Find Academic Supervisors

• Edge-Cloud Computing
• Resource Optimization
• Applied Machine Learning
• +5 more

Jia Hu is an Associate Professor in Computer Science at the University of Exeter. He holds a PhD in Computer Science from the University of Bradford (2010), and M.Eng/B.Eng degrees in Electronic Engineering from Huazhong University of Science and Technology. His research specializes in edge-cloud computing, federated learning, and AI-driven optimization for networks and IoT systems. Research Interests: Hu's work spans resource optimization, applied machine learning (particularly in distributed settings), network security, blockchain integration, and intelligent systems for electric vehicles and Industry 4.0. His recent projects focus on federated edge AI, 6G-enabled industrial IoT, and real-time federated learning via hardware-algorithm co-design. Publications: His 150+ papers emphasize federated learning, edge computing, and reinforcement learning applications. Recent works (2020–2025) show a strong trend toward optimizing AI at the network edge, with themes like digital twins, blockchain security, and EV-integrated systems dominating. Awards & Recognition: Best Paper Awards: IEEE SOSE'16, IUCC'14 Outstanding Service & Leadership Awards for IEEE conferences Top 4% contributor to EPSRC Peer Review Fellow of the Higher Education Academy (HEA) Grants & Projects: Secured €4.7M+ funding from EU Horizon, EPSRC, and Royal Society for projects including: SAILING (Secure AI for Smart Internet-of-Energy, €3.6M) REFINE (Real-time Air Quality Monitoring with UAVs, €897K) SustainAIRA6G (Energy-Efficient AI for 6G Networks, £118K) Advising: Supervised 12 PhD students to completion; currently mentoring 7 students in federated learning, edge computing, and AIoT.

• Construction Logistics
• Digital Twin Frameworks
• Building Information Modeling (BIM)
• +4 more

Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.

Jose Paolo TalusanView profile

Researcher

• Smart Transportation Systems
• Cyber-Physical Systems
• Middleware
• +4 more

Dr. Jose Paolo Talusan is a Research Scientist at the Department of Computer Science and Computer Engineering , Vanderbilt University, specializing in smart transportation systems , distributed computing , and cyber-physical systems . He is affiliated with ScopeLab , a research group focused on smart cyber-physical systems. Education: PhD from Nara Institute of Science and Technology, Japan (2020) Research Interests: His work addresses challenges in urban mobility through middleware architectures, optimization algorithms, and machine learning. Key areas include incident detection in transportation systems, privacy-preserving route planning, and vehicle-to-building charging optimization. Publication Trends: Recent publications focus on real-time transit optimization (2024-2025), leveraging reinforcement learning for heterogeneous agents in vehicle-to-building systems, and privacy-aware route planning in smart cities. His work integrates IoT , edge computing , and graph neural networks to tackle imbalanced data and sparsity issues in transit analytics. Labs & Teams: Actively contributes to ScopeLab at Vanderbilt University, collaborating on interdisciplinary projects with researchers in computer science, electrical engineering, and urban planning.

Ye ZhaoView profile

Associate Professor

• Robotics
• Formal Methods
• Optimization
• +7 more

Dr. Ye Zhao is an Associate Professor and Woodruff Faculty Fellow at the Georgia Institute of Technology's Woodruff School of Mechanical Engineering, where he directs the Laboratory for Intelligent Decision and Autonomous Robots (LIDAR). He holds affiliations with the Institute for Robotics and Intelligent Machines, Machine Learning Center, and Supply Chain and Logistics Institute. Dr. Zhao received his Ph.D. from UT Austin (2016) and completed postdoctoral training at Harvard University. Research Focus: His work integrates planning, control, and learning for contact-rich robots, emphasizing computationally efficient algorithms with formal safety guarantees. Key research thrusts include: Reactive synthesis for terrain-adaptive locomotion and manipulation Vision-tactile perception for deformable object grasping Social navigation of bipedal robots in human environments Distributed optimization for multi-robot coordination His lab utilizes platforms including Mini Cheetah quadruped, Cassie biped, and custom manipulators. Publication Trends: Recent articles demonstrate a strong focus on bridging formal methods (temporal logic, reactive synthesis) with learning-based approaches (RL, transformers) to enhance robustness in locomotion and manipulation. Key themes include terrain adaptation, human-robot interaction, and real-time model predictive control. Awards & Honors: ONR Young Investigator (2023) NSF CAREER Award (2022) IEEE ICRA Best Automation Paper Finalist (2021) IEEE Senior Member (2022) Woodruff Faculty Research Award (2023) Educational Initiatives: Leads the Vertically Integrated Program (VIP) for Agile Locomotion & Manipulation, engaging 80+ undergraduates in robotics research. The team won 1st place in Georgia Tech's VIP Innovation Competition (2021, 2022).

• Fuzzy Logic Systems
• Artificial Intelligence
• Model-Based Predictive Control
• +6 more

Professor Mahdi Mahfouf holds the Chair in Intelligent Systems at the University of Sheffield's School of Electrical and Electronic Engineering . He obtained his MPhil (1988) and PhD (1991) in Control Systems from the same institution. After postdoctoral research (1992-1996) on Leverhulme-funded projects in Model-Predictive Control and Fuzzy Logic, he progressed through academic ranks at Sheffield to Full Professor (2005). Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award (for ICU Decision Support Systems) Over 370 publications, including 130+ journal papers Head of the Intelligent Systems Research Laboratory Research Themes His work spans fundamental research in Fuzzy Logic (modelling, control), Neural-Fuzzy Systems, Self-Organising Control, and Evolutionary Optimization, alongside applied domains in pharmaceutical manufacturing, aerospace systems, biomedical engineering (ICU monitoring), and intelligent transportation. Recent publications focus on hybrid AI for pharmaceutical processes , type-2 fuzzy control systems , and machine learning in manufacturing metrology . Lab initiatives include multistage process monitoring and human-machine interaction systems for stress management.

Richard CollinsView profile

Senior Lecturer

• Water Distribution Systems
• Hydraulic Transients
• Pipe Fatigue Analysis
• +5 more

Dr Richard Collins is a Senior Lecturer in Water Engineering at the University of Sheffield , affiliated with the School of Mechanical, Aerospace and Civil Engineering. His research focuses on hydraulic transients , pipeline integrity , and smart water infrastructure . Graduated with an Aerospace Engineering degree (2005) and PhD in Materials and Mechanical Engineering (2009) Current research explores pressure transients , leak detection , and autonomous robotic systems for pipeline inspection Projects include fatigue analysis , biofilm mobilisation , and ultrasound-based pipe assessment His publications emphasize cast iron pipe fatigue , acoustic leak detection , and transient-induced contamination . Funded by RCUK and Datatecnics , his work bridges mechanical engineering and civil infrastructure challenges.

• Geoinformatics
• Cartography
• Geodetic Science
• +5 more

Prof. Monika Sester is a distinguished Professor and Executive Director of the Institute of Cartography and Geoinformatics at Leibniz University Hannover, within the Faculty of Civil Engineering and Geodetic Science. She also serves as Spokesperson for the Leibniz Research Center FZ:GEO and holds multiple leadership roles including Faculty Information Officer (FIO) for the Faculty of Civil Engineering and Geodetic Science, Ombudsman for Good Scientific Practice, and Exchange Coordinator for Geodetic Science and Geoinformatics. Her research focuses on the intersection of geospatial information science, cartography, and urban mobility. Prof. Sester's work spans several key areas: Geospatial data processing and analysis Cartographic representation and visualization Urban mobility and transportation systems Spatial data uncertainty and quality Digital mapping technologies and applications Historical map analysis and interpretation Prof. Sester's recent publications demonstrate a strong focus on applying advanced computational techniques to geospatial problems. Her work shows increasing emphasis on machine learning applications for map analysis, urban mobility optimization, and 3D spatial modeling. She has been particularly active in researching applications of deep learning for historical map interpretation, urban mobility patterns, and spatial uncertainty visualization. Her contributions to the field have been recognized through leadership positions in major research initiatives: Executive Director, Institute of Cartography and Geoinformatics Spokesperson, Leibniz Research Center FZ:GEO Faculty Information Officer, Faculty of Civil Engineering and Geodetic Science Ombudsman for Good Scientific Practice Member of multiple academic committees including the Admissions and Examination Board Prof. Sester actively collaborates with students and researchers across multiple projects focused on geospatial information systems, urban mobility, and cartographic visualization. Her leadership extends to guiding research directions within the Leibniz Research Center FZ:GEO, which brings together interdisciplinary expertise to address complex spatial challenges.

• Cooperative Robotic Systems
• Multi-Robot Systems
• Human-Robot Collaboration
• +7 more

Luis Merino is an Associate Professor at the School of Engineering, Universidad Pablo de Olavide (UPO), Seville, Spain. He founded and leads the Service Robotics Laboratory and contributed to establishing the Systems Engineering and Automation division at UPO. He served as Vice-Dean for five years and currently coordinates the Computer Science degree program. Education: Ph.D. in Robotics from the University of Seville (2007), supervised by Anibal Ollero. Research: Focuses on cooperative robotic systems, human-robot collaboration, localization/navigation techniques, and machine learning in social robotics. His work includes leading 2 H2020, 4 FP7, 3 National R&D, and 3 Andalusian regional projects. Notable projects: MBZIRC 2020 (PI), collaboration with Honda Research Institute Japan, and EU-funded initiatives. He advocates for open-source code/datasets and industry technology transfer. Scientific Awards: ABB Award to the Best Doctoral Dissertation on Robotics (2007) Best Paper Award at ROBOT2019 Professional Roles: Associate Editor for Image and Vision Computing and IEEE Robotics and Automation Letters . Serves on ICRA/IROS conference program committees. Grant reviewer for FONDECYT (Chile), SBIR (USA), and ERC.

Melrose BrownView profile

Associate Professor

• Space Situational Awareness
• Hypersonic Aerodynamics
• Satellite Drag Modeling
• +6 more

Associate Professor Melrose Brown is a faculty member at UNSW Canberra, School of Engineering and Technology, where he leads numerical space situational awareness research and coordinates the Space Masters program. He holds advanced degrees in Aerospace Engineering and specializes in applying high-fidelity simulations to satellite-environment interactions in Low Earth Orbit (LEO). Research Focus: DSMC/PIC simulations for LEO satellites Orbit propagation and determination Ionospheric drag modeling Atmospheric physics Hypersonic CFD His recent publications analyze thermospheric responses to geomagnetic storms using GITM-OVATION models, ionospheric drag effects, and numerical tools like pdFOAM. Key keywords include Space Weather, Satellite Formation Control, and Computational Fluid Dynamics. He supervises Ph.D. projects related to aerospace engineering and offers scholarships for research in LEO dynamics. His work involves collaborations on CubeSat missions (e.g., M2) and space traffic management systems.

Justin BradleyView profile

Associate Professor

• Artificial Intelligence and Intelligent Agents
• Cyber-Physical Systems
• Embedded and Real-Time Systems
• +3 more

Justin Bradley is an Associate Professor in the Computer Science Department at North Carolina State University. Previously, he held the position of Richard L. and Carol S. McNeel Associate Professor of Computing in the School of Computing at the University of Nebraska-Lincoln. His educational background includes: Ph.D. in Aerospace Engineering from the University of Michigan (2014) M.S. in Aerospace Engineering from the University of Michigan (2012) M.S. in Electrical Engineering from Brigham Young University (2007) B.S. in Computer Engineering from Brigham Young University (2005) Dr. Bradley's research focuses on cyber-physical systems with particular emphasis on control, autonomy, software, and computing for aerospace vehicles. A key theme in his work involves developing algorithms that can dynamically adjust their resource utilization in response to uncertainty while maintaining performance requirements. His research spans several critical areas including Artificial Intelligence and Intelligent Agents, Cyber-Physical Systems, and Embedded and Real-Time Systems, with applications primarily in unmanned aircraft systems (UAS) operating in challenging environments like wetlands and fire-prone areas. His scientific achievements have been recognized with prestigious awards including: 2021 NSF CAREER award AIAA Associate Fellow designation Dr. Bradley has been actively involved in research funding and mentoring. His NSF CAREER award (NSF-2047971) supports work on "co-regulation" algorithms for unmanned aircraft systems. He has co-directed research labs including the MAGICC lab at BYU, the A2Sys lab at the University of Michigan, and the Nebraska Intelligent MoBile Unmanned System (NIMBUS) lab since 2015. His research group focuses on developing performance-adjustable, resource-aware algorithms for autonomous systems, with applications in environmental monitoring, wetland studies, and fire management. His educational efforts target K-12 through adult engagement to expand the cyber-physical systems educational pipeline. His laboratory work centers around the development of the Co-regulated Hybrid Systems (CHS) framework, Co-regulated Real-Time Kernel (CRTK), and co-regulated Markov Decision Process (MDP) for resource-aware autopilots. These technologies enable unmanned systems to dynamically reallocate computing resources while maintaining mission objectives, particularly valuable in complex environments like rainforests where systems must transition between surveillance, sampling, and sensor emplacement tasks.

Stefan LarssonView profile

Senior Lecturer

• Artificial Intelligence and Society
• Socio-legal Studies
• Technology and Social Change
• +4 more

Stefan Larsson serves as Senior Lecturer and Associate Professor in Technology and Social Change at Lund University's Department of Technology and Society within the Faculty of Engineering. He directs the AI and Society research team and holds affiliate status at Lund's Centre for Retail Research, leveraging dual PhDs in Sociology of Law and Spatial Planning alongside an LLM to examine technology's societal impacts. His educational credentials include: PhD in Sociology of Law PhD in Spatial Planning Master of Laws (LLM) Larsson investigates critical intersections of law, technology, and social systems with emphasis on AI governance frameworks , consumer protection in digital markets , and trust mechanisms for autonomous systems . His work addresses socio-legal challenges across healthcare robotics, public sector automation, and algorithmic consumer markets while advancing UN Sustainable Development Goals through responsible innovation pathways. Current publications reveal concentrated analysis of youth interactions with generative AI and regulatory tensions in the EU AI Act , demonstrating how users navigate authenticity assessments of AI content while exposing fundamental conflicts between technological evolution and legal stability. Key distinctions include: Election to Royal Swedish Academy of Engineering Sciences (2024) Co-chair appointment for RCSL Working Group on Digitalisation, AI and Society (2024) Research board membership at Lund Engineering Faculty (2022) As supervisor for three doctoral candidates, Larsson manages significant research portfolios: Principal Investigator : 'When N equals 1' (2025-2027) on AI ethics in predictive medicine Project Coordinator : 'Girls in AI Science' gender-inclusion network (2025) Researcher : Swedish Research Council project on EU AI Act risk governance (2024-2026) His multidisciplinary team actively collaborates with public sector agencies, healthcare institutions, and consumer protection bodies to develop practical frameworks for trustworthy AI implementation across societal domains.

Jari VepsäläinenView profile

Assistant Professor

• Mechatronics Design
• Energy Efficient Systems
• Generative Design
• +7 more

Jari Vepsäläinen is an Assistant Professor at Aalto University's Department of Energy and Mechanical Engineering under the College of Engineering. He serves as Director of the Fluid Power group and specializes in mechatronics design, energy efficiency, and generative design methodologies. Research focuses on physics-based modeling for energy recovery AI/ML applications in electromechanical system design Applications in robotics, heavy machinery, and sustainable transportation His recent publications demonstrate expertise in hybrid systems, fluid power optimization, and AI-driven engineering, with a strong emphasis on electrification and efficiency across automotive, maritime, and industrial domains. Key areas: Mechatronics, Energy Systems, Generative Design Technologies: Digital Twins, IoT, Machine Learning Current projects involve thermal energy systems, electric motor optimization, and advanced control algorithms for mobile machinery.

• Maritime Engineering
• Machine Learning
• Risk Analysis
• +4 more

Mingyang Zhang is a Postdoctoral Researcher at the Department of Energy and Mechanical Engineering , Aalto University, Finland. His research focuses on the intersection of Maritime Engineering and Artificial Intelligence , particularly in Digital Twin Technology , Ship Motion Prediction , and Risk Analysis for Arctic and inland waterway operations. Awarded Best Paper at G-NAOE 2024 Honored with 5 Highly Cited Paper Awards (2021-2024) Active in Marine and Arctic Technology research group His machine learning work addresses ship fuel consumption prediction , collision avoidance , and grounding risk assessment , with applications in autonomous shipping and offshore wind farm monitoring . Key publications span Reliability Engineering , Ocean Engineering , and Marine Hydrodynamics journals. Recent article trends include: Digital Twin applications for shipping decarbonization (2024) Deep learning models for 6-DoF ship motions and focused wave prediction (2023) Big Data Analytics for Arctic navigation risks and inland waterways (2022-2021) Integration of HFACS and fault tree analysis in risk modeling (2019) Scientific achievements include: 2024: Best Paper, G-NAOE Conference 2023: 2 Highly Cited Paper Awards 2022: 2 Highly Cited Paper Awards 2021: Highly Cited Paper Award 2019: Best Paper, 5th International Conference on Transportation Information and Safety Current research at the Marine and Arctic Technology group emphasizes AI-driven maritime safety , real-time risk monitoring , and data-intensive shipping decarbonization projects. Collaborations include Spyros Hirdaris , Pentti Kujala , and Jakub Montewka .

Daniel LeidnerView profile

Professor

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +5 more

Daniel Leidner is a Cooperation Professor at the University of Bremen and a researcher at the German Aerospace Center (DLR) where he has been contributing to the Institute of Robotics and Mechatronics since 2011. He earned his doctorate in Artificial Intelligence and Robotics from the University of Bremen in 2017. Since 2017, he has led the Semantic Planning Group and the Fault-Tolerant Autonomy Architectures group at DLR, focusing on advanced task planning for autonomous robotic systems and enhancing the reliability of robotic operations in dynamic environments. Leidner's research interests span multiple areas in robotics and artificial intelligence. His work emphasizes developing robust and resilient robotic systems capable of autonomous operation in complex environments. He specializes in creating systems that can not only handle predictable scenarios but also flexibly respond to unforeseen events. His ERC Starting Grant project RECOVER.ME aims to equip robots with metacognitive abilities to autonomously manage hardware malfunctions by integrating formal reasoning with Vision-Language Models. This innovative approach enhances the resilience and efficiency of space robots, reducing the need for manual intervention during missions and leveraging insights from cognitive psychology for improved problem-solving capabilities. Leidner's research portfolio includes significant projects such as RECOVER.ME, FUTURO, EASE, OPERA, Smile2gether, Surface Avatar, and CoViPa. His publications demonstrate a strong focus on autonomous task planning, human-robot interaction, fault tolerance, and metacognitive capabilities in robotic systems. Recent publications highlight advancements in space teleoperation, assistive robotics, and cognitive reasoning for resilient robotic systems. ERC Starting Grant (2024) for project RECOVER.ME Georges Giralt PhD Award (Best European PhD Thesis in Robotics) Helmholtz Doctoral Prize MIT Technology Review Innovator under 35 Award Leidner has served as an advisor to the German Federal Government from October 2023 to July 2024, where he played a crucial role in developing a national strategy for AI-based robotics. His leadership in the Semantic Planning Group and Fault-Tolerant Autonomy Architectures group at DLR demonstrates his significant contributions to advancing robotic capabilities in challenging environments. His work bridges theoretical advances in cognitive robotics with practical applications in space exploration, healthcare, and industrial automation.

• Robotics
• Multi-Agent Systems
• Crowd Simulation
• +6 more

Stephen J Guy is an Associate Professor in the Department of Computer Science and Engineering at the University of Minnesota's College of Science and Engineering. His research focuses on robotics, multi-agent systems, and human-computer interaction with applications in biomedical engineering and digital entertainment. University of Minnesota, College of Science and Engineering Department of Computer Science and Engineering Active research in multi-agent navigation and biomedical applications Dr. Guy's work spans robotics and computer science, with particular emphasis on multi-agent navigation , crowd simulation , and path planning . His research also extends into biomedical applications such as motion analysis for developmental disorders and digital game design for interactive entertainment. Recent publications demonstrate expertise in motion tracking and behavioral analysis. His work on augmented reality games (2024) and multi-agent coordination (2020) represent key contributions to human-computer interaction and autonomous robotics. No specific scientific awards were identified in the scraped data. Dr. Guy collaborates across disciplines including biomedical engineering (e.g., Tourette Syndrome research) and retail analytics (trajectory pattern analysis with Tesco PLC). He serves as Principal Investigator for multiple NSF-funded projects related to robotics and human well-being.