Find Academic Supervisors

Zhen GaoView profile

Associate Professor

• Automation Engineering Technology
• Robotics
• Industry 4.0
• +5 more

Dr. Zhen Gao is an Associate Professor of Automation Engineering Technology at the W Booth School of Engineering Practice and Technology, McMaster University. He holds associate membership roles in the School of Computational Science & Engineering, Department of Civil Engineering, and McMaster School of Biomedical Engineering. His expertise spans Automation Engineering Technology, Industry 4.0, Health Technology, and Robotics. Research focuses on advanced manufacturing systems, smart systems, and biomedical engineering applications. Dr. Gao’s work integrates robotics, AI, and sensor technologies for practical applications like wound analysis, autonomous systems, and healthcare automation. His recent publications emphasize 3D object detection algorithms, machine learning for medical diagnostics, and robotics control systems. He advises students in emerging technologies, including Shiyu (Shannon) Chen, a Master of Engineering Systems and Technology student. His academic contributions include innovations in parallel robotic mechanisms, smart grid systems, and project-based learning methodologies. He actively collaborates with institutions like St. Joseph’s Healthcare Hamilton to advance healthcare technologies.

• Maritime Economics
• Port Management
• Transport Logistics
• +4 more

Hanna Klimek , a Professor at the University of Gdańsk, Faculty of Economics, is a leading expert in maritime transport and trade. Her work spans port competitiveness, innovation, and sustainable development. Department of Maritime Transport and Trade Research focus: Maritime Economics, Port Logistics, CSR, Sustainable Development Her research explores maritime port modernization, including unmanned surface vehicles , LNG bunkering , and hydrogen economy integration . She emphasizes smart port technologies , digitalization , and environmental strategies in global and regional contexts (e.g., Gdynia, Poland). Recent publications analyze container terminal competitiveness , CSR disclosure in Polish ports, and virtual sampling methods for maritime market research. Her work bridges theoretical frameworks with practical case studies, particularly in Baltic Sea region ports.

Nuno CruzView profile

Associate Professor

• Marine Robotics
• Autonomous Vehicles
• Underwater Sensor Systems
• +3 more

Nuno Cruz is an Associate Professor at the Faculty of Engineering of the University of Porto and Coordinator at the Centre for Robotics and Autonomous Systems at INESC TEC. He holds a MSc in Digital Systems Engineering (UMIST, UK) and a PhD in Electrical Engineering (University of Porto). His research focuses on marine robotics, autonomous vehicles, and underwater sensor systems. He has over 125 publications and 30 years of experience developing marine robotic vehicles like the Zarco/Gama ASVs and MARES/TriMARES AUVs. Research interests include adaptive sampling strategies for autonomous vehicles and energy-efficient underwater platforms. He is a Senior Member of IEEE Oceanic Engineering Society, chairs the Portuguese IEEE OES Chapter, and serves as Associate Editor for IEEE Journal of Oceanic Engineering. Recent work emphasizes underwater sensor calibration via sonar imaging, energy-saving control systems, and advancements in SMART cable technology. Supervised theses include multi-sensor fusion for marine vehicle docking and autonomous bathymetric mapping.

Mike KnowlesView profile

Senior Lecturer

• Condition Monitoring
• Asset Management
• Electric and Low Carbon Vehicles
• +6 more

Dr Mike Knowles is an Associate Dean (Learning & Teaching) and Principal Lecturer (Research and Innovation) at Teesside University's School of Computing, Engineering and Digital Technologies. He holds a PhD in Electronic and Electrical Engineering from the University of Birmingham (2006) and is a Chartered Engineer (CEng) and Senior Fellow of the Higher Education Academy (SFHEA). His career includes roles as a Postdoctoral Research Assistant at the University of Sunderland, work in the Institute for Automotive and Manufacturing Advanced Practice (AMAP), and leadership positions such as Programme Leader and Team Leader. Education qualifications include a Master of Engineering (MEng, 2002) and PhD (2006) from the University of Birmingham. Key research interests span application of intelligent systems to engineering challenges, new product development for electronic systems, and engineering pedagogy focusing on skills development and assessment methodologies. His research has addressed energy transition, decarbonization, EV asset management, and maintenance strategies for wind turbines and marine systems. He has led Knowledge Transfer Partnerships (KTPs) and contributed to EU-funded projects like NESTCOM and POSEIDON. External roles include chairing the IET Northumbria Local Network and serving as a Professional Registration Advisor. Notable awards and fellowships include SFHEA and CEng. His work emphasizes bridging academic research with industry needs, particularly in low-carbon technologies and sustainable energy systems. Recent publications highlight energy justice, regional decarbonization strategies, and innovative teaching methods.

