, and alpine mass movement monitoring using drones, SAR satellites, and machine learning. Education: PhD in Remote Sensing (University of Zurich, 2005-2009), High-School Teaching Certification (MAS SHE, 2003-2005). Key projects: Large-scale avalanche mapping in India, drone-based snow depth monitoring, and thermomechanical modeling for hazard indication. Research Trends : Recent publications highlight advancements in machine learning for avalanche segmentation , multi-sensor displacement monitoring , and climate change integration into hazard models . His work bridges geomechanics , remote sensing technology , and operational risk mitigation across Switzerland, Himalayas, and international collaborations. Scientific Contributions : He has received a Research Fellowship at the University of Otago and led leadership programs at FHNW. His team developed RAMMS::LSHIM for large-scale hazard mapping and pioneered low-cost lidar for avalanche monitoring.

• Wind Energy
• Turbulence
• Experimental Fluid Mechanics
• +4 more

Ingrid Neunaber is an Assistant Professor in Fluid Mechanics at the Engineering Mechanics Department , KTH Royal Institute of Technology , since May 2025. Her expertise bridges fundamental turbulence research and applied wind energy systems.

Usman HadiView profile

Assistant Professor

• Wireless Communication
• 5G and Beyond 5G Networks
• Time Sensitive Networks
• +7 more

Dr. Usman Hadi serves as an Assistant Professor in the School of Engineering within Ulster University's Faculty of Computing, Engineering and Built Environment at the Jordanstown campus. His academic trajectory includes a Ph.D. in Electronic Engineering from the University of Bologna (2020), followed by postdoctoral research at Aalborg University and industry experience as an External Research Engineer at Nokia Bell Labs in Denmark (2019-2021). His educational foundation comprises: PhD in Electronic Engineering, University of Bologna (2020) Master's in Digital Predistortion for Compensation of Nonlinearities in Radio over Fiber Links, University of Bologna Dr. Hadi's research spans cutting-edge domains in wireless communications and AI-driven networking solutions. His primary focus includes 5G/6G technologies, Time Sensitive Networks, Radio over Fiber systems, and machine learning applications in telecommunications. Recent work emphasizes AI-enhanced signal detection for MIMO systems, UAV-based communication frameworks, and IoT security architectures, with significant contributions to optical front-haul optimization and wireless sensor networks. Analysis of his publication record reveals a strategic emphasis on AI integration for next-generation wireless systems. Key trends include deep learning applications for MIMO detection in 6G networks, digital twin implementations for UAV fault detection, and secure IoT frameworks for drone communications. His work consistently bridges theoretical advancements with practical implementations in optical and wireless front-haul systems, particularly through the MADNI (Made in UU) drone platform. Notable recognitions include: Top 2% Cited Researcher designation for three consecutive years (2021-2023) Research and Impact Fund Award (2023) Dr. Hadi supervises two PhD students: Ms. Cara Rose (Department of Economy-funded, 2023-present) and Mr. M.Y. Daha (Vice Chancellor's Research Studentship, 2022-present). His active research portfolio includes drone-based climate resilience initiatives funded by the British Council (2025-2026) and IoT-driven cybersecurity frameworks supported by Innovate UK (2025), alongside participation in EPSRC-funded infrastructure projects. He leads the MADNI drone research platform, which integrates state-of-the-art 5G connectivity, object detection, and facial recognition capabilities. His laboratory maintains active collaborations with Nokia Bell Labs, University of Manchester, University of East Anglia, Manchester Metropolitan University, University of Texas, and Boise State University, focusing on next-generation communication technologies and sustainable development applications aligned with UN SDGs.

• Assistive Technologies
• Chemistry Education
• 3D Printing
• +7 more

Dr. Terence Cavanaugh is a full professor of Instructional Technology at the University of North Florida’s College of Education and Human Services, specializing in curriculum design, instructional technology, and assistive technology. As a Fulbright Specialist, he brings global experience from teaching in diverse regions including China, Korea, Bahrain, Kuwait, Tuvalu, and the Caribbean, alongside a robust publication record in educational technology and open-source resources. Education: Science Education (with certifications in Physics, Chemistry, Biology, Earth Science, General Science, and Middle Grades) Instructional Technology State-certified media specialist Research Interests: Assistive Technologies for disabilities and Deaf/Hard of Hearing learners 3D Printing applications in STEM education and tactile learning Digital Learning strategies across K-12 and higher education Open Educational Resources (OER) and textbook innovation Scientific Contributions: 15+ publications on technology integration, including books on OER and science education Key focus areas: computational thinking, infographic resumes, and performance-based funding Scientific Awards: Fulbright Specialist for global educational collaboration

