Find Academic Supervisors

• Healthcare Applications
• ECG Signal Processing
• Sleep Apnea Detection
• +5 more

Nuno Gonçalo Coelho Costa Pombo is an active researcher and faculty member at the University of Beira Interior, Portugal, where he works in the School of Technology and Management within the Department of Computer Science. His academic career spans over a decade with consistent publication output from 2014 through 2025, demonstrating sustained research productivity and evolving expertise across multiple domains. Dr. Pombo's research interests center on the intersection of computer science and healthcare applications. His work prominently features ECG signal processing for medical diagnostics, with significant contributions to sleep apnea detection systems and clinical decision support systems . He has pioneered approaches in activities of daily living recognition using sensor data from mobile devices, which has important applications in elderly care and chronic disease management. His research methodology often combines machine learning techniques with Internet of Things (IoT) frameworks to create healthcare monitoring solutions that balance effectiveness with user privacy concerns. Recent work has expanded into educational technology applications, including augmented reality for programming instruction and futuristic thinking development in education. An analysis of Dr. Pombo's publication trends reveals a natural progression from foundational research in activity recognition to increasingly sophisticated healthcare applications. His early work focused on basic activity recognition frameworks, while more recent publications demonstrate advanced applications in specific medical conditions including diabetes management, mental health support, and cardiovascular diagnostics. The interdisciplinary nature of his research is evident in his extensive collaborations across engineering, medical, and social science domains, reflecting a holistic approach to healthcare technology development. Dr. Pombo maintains an active supervision role, with numerous publications featuring co-authors who appear to be students or early-career researchers. His work has been supported by research initiatives focused on healthcare technology innovation, though specific grant details are not evident from publication records. The consistent output across reputable venues including IEEE Access, Sensors, and international conferences demonstrates sustained research impact in his field.

• Multi-Robot Systems
• Robotic Swarms
• Autonomous Technologies
• +5 more

Spring Berman is an Associate Professor of Aerospace and Mechanical Engineering at Arizona State University (ASU), with affiliations in the School for Engineering of Matter, Transport and Energy, the Global Security Initiative, and the Center for Human, Artificial Intelligence, and Robot Teaming. She also holds an adjunct professorship in the Sandra Day O’Connor College of Law. Berman’s research focuses on multi-robot systems, swarm robotics, and biologically-inspired control strategies. She earned her Ph.D. (2010) and M.S. (2008) in Mechanical Engineering from the University of Pennsylvania and a B.S.E. (2005) in Mechanical and Aerospace Engineering from Princeton University. Her work includes grants from DARPA, NSF, and industry partnerships. She has led projects on swarm robotic control frameworks, boundary coverage, and cooperative manipulation. Berman teaches advanced engineering courses on system dynamics, control theory, and research methodologies. Her recent publications emphasize decentralized control strategies, swarm intelligence, and ethical considerations in autonomous systems. Her research activities span robotic swarm dynamics, autonomous vehicle testbeds, and human-swarm interaction. Key collaborations include projects on stochastic coverage strategies and multi-agent systems. Berman’s contributions bridge robotics, control theory, and societal applications through interdisciplinary initiatives.

• Marine Autonomy
• Autonomous Robotics
• Underwater Imaging
• +5 more

Blair Thornton is a Professor of Marine Autonomy at the University of Southampton's Engineering and Physical Sciences faculty. He specializes in autonomous marine robotics, sensing systems, and AI-driven data interpretation for oceanic research. As Co-Director of the FEPS In situ and Remote Intelligent Sensing (IRIS) Centre of Excellence, he leads projects advancing underwater exploration technologies. Education: PhD in Underwater Robotics (University of Southampton, 2006), with postdoctoral research at the University of Tokyo (2006–2016). Over 500 days at sea, leading 30 expeditions as Principal Investigator. Teaching includes modules on Maritime Robotics and Intelligent Mobile Robotics with practical robotics coding. Research focuses on 3D seafloor mapping, low-cost robotic platforms, and laser spectroscopy for in-situ chemical analysis. Collaborations include the National Oceanography Centre, Sonardyne International, and JAMSTEC. Awards include the Okamura Kenji Prize (2014), IEEE Mid-Career Rising Star (2022), and Japanese Government Open Innovation Prize (2024). Leading 15+ active/completed research projects, including BioCam (NERC), TechOceanS (EU), and DriftCam (EPSRC). Supervises 15+ PhD students in marine robotics and sensing. External roles include IEEE Journal reviewing and international conference speaking on seabed imaging and marine autonomy. Labs/Teams: Ocean Perception Group, Southampton Marine and Maritime Institute, and the IRIS Centre. Develops commercial survey services and robotic teaching platforms for field trials and education.