Axel KlarView profile

Professor

• Kinetic Theory
• Traffic Flow Modeling
• Pedestrian Dynamics
• +6 more

Prof. Axel Klar is a Professor in the Department of Technomathematics at the Rheinland-Palatinate University of Applied Sciences (RPTU) Kaiserslautern-Landau. His research focuses on mathematical modeling of complex systems, with a strong emphasis on kinetic theory, fluid dynamics, and applied analysis. Key areas of expertise include traffic flow dynamics, fiber dynamics in industrial processes, pedestrian movement patterns, and biological systems such as cell motion and tumor growth. He develops and analyzes numerical methods for partial differential equations and stochastic systems, often addressing challenges in technical textile production, non-equilibrium thermodynamics, and multi-physics simulations. His work bridges microscopic particle-based models with macroscopic continuum descriptions, emphasizing asymptotic methods and domain decomposition techniques. Notable contributions include stochastic fiber lay-down models for nonwoven manufacturing, mesh-free particle methods for granular and rarefied gas flows, and kinetic-based traffic models with applications to autonomous vehicles and crowd control. Current research explores data-driven approaches for coupled systems in socio-economic and biomedical contexts. Prof. Klar’s interdisciplinary projects involve collaborations with industry partners (e.g., in textile engineering) and academic institutions globally. His team develops open-source numerical toolkits for applications ranging from radiation therapy optimization to climate-resilient infrastructure design. Recent efforts focus on AI-driven parameter estimation for high-dimensional PDE systems and uncertainty quantification in multi-scale modeling.

Aamir AhmadView profile

Professor

• Aerial Robotics
• Multi-Robot Systems
• Deep Learning
• +7 more

Aamir Ahmad is a Tenure-track Professor (Flugrobotik) and Deputy Director (Research) at the Institute of Flight Mechanics and Control, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart. He also leads the Robot Perception Group (RPG) at the Max Planck Institute for Intelligent Systems in Tübingen. His research focuses on aerial robotics, multi-robot systems, deep reinforcement learning, formation control, and perception-driven navigation. He leads the Flight Robotics Group (FRG) and Robot Perception Group (RPG), which are part of the Cyber Valley and IMPRS-IS initiatives. His work includes developing autonomous aerial systems for tasks like motion capture, environmental monitoring, and cooperative target tracking. Key projects include AirCap (aerial human motion capture) and GRADE (generating dynamic environments for robotics). Research interests span reinforcement learning for autonomous systems, SLAM algorithms, and bio-inspired robotics. Notable contributions include autonomous multi-rotor landing on moving platforms, viewpoint-driven airship formations, and synthetic data-driven wildlife tracking. Ahmad has secured grants such as the EU H2020-funded DeepField project. He advises PhD students through the IMPRS-IS program and offers postdoc and research positions. His groups collaborate with institutions globally and engage in open-source software development for robotics.

Paolo StegagnoView profile

Associate Professor

• Multi-Robot Systems
• Mobile Robotics
• Aerial Robotics
• +6 more

Paolo Stegagno is an Associate Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island. His research focuses on advanced robotics, including multi-robot systems, mobile robotics, aerial robotics, and human-robot interaction. He leads projects in adaptive control, fault detection, and cooperative systems, with applications in underwater vehicles, swarm robotics, and soft robotics. Education : Ph.D., Systems Engineering, Sapienza Università di Roma (2012) M.S., Electronic Engineering, Sapienza Università di Roma (2008) B.S., Electronic Engineering, Sapienza Università di Roma (2005) Research Interests : Dr. Stegagno explores cutting-edge topics such as distributed control algorithms for multi-agent systems, adaptive learning for uncertain environments, and fault-tolerant robotics. His work combines theoretical advancements in control theory with practical implementations in aerial, underwater, and soft robots. Recent projects include cooperative transportation systems, swarm localization, and human-in-the-loop control for safer and more efficient robotic operations. Grants & Collaborations : PI: NSF RII Track-2 FEC grant on computational methods for predicting harmful cyanobacterial blooms using autonomous robotics (2023) Co-PI: Vision-based bridge damage detection using UAVs (2022) Co-PI: NSF Collaborative Research on distributed multi-agent control (2020) Labs & Teams : Leads the URI Robotics Lab, focusing on hardware-in-the-loop simulations, aerial robotics, and cooperative systems. Active collaborations with Dartmouth College and the University of Maine on environmental monitoring and structural inspection projects.