Darren Hurley-SmithView profile

Senior Lecturer

• Cyber Security
• Network Security
• Autonomous Systems Security
• +7 more

Dr Darren Hurley-Smith serves as a Senior Lecturer in the School of Computing at the University of Kent, specializing in cyber physical systems, network security, and autonomous platforms including unmanned aerial, ground, and submersible vehicles. His work bridges critical infrastructure protection with cutting-edge security research. Education PhD in Mobile Ad Hoc Networks, MANET Security, and Distributed Task Allocation Algorithms from the University of Greenwich (2015) Research Focus His pioneering work spans ransomware ecosystem analysis—developing cryptocurrency tracking tools and Ethereum blockchain attack mitigation—and transport security innovation including Vehicle-to-Infrastructure (V2I) communications. He has engineered secure MANET routing protocols for 5G-connected drone networks and investigates privacy harms from unregulated data harvesting by AI developers. Key Projects National Highways (2024) : Project Lead for CCTV network dataflow simulation in transport systems Omnidrome Facility (2022-2024) : Technical Manager for Royal Holloway's UAV/UGV/ROV research infrastructure RAMSES2020 (2016-2020) : Horizon 2020 Research Associate tracking ransomware financial flows Academic Leadership Dr Hurley-Smith teaches Digital Forensics (COMP8230), Information Security Management (COMP6644/8340), Network Security, and Ethical Hacking. He actively supervises postgraduate research in autonomous vehicle security and decentralized network integrity, emphasizing public safety applications. His lab work focuses on simulating cyber-physical attack scenarios for critical infrastructure resilience testing.

Weibing GongView profile

Assistant Professor

• Climate change-related hazards
• Seismic hazards
• Infrastructure resilience against natural hazards
• +3 more

Weibing Gong is an Assistant Professor of Geological Engineering in the Department of Geosciences and Geological and Petroleum Engineering at Missouri University of Science and Technology (Missouri S&T), affiliated with the Center for Intelligent Infrastructure in Rolla, Missouri. His educational background includes: Ph.D. in Geosystems Engineering, University of California, Berkeley (2023) M.S. in Geotechnical Engineering, Tongji University (2018) B.S. in Civil Engineering, Central South University (2015) Dr. Gong's research centers on natural hazard mitigation , with emphasis on climate change impacts , seismic resilience , and AI-driven infrastructure monitoring . His work integrates remote sensing and machine learning to enhance geological engineering solutions, particularly for landslide prediction and pavement systems, while exploring emerging applications in carbon capture technologies. Analysis of his 2023-2025 publications reveals a pronounced shift toward physics-informed AI for geotechnical challenges, featuring recurrent themes in regional landslide modeling (especially in Puerto Rico and Greece), dynamic pavement response under traffic loads, and unsaturated soil mechanics . This interdisciplinary approach bridges computational science, civil engineering, and environmental systems through advanced numerical frameworks. Dr. Gong actively contributes to Missouri S&T's Center for Intelligent Infrastructure, focusing on developing next-generation methodologies for infrastructure resilience against natural hazards through computational innovation and field-based validation.

Jin Woo SongView profile

Associate Professor

• Navigation and Sensor Systems
• Control Theory
• Estimation Theory
• +7 more

Jin Woo Song is an Associate Professor in the Department of Artificial Intelligence and Robotics at Sejong University's School of Intelligent Mechatronics Engineering. He has held academic positions at Seoul National University and Hoseo University prior to joining Sejong University in 2017. His professional experience also includes serving as CTO/COO at Microinfinity Co., Ltd. from 2004-2014. Currently, he holds multiple leadership roles including Director of Sejong Enterprise Support Foundation, Director of SW-AI Convergence Center, and Provost of Sejong University. Dr. Song received his B.S., M.S., and Ph.D. in Control and Instrumentation Engineering/Electrical Engineering from Seoul National University. His educational background laid the foundation for his expertise in navigation systems and control theory. Dr. Song's research focuses on navigation and sensor systems, control theory, and estimation theory with applications in unmanned systems. His work spans MEMS inertial sensor technologies, Kalman filtering techniques, optimal and robust control theories, and fault detection algorithms. His research has significant applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems. His recent publications (2023-2025) demonstrate continued innovation in navigation systems, with emphasis on fault tolerance, sensor fusion, and improved positioning accuracy in challenging environments. His work shows strong trends toward integrating multiple sensor modalities and developing robust algorithms for real-world navigation challenges. Best student paper award, NAECON2000 (IEEE, National Aerospace and Electronics Conference), USA, 2000 Ministry Award, 'IT R&D Engineer of the Year', Ministry of Information and Communication, Republic of Korea, 2005 Best Presentation Award, ICASS 2015, 2015 Best Paper Award, KIEE Conference, 2019 Distinguished Teaching Award, Sejong University, 2021 Distinguished Research Award, Sejong University, 2022 Distinguished Professor, Sejong University, 2024 Dr. Song has served as Editor-in-Chief for ICROS journal and holds editorial positions for multiple prestigious journals including the International Journal of Aeronautical and Space Sciences. He has been actively involved in numerous research grants and industry collaborations, including a recent academic-industrial partnership with Hanwha Systems. As Vice-President of The Institute of Control, Robotics and Systems (ICROS) and various other professional organizations, he plays a significant role in shaping research directions in his field. He leads the Intelligent Navigation and Control Systems Lab at Sejong University, where his team develops cutting-edge navigation sensors and systems, optimal controllers for autonomous systems, and embedded systems for reliable navigation and control. The lab's work has direct applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems.