Find Academic Supervisors

Nicolas P AvdelidisView profile

Professor

• Nondestructive Testing
• Aircraft Systems Monitoring
• Autonomous Systems
• +3 more

Nicolas P. Avdelidis is a Professor and Head of the Integrated Vehicle Health Management (IVHM) Centre at Cranfield University since July 2020. He also holds an Associate Professor position at Université Laval in Quebec, Canada. His research focuses on nondestructive inspection, robotic autonomous systems in MRO, advanced monitoring technologies, and aircraft systems health management . He collaborates extensively with institutions like the National Research Council (NRC) and industry partners. His expertise spans non-invasive imaging techniques for composites, thermal imaging, structural diagnostics, and sustainable aviation innovations . Key projects include developing hybrid prognostics for aircraft systems and autonomous systems integration. He leads Cranfield’s IVHM Centre, fostering interdisciplinary research in vehicle health management and sensor technologies. Notable collaborations include work with the NRC, Fraunhofer Institute, and international teams. His research bridges theory and practice, emphasizing solutions for aerospace safety and sustainability through AI-driven diagnostics and autonomous technologies.

Greg DrogeView profile

Assistant Professor

• Model Predictive Control
• Robotics
• Autonomous Systems
• +6 more

Greg Droge is an Assistant Professor in the Department of Electrical and Computer Engineering at Utah State University's College of Engineering, specializing in systems and controls. He earned his PhD (2014) and MS (2012) from Georgia Institute of Technology in Electrical and Computer Engineering, and a BS (2009) in Electrical Engineering from Brigham Young University. His research focuses on Model Predictive Control (MPC) for multi-agent systems , particularly in satellite formation flying , autonomous vehicle path planning , and electric bus charging optimization . His work integrates control theory with practical applications in aerospace and transportation systems, including uncertainty modeling for radar detection and curvature-constrained vehicle navigation. Recent publications emphasize stochastic scheduling , graph-based optimization , and mission planning for robotic systems. His research has been recognized by multiple awards including Faculty Researcher of the Year (2024) and Teacher of the Year (2022) . Faculty Researcher of the Year, College of Engineering, 2024 Researcher of the Year, Department of Electrical and Computer Engineering, 2024 Teacher of the Year, Electrical Engineering Department, USU, 2022 Dr. Droge has mentored numerous graduate students and taught courses such as Introduction to Planning and Control for Mobile Robots, Robot Operating System (ROS), and Linear Multivariable Control at USU since 2019.

Louise DennisView profile

Associate Professor

• Artificial Intelligence
• Autonomous Systems
• Formal Verification
• +3 more

Dr. Louise Dennis is an Associate Professor at the University of Manchester's Department of Computer Science, specializing in artificial intelligence, autonomous systems, and formal verification. Her work focuses on developing verifiable systems, ethical reasoning in AI, and agent-based architectures. She contributes to the Centre for Digital Trust and Society and the Centre for Robotics and Artificial Intelligence, advancing research in safety-critical systems and human-AI collaboration. Her research interests span formal verification of autonomous systems, machine ethics, and agent programming languages. Notable projects include work on BDI agent models, ROS-based robotics verification frameworks, and ethical decision-making modules for space and nuclear systems. She actively participates in interdisciplinary initiatives addressing future computing risks and AI transparency. Key contributions include developing verification tools like Agent JPF and the PROSPER Toolkit, as well as pioneering ethical reasoning frameworks for autonomous robots. Recent work emphasizes explainability in safety-critical contexts and assurance case methodologies for robotic systems. Dr. Dennis collaborates internationally on standards for transparent autonomous systems (e.g., IEEE P7001) and advises on critical infrastructure resilience. She has delivered invited talks on machine ethics and verification, and her research spans robotics, cybersecurity, and space exploration applications.