Jacob GuntherView profile

Professor

• Signal Processing
• Statistical Signal Processing
• Array Processing
• +7 more

Jacob Gunther is a Professor in the Department of Electrical and Computer Engineering at Utah State University's College of Engineering. He specializes in signal processing, statistical signal processing, and communication theory, with applications in transportation systems, SAR navigation, and adaptive filtering. PhD , Electrical Engineering, Brigham Young University, 1998 MS , Electrical Engineering, Brigham Young University, 1994 BS , Electrical Engineering, Brigham Young University, 1994 Gunther's research spans signal processing for electric bus charging optimization, GPS-denied navigation using SAR, and advanced filtering techniques. His work includes hyperspectral imagery unmixing, communication systems, and sparse signal recovery. Recent publications focus on electric bus fleet charging cost minimization, SAR-based navigation, and adaptive filtering algorithms. Notable trends include integration of optimization theory with transportation electrification and robust positioning systems. Teacher of the Year (2015, 2005, 2004) IEEE Senior Member (2011) Advisor of the Year (2010, 2003) Researcher of the Year (2004) Award of Merit (2010, 2007) Gunther has mentored numerous graduate students in Electrical and Computer Engineering, including Jordan Johnson and Daniel Mortensen. His teaching includes Discrete-Time Systems and Signals and Convex Optimization , with a focus on practical signal processing applications.

Junghwan KimView profile

Professor

• Communication Systems
• Satellite Systems
• Anti-jamming Technologies
• +7 more

Junghwan Kim is a Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. His research focuses on advanced communication systems, including satellite architectures, wireless sensor networks, and anti-jamming technologies. He also explores physical layer encryption and digital multimedia broadcasting (DMB). His work emphasizes practical applications such as improving bit error rate (BER) in wireless systems through innovative modulation techniques like APSK-TCM and LDPC coding. Recent contributions include secure physical layer key generation for autonomous vehicles and machine learning approaches to face detection in noisy channels. Publications highlight advancements in satellite communication synchronization, cooperative localization in cellular networks, and error correction techniques for CDMA systems. His research bridges theoretical foundations with real-world challenges in telecommunications and cybersecurity.

Gian Luca ForestiView profile

Professor

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +2 more

Prof. Gian Luca Foresti is Full Professor of Computer Science at the University of Udine and Director of the Master in Intelligence and Emerging Technologies. His research spans artificial intelligence, computer vision, and cybersecurity with applications in medical imaging, industrial inspection, and aerial surveillance. Research develops novel neural architectures including capsule-enhanced models, physics-informed networks, and bio-inspired systems. Recent innovations address underwater imaging, federated medical AI, anomaly detection, and document analysis for cultural heritage preservation. Publications demonstrate leadership in multi-disciplinary applications, particularly medical imaging (MS segmentation, brain anomaly detection) and industrial automation (defect detection, quality control). Recent work shows emphasis on efficient models for edge deployment and security applications. Directs research initiatives in intelligence technologies, including drone swarm coordination for surveillance tasks and cybersecurity frameworks for containerized environments. Current projects span healthcare diagnostics, environmental monitoring, and heritage preservation.

Lazaros NalpantidisView profile

Professor

• Autonomous Systems
• Robot Perception
• Machine Learning
• +3 more

Lazaros Nalpantidis is a Professor at the Department of Electrical and Photonics Engineering at the Technical University of Denmark (DTU), leading the Perception and Cognition for Autonomous Systems group. He also serves as Head of the Automation and Control Group and Head of Studies for DTU's MSc in Autonomous Systems. Previously, he was an Associate Professor at Aalborg University and a postdoctoral researcher at KTH Royal Institute of Technology. His research focuses on autonomous systems, robot perception, and machine learning, with applications in robotics, construction automation, agriculture, and maritime systems. Key projects include the RoBétArmé Project for shotcrete construction automation and the development of vision-based systems for weed detection in agriculture. Publications highlight advancements in object detection, semantic 3D reconstruction, and maritime robotics. He has supervised multiple PhD students and contributed to datasets like RumexWeeds and ConRebSeg. His work aligns with UN SDGs, particularly sustainable agriculture and industry innovation. Notable awards include IEEE Senior Member (2020). Collaborations span academia and industry, addressing challenges in autonomous systems across diverse domains.

• Data Science
• Machine Learning
• Evolutionary Algorithms
• +4 more

Sibylle Sager-Müller is a Lecturer at the Lucerne School of Computer Science and Information Technology, part of Lucerne University of Applied Sciences and Arts (HSLU). She holds a Dipl.-Ing. in Mechanical Engineering from the University of Stuttgart and a Dr. sc. techn. from ETH Zürich, where she received the ETH Medal and ECCOMAS Prize. Her professional experience includes roles as a simulation engineer at Robert Bosch GmbH and as a Product Owner for Explainable AI projects in Powertrain Solutions. She has held visiting fellowships at Stanford University, California Institute of Technology, and NASA Ames Research Center. Education: Dipl.-Ing. Maschinenbau, Universität Stuttgart Dr. sc. techn. ETH Zürich (awarded ETH Medal & ECCOMAS Prize) Professional Experience: Simulationsingenieurin, Robert Bosch GmbH Product Owner for Explainable AI (AI in Powertrain Solutions), Bosch Visiting Fellowships: Stanford, Caltech, NASA Ames Her research focuses on data science , evolutionary algorithms , and optimization techniques , with applications in autonomous systems, fluid dynamics, and AI. Recent work emphasizes explainable AI (xAI) dashboards for computer vision and optimization of flow systems using stochastic and bio-inspired methods. Key projects include developing AI-assisted offering processes, analyzing transport company performance via geo-localized data, and studying customer behavior in e-bike sharing systems. Her publications span over two decades, with a strong emphasis on evolutionary strategies, machine learning, and their engineering applications. Awards: ETH Medal (ETH Zurich), ECCOMAS Prize, and recognition for contributions to computational methods in applied sciences. Advising & Grants: Extensive experience in project leadership across Bosch and academic collaborations, though specific grant details are not detailed in the provided text. She contributes to interdisciplinary teams in AI development and leads research on smart transportation systems and fluid dynamics optimization.

Michael SfakiotakisView profile

Professor

• Robotic Control Systems
• Bio-inspired Robotics
• Underwater Robotics
• +3 more

Michael Sfakiotakis is Professor of Robotic Control Systems and Director of the Computational Systems & Robotics Laboratory (CSRL) at the Hellenic Mediterranean University. His research spans bio-inspired robotics, autonomous systems, and educational technology, with particular expertise in underwater locomotion and agricultural applications. He has pioneered octopus-inspired robotic systems, developing multi-arm swimming robots and soft pneumatic manipulators. Agricultural robotics projects include disease detection frameworks for greenhouse crops and tomato harvesting robots. Educational contributions include remote-access laboratory platforms for engineering education. His publication trends demonstrate sustained innovation in biomimetic systems, particularly undulatory propulsion mechanisms for underwater robots. Recent work expands into agricultural automation and advanced control theory for autonomous vehicles in dynamic environments.

Dirk Martin LuchtenburgView profile

Associate Professor

• Dynamics and Control
• Fluid Mechanics
• Smart Vehicles
• +4 more

Dirk Martin Luchtenburg is an Associate Professor in the Department of Mechanical Engineering at The Cooper Union, holding the C. V. Starr Distinguished Professorship of Engineering. He leads the Dynamics and Control Lab, where undergraduate students design model-based controllers for smart vehicles such as quadcopters and ground robots. His research spans fluid mechanics, dynamics, and control systems, with applications in active flow control, nonlinear aerodynamics, and robotics. Education: He earned his MS in Aerospace Engineering from Delft University of Technology (Netherlands) and his PhD in Fluid Mechanics from TU Berlin. He held postdoctoral and lecturing roles at Princeton University before joining Cooper Union in 2013 as a research fellow, becoming a full-time faculty member in 2015. Key Research Areas: Fluid flows, feedback control, robotics, and model reduction. Applications: Active flow control, nonlinear stall models, and smart vehicle control. Recent work includes gyroscopic control of robotic systems, dynamic mode decomposition for complex systems, and compliant leg designs for robotic landings. His lab emphasizes hands-on student involvement in cutting-edge projects. Awards: C. V. Starr Distinguished Professor of Engineering (2023) Ben-Gurion University Summer Research Fellowship (2025) Grants & Advising: Co-authored papers with students, including David Shekhtman and Yeeho Song. Received the 2021 Educational Innovation Grant. Mentors undergraduates in the Dynamics and Control Lab, focusing on robotics and fluid dynamics research. Labs & Collaborations: Cooper Dynamics and Control Lab. Collaborations include work on plasma blasters and participation in conferences like ASME and ICRA.

Shayok MukhopadhyayView profile

Associate Professor

• Robotics and Automation
• Control Systems
• Nonlinear Systems
• +4 more

Shayok Mukhopadhyay is an Associate Professor in Electrical Engineering & Computer Science at the Tagliatela College of Engineering, University of New Haven. He holds a Ph.D. from Georgia Tech, an M.Sc. from Utah State University, and a B.E. from College of Engineering Pune. His research spans robotics, control systems, energy systems, and autonomous vehicles. Dr. Mukhopadhyay's work integrates advanced control algorithms with practical applications in renewable energy and robotic systems. Recent publications focus on electric vehicle traction optimization, battery management, and autonomous inspection robots. His research has been recognized with awards including the Best Presentation Award at the American Control Conference and the UAE AI and Robotics for Good Award. He leads projects developing AI-powered emergency response robots and serves as Chair of IEEE UAE's CSS/RAS/EMBS joint chapter. His lab explores robotic path planning, battery failure detection, and adaptive control for nonlinear systems.