Chris LehnertView profile

Senior Lecturer

• Agricultural Robotics
• Robotic Perception
• Grasping Systems
• +4 more

Dr Chris Lehnert is a Senior Lecturer at the Queensland University of Technology (QUT) within the Faculty of Engineering, School of Electrical Engineering & Robotics. With over a decade of experience, he specializes in robotic perception and grasping systems, particularly in agricultural robotics. His research focuses include Robotic manipulation in cluttered environments Vertical farming automation Agricultural robotics Dynamic grasping systems He leads projects like 'Moving to See' and 'Harvey – The Robotic Capsicum Harvester', aiming to revolutionize agricultural automation through advanced robotic solutions. Dr Lehnert's publications and supervised research emphasize cooperative learning algorithms and 3D shape completion for harvesting tasks. He collaborates with prominent researchers including Peter Corke and Niko Sünderhauf, advancing practical applications in indoor cropping systems.

Ziping XuView profile

Research Fellow

• Statistical Reinforcement Learning
• Transfer Learning
• Multitask Learning
• +1 more

Ziping Xu is a Research Fellow in the Department of Statistics at Harvard University, working under Professor Susan Murphy. His research focuses on Statistical Reinforcement Learning, Transfer Learning, and Multitask Learning, with applications in mobile health and digital interventions. Research Focus: Xu develops sample-efficient algorithms for adaptive decision-making systems, statistical methods for inference in adaptive data collection, and transfer learning approaches for domain shifts. He leads RL algorithm design for clinical trials like ADAPTS-HCT, targeting medication adherence in young transplant patients. Publications: His 15 most recent publications demonstrate consistent focus on reinforcement learning optimizations for healthcare applications, algorithmic improvements for non-stationary environments, and theoretical advances in multitask learning. Recurrent themes include medication adherence systems, cryo-EM imaging optimization, and bandit algorithms for personalized medicine.

• Computational Geometry
• Sensor Networks
• Algorithm Design
• +2 more

Professor of Computer Science at City College of New York, currently on leave at NSF. Research expertise includes computational geometry, multi-robot systems, sensor networks, and algorithm design. Publications address geometric coverage problems, robot exploration strategies, and optimization in unreliable sensor environments. Develops algorithms for spatial computing problems including range-aggregate queries, tethered robot path planning, and event boundary detection. Theoretical work focuses on graph exploration complexity, k-center problems, and geometric inequalities. Author of 'Research Problems in Discrete Geometry' and contributor to advanced data structure design. Current NSF work involves fundamental algorithmic research supporting sustainable and equitable technology systems.

Magnus Berg LadefogedView profile

Research Fellow

• Operations Research
• Artificial Intelligence
• Maritime Search and Rescue
• +3 more

Magnus Berg Ladefoged serves as a PhD Fellow at Aalborg University's Department of Materials and Production within The Faculty of Engineering and Science. His research focuses on AI-driven operations optimization across maritime, logistics, and sensor network domains. His research interests leverage Operations Research and Artificial Intelligence to solve complex industrial problems. Key areas include maritime search-and-rescue pathfinding, automated sorting system optimization, and drone detection network design. His work integrates dynamic probability modeling, constraint programming, and heterogeneous system coordination to enhance operational efficiency in real-world scenarios. Recent publications reveal a strong trend toward applied AI in industrial systems , particularly maritime operations and logistics automation. His research bridges theoretical optimization with practical implementations in robotic sorting systems and emergency response frameworks. Magnus actively collaborates with researchers like A. K. Larsen and K. I. Kilic on projects spanning maritime safety, automated material handling, and drone surveillance networks. His work demonstrates significant potential for industrial implementation in port operations and supply chain management.

Fred LabrosseView profile

Senior Lecturer

• Robotics
• Autonomous Navigation
• Machine Vision
• +7 more

Fred Labrosse is a Senior Lecturer in the Department of Computer Science at Aberystwyth University, UK. He has been a core faculty member since 2000, contributing significantly to robotics education and research. His work bridges computer science, environmental science, and assistive technology through innovative applications of autonomous systems. PhD in Electrical Engineering, École Polytechnique de Montréal (1999) Postdoctoral Research, University of Bath, UK Senior Lecturer, Aberystwyth University (2000–present) Dr. Labrosse's research centers on robotics and machine vision, particularly in autonomous off-road navigation. His work includes topological mapping, cross-field navigation, and the development of custom robots such as multi-copters and fixed-wing UAVs. He applies these systems to real-world challenges in collaboration with archaeologists, biologists, and geographers, focusing on environmental monitoring and conservation. His research contributes to UN Sustainable Development Goals, particularly in environmental sustainability. His recent publications span autonomous navigation, smart wheelchairs, UAV-based animal tracking, and brain tissue classification. These works reflect a strong trend toward interdisciplinary robotics, combining visual perception, environmental adaptation, and human-centered design. His projects often involve low-cost, field-deployable systems for real-world impact. Dr. Labrosse has secured multiple research grants as Principal Investigator from organizations including Qinetiq, the Ministry of Defence, and the Higher Education Funding Council for Wales. He mentors several PhD and MPhil students, fostering the next generation of roboticists. His work has been featured in media coverage and academic talks, and is referenced in patents and Wikipedia, indicating broad influence. He leads or collaborates on various robotics initiatives, including the UK Robotics and Autonomous Systems Conference (UKRAS), and develops systems for applications ranging from peatland monitoring to care circle technology. His lab emphasizes practical, deployable robotics solutions that address societal and environmental challenges.

João Afonso Braun NetoView profile

Assistant Professor

• Autonomous Robotics
• Computer Vision
• Control Theory
• +3 more

João Afonso Braun Neto is an Assistant Professor at the Polytechnic Institute of Bragança (IPB), affiliated with the School of Technology and Management (ESTiG) and the Department of Electrical and Computer Engineering . He holds a Ph.D. (2024) and dual Master's/Bachelor's degrees (2019) in related fields. His research focuses on autonomous robotics, computer vision, control theory, deep learning, and AI , with over 40 publications in indexed journals and conferences. Affiliations and Roles: - Investigator at Center for Research in Digitalization and Intelligent Robotics (CeDRI) - Co-chair of European RoboCup Junior 2022 - Session chair at OL2A 2023 and ROBOT 2023 conferences - Thesis supervisor and jury member for academic projects Recognition: - Best Doctoral Thesis in Robotics (2024, Portuguese Robotics Society) - PhD with Impact Award (2023/2024) - INPhINIT and FCT doctoral fellowships - Media coverage in major Portuguese newspapers Research Contributions: - Pioneering work on mecanum-wheeled control, LiDAR-based navigation, and AI-driven localization systems - Active in robotics competitions and educational outreach - Collaboration with industry on precision agriculture and smart systems Labs/Teams: - Leading robotics workshops for secondary school teachers - Core member of CeDRI's robotics research initiatives

Briana WellmanView profile

Professor

• Robotics
• Artificial Intelligence
• Cybersecurity
• +3 more

Briana Wellman is a Professor and Associate Dean for Academics at the School of Engineering and Applied Sciences, University of the District of Columbia (UDC). She leads academic affairs while maintaining active roles in research and teaching, particularly in robotics, artificial intelligence (AI), and cybersecurity. Her academic career includes chairing the Department of Computer Science and Information Technology from 2017 to 2024. Education: Earned a Doctor of Philosophy in Computer Science from the University of Alabama. Research Interests: Focus on multi-robot systems, AI-driven cybersecurity solutions, computer science education innovation, and applying robotics in interdisciplinary contexts like fashion and disaster relief. Recent