• User Experience Design
• Human-Computer Interaction
• Human-Robot Interaction
• +3 more

Beatrice Alenljung is an Associate Professor of Information Technology at the University of Skövde, Sweden, leading the Interaction Lab. She specializes in human-centered technology research with a focus on user experience (UX) design, human-robot interaction, and decision support systems. Her work bridges theoretical insights with practical applications in fields like healthcare robotics, industrial automation, and educational technology. She teaches in the User Experience Design program and actively contributes to interdisciplinary projects addressing challenges in aging populations, industrial collaboration, and sustainable digital transformation. Key ongoing projects include exploring socially assistive robots for older adults (RoSA and RO-LIV), optimizing human-robot collaboration in manufacturing (KOMPARO and AIHURO), and risk reduction strategies for emergency services through digital simulation. Her research emphasizes empirical studies on UX evaluation frameworks (e.g., ANEMONE), human factors in robotics, and the societal impacts of emerging technologies. Alenljung has authored over 40 peer-reviewed publications, spanning conference papers and book chapters in HCI, robotics, and requirements engineering. She holds a PhD in Decision Support Systems from the University of Skövde and has maintained collaborative ties with industries and institutions across Europe.

Juan SandinoView profile

Research Fellow

• Autonomous Systems
• Reinforcement Learning
• Remote Sensing
• +6 more

Dr. Juan Sandino is a Research Fellow at the QUT Centre for Robotics, affiliated with the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT). He holds a BEng (Mechatronics) from Nueva Granada Military University and a PhD in Robotics and Autonomous Systems from QUT (2022). His research focuses on autonomous UAV decision-making, machine learning, and remote sensing for environmental monitoring, biosecurity, and search and rescue operations. Education : PhD in Robotics and Autonomous Systems (2018–2022), QUT Bachelor of Engineering (Mechatronics, 2010–2015), Nueva Granada Military University Diploma in Project Management (2017–2018), Australian Pacific College Research Interests : Dr. Sandino specializes in developing drone-based solutions for environmental challenges. His work integrates autonomous systems, reinforcement learning, and hyperspectral imaging to address issues such as biosecurity threats, Antarctica's fragile ecosystems, and search and rescue missions in GPS-denied environments. His projects include UAV frameworks for planetary exploration (UAV4PE), detection of invasive species like Bitou Bush and Parthenium Weed, and real-time vegetation monitoring in polar regions. Awards & Recognition : CSIRO Data61 PhD and Top-Up Scholarships (2018–2021) Best Team Award, QUT Centre for Robotics (2021) Phase 1 Finalist, OpenCV AI Competition (2021) Projects & Grants : He leads projects funded by the Australian Research Council (SAEF initiative) and industry partners, including aerial mapping of forests affected by pathogens, UAV-based monitoring in Antarctica, and pest risk modeling for Buffel Grass. His work emphasizes collaboration with organizations like CSIRO Data61 and Charles Sturt University. Labs & Teams : Dr. Sandino contributes to the Securing Antarctica’s Environmental Future (SAEF) initiative and collaborates with interdisciplinary teams at QUT’s Centre for Robotics. His research integrates robotics software (ROS, PX4), sensor instrumentation, and AI for real-world applications.

Daniel CasiniView profile

Assistant Professor

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +3 more

Dr. Daniel Casini is an Assistant Professor at the Department of Information Engineering and Computer Science, Sant'Anna School of Advanced Studies. His academic journey includes a PhD (2016–2019) and postdoctoral research (2019–2021) in Real-Time Systems. He specializes in real-time scheduling algorithms, edge computing, and embedded system predictability. His work focuses on optimizing latency, resource allocation, and security in cyber-physical systems. Education: PhD in Computer Science, Sant'Anna School of Advanced Studies (2016–2019) Postdoctoral Researcher in Real-Time Systems (2019–2021) Research Interests: Real-Time Scheduling (Partitioned/EDF/Gang Scheduling) Edge Computing and Predictable Virtualization Middleware Optimization (DDS/ROS 2) Hardware-Software Co-Design for Cyber-Physical Systems Security-Temporal Trade-offs in Critical Systems Key Contributions: Developed MATERIAL framework for edge real-time applications on QNX RTOS Pioneered analysis of QNX IPC predictability and Linux kernel noise Designed latency-optimized thread chains for DDS middleware Awards: IEEE TCCPS Early-Career Award 2023 Labs/Teams: Active contributor to the SPHERE project, developing heterogeneous multi-SoC architectures for next-gen cyber-physical systems.

• Robotics
• Electronics Engineering
• Artificial Intelligence
• +3 more

María Elena López Guillén is a Professor in the Department of Electronics at the University of Alcalá. She holds a Ph.D. from the same institution (2004), focusing on navigation systems for personal assistance robots using partially observable Markov decision processes. Her research group, Robesafe, specializes in service robotics and e-safety technologies. Her work spans robotics, autonomous systems, and biomedical engineering. Key areas include SLAM algorithms, sensor fusion, electrooculography-based interfaces, and assistive technologies for the visually impaired. She has authored over 50 publications since 1995, with recent focus on real-time semantic segmentation, multi-sensorial navigation, and wheelchair control systems. Notable contributions include pioneering research on EOG-based human-computer interaction, low-cost UAV navigation systems, and robotic solutions for healthcare applications. Her work bridges theoretical robotics with practical implementations in safety-critical environments.

Chase MurrayView profile

Associate Professor

• Operations Research
• Autonomous Vehicles
• Vehicle Routing & Logistics
• +5 more

Chase Murray is an Associate Professor in the Department of Industrial and Systems Engineering at the University at Buffalo (SUNY). He directs the SOAR Drone Facility and Optimator Lab , focusing on operations research applications for autonomous systems. His work includes drone logistics, routing optimization, and AI integration in delivery networks. Education: PhD, Industrial & Systems Engineering, University at Buffalo, 2010 ME, Industrial Engineering, Texas A&M University, 2000 BS, Industrial Engineering, Texas A&M University, 1998 Research Interests: Dr. Murray’s research emphasizes leveraging autonomous vehicles for logistics and surveillance. Key areas include: - Routing algorithms for drone-truck systems - Weather and traffic impact modeling - Integer programming for problem classification - FAA-certified drone pilot with hands-on SOAR facility testing . Publications: Over 30 peer-reviewed articles focus on drone coordination, vehicle routing, and optimization frameworks. Recent work includes graph-based ILP classification and weather-aware delivery systems. Labs & Software: SOAR : Drone test facility with 3D digital twin simulations Optimator Lab : Develops tools like VeRoViz (routing visualization) and tex2solver (LaTeX-to-code translator) Open-source projects: Ground Control Station software, ROS-enabled web interfaces Grants & Advising: Advised PhD students Ritwik Raj (traffic congestion modeling) and Lan Peng (weather-impact scheduling). Active in collaborative projects on AI-driven logistics systems.

Savvas ChatzichristofisView profile

Professor

• Artificial Intelligence
• Computer Vision
• Robotics
• +6 more

Savvas Chatzichristofis is a Professor of Artificial Intelligence and Head of the Department of Computer Science at Neapolis University Paphos (NUP). He also serves as Vice-Rector of Research and Innovation, overseeing strategic R&D initiatives. His research focuses on AI, computer vision, robotics, and their applications in education, urban systems, and autonomous systems. Education: Holds a Diploma (M.Eng.) and Ph.D. in Computer Vision from Democritus University of Thrace. Previously served as a special scientist, visiting lecturer, and researcher at multiple institutions. Research Interests: AI-driven educational technologies Robotics in pedagogy and industry Autonomous systems (UAVs/AUVs) Blockchain for sustainability monitoring Machine learning optimization Notable Projects: NOPTILUS: Autonomous underwater/air vehicle navigation sfly: Swarm robotics for mapping EU-funded projects on smart cities and green bonds Publications span AI ethics, UAV efficiency, educational robotics, and blockchain frameworks, with over 50 peer-reviewed articles since 2011.

Niko SuenderhaufView profile

Professor

• Robotic Vision
• Computer Vision
• Machine Learning
• +7 more

Professor Niko Suenderhauf is a leading researcher in robotic vision and AI at Queensland University of Technology (QUT). He focuses on enabling robots to understand and interact with their environment through advancements in SLAM, scene understanding, and semantic mapping. His work bridges robotics, computer vision, and machine learning, aiming to create reliable, relatable, and sustainable robotic systems that collaborate with humans to address societal challenges like climate change and aging populations. His key achievements include pioneering graph-based SLAM methods integrated into the ROS ecosystem, developing object-based semantic SLAM systems, and demonstrating the efficacy of deep learning for place recognition. Collaborations with institutions like DeepMind and Amazon reflect his interdisciplinary approach. Awards include recognition for groundbreaking SLAM research and highly cited publications. Research interests emphasize open-world navigation, privacy-preserving vision, and embodied AI, with a focus on practical applications in construction, environmental monitoring, and domestic robotics. His work on uncertainty quantification and robust perception ensures systems operate safely in unpredictable environments. Professor Suenderhauf actively engages in education, mentoring students across undergraduate and postgraduate levels, and emphasizes the societal impact of technology through collaborations with neuroscience, law, and design experts.

Ken GoldbergView profile

Professor

• Artificial Intelligence
• Robotics
• Deep Reinforcement Learning
• +5 more

Ken Goldberg is a Professor of Industrial Engineering and Operations Research at UC Berkeley, with secondary appointments in EECS, Art Practice, and UCSF's Radiation Oncology. He joined UC Berkeley in 1995 and holds a PhD from Carnegie Mellon University (1990) and dual degrees from the University of Pennsylvania (1984). His research spans robotics, automation, and art, focusing on artificial intelligence, medical robotics, and human-robot interaction. He leads the AUTOLab and is a co-founder of the Berkeley Artificial Intelligence Research (BAIR) Lab. Goldberg's art installations, including collaborations with Sundance films, explore the intersection of technology and humanity. He has pioneered cloud robotics, surgical robotics, and collaborative filtering systems. Notable awards include the IEEE Fellow (2005), Joseph Engelberger Robotics Award (2000), and NSF Presidential Faculty Fellow (1995). His work integrates technical innovation with societal impact, emphasizing ethical AI and automation. Educations: PhD in Computer Science, Carnegie Mellon University (1990) BSEE in Electrical Engineering, University of Pennsylvania (1984) BSE in Economics, UPenn Wharton (1984) Research Interests: Goldberg's work bridges robotics, AI, and art. Key areas include cloud robotics (FogROS2), surgical robotics (Cal-MR), AI ethics, and interactive systems. His research in dexterous manipulation and grasp planning (Dex-Net) has advanced robotic capabilities in manufacturing and healthcare. Publications: Over 300 papers, including influential works on grasp planning, robotic learning, and collaborative filtering. Recent focus on AI in robotics, surgical assistance, and ethical automation. Awards: IEEE Fellow (2005) Joseph Engelberger Robotics Award (2000) NSF Presidential Faculty Fellow (1995) Advising and Grants: Supervised numerous students in robotics, automation, and AI. Active in funding initiatives like the National Robotics Initiative and NSF grants. Labs/Teams: Leads AUTOLab and co-founded the Berkeley Center for New Media (BCNM). Collaborates with industry partners like Ambi Robotics and Jacobi Robotics.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +14 more

Evren Dağlarlı is an Associate Professor in the Department of Computer Engineering at the Faculty of Computer and Informatics, Istanbul Technical University. He holds a Ph.D. in Control and Automation Engineering from ITU and has extensive experience in robotics, artificial intelligence, and intelligent systems. He is actively involved in research projects and has published in top-tier IEEE conferences and journals. Ph.D., Control and Automation Engineering, Istanbul Technical University (2008–2019) M.Sc., Mechatronics Engineering (Intelligent Systems and Robotics), Istanbul Technical University (2005–2007) B.Sc., Electrical Education, Marmara University (2000–2004) B.Sc., Electrical-Electronics Engineering, Ege University (2021–2023) His research focuses on robotics, artificial intelligence, human-robot interaction, cognitive neuroscience, and machine learning . He develops brain-inspired cognitive architectures and applies them to humanoid robots and autonomous systems. His work integrates deep learning, personality modeling, and explainable AI to enhance intelligent behavior in machines. Recent publications highlight a strong trend in generative AI, personality-integrated language models, UAV design, and computational cognitive modeling . His work bridges neuroscience and AI, aiming to create more adaptive, self-aware, and explainable robotic systems. He frequently collaborates with E. Aribas on topics ranging from UAVs to AI-driven personality modeling. Yenilikçilik Ödülü (Innovation Award), Istanbul Technical University, 2024 He has supervised students and co-authored multiple papers with advisees. He has participated in national and international research projects, including the Gökbörü Alemdar Savaşan İHA Projesi (2024–2025). His technical expertise includes ROS, embedded systems, real-time operating systems, and AI frameworks. He is a member of IEEE, ACM, and ASME and actively contributes to the advancement of intelligent systems through research, development, and academic mentorship.

Nikola MiškovićView profile

Professor

• Marine Robotics
• Autonomous Underwater Vehicles (AUV)
• Human-Robot Interaction
• +3 more

Nikola Mišković is a Full Professor at the Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing, University of Zagreb. His work focuses on marine robotics and autonomous systems. Marine Robotics Autonomous Underwater Vehicles (AUV) Human-Robot Interaction Control Systems Sonar Data Processing His research explores underwater localization, formation control, and sensor integration with applications in aquaculture and environmental monitoring. Projects include EU-funded initiatives like FP7 CADDY , H2020 EXCELLABUST , and subCULTron . Key collaboration networks involve institutions in Croatia, Israel, and EU marine robotics consortia. His work demonstrates strong integration of simulation (Gazebo, LabVIEW) and real-world deployment.

• Formal Methods
• Software Engineering
• Formal Verification
• +5 more

Alcino Cunha is an Associate Professor with habilitation at the Department of Informatics of the University of Minho. He is a member and co-coordinator of the High-Assurance Software Laboratory, part of the University of Minho and INESC TEC. His research focuses on making formal software design accessible, particularly through advancements in the Alloy framework, including Alloy4Fun and Alloy Version 6. He has contributed to tools like HAROS for robotic software verification and Echo for model repair. Teaching roles include Formal Methods in Software Engineering (MSc), Formal Verification (MSc), and Algorithmic Problem Solving Lab (BSc). He has led projects such as SAFER (robotic safety verification), TRUST (Alloy-based design), and DigiLightRail (railway network verification). His service includes PC roles at SEFM 2025, ABZ 2025, and QRARSAC conferences. Research highlights include formal specification education, temporal relational modeling (Pardinus), and verification of distributed systems. Collaborations with ONERA and INESC TEC have produced influential frameworks like Alloy4Fun and Electrum. His work bridges academia and industry, notably through consultancy with EFACEC and contributions to national CRIS ecosystems (PTCRISync).

Venkata Prashanth UppalapatiView profile

Researcher

• Robotics
• Autonomous Systems
• Human-Computer Interaction
• +3 more

Venkata Prashanth Uppalapati is a Researcher at the Faculty of Mechanical Engineering , Schmalkalden University of Applied Sciences , focusing on Robotics and Mechatronics . Specializes in Autonomous Systems , Human-Centered Robotics , and Educational Technology Key projects include outdoor autonomous logistics solutions , MicroROS-based controllers , and V2X communication for urban robots Research Highlights: His work bridges mobile robotics with human factors , emphasizing cost-effective prototyping and educational tools for robotics training. Recent Publications address: Low-cost drive systems for outdoor logistics robots MicroROS and RViz integration for educational modules V2X-enabled decision-making in urban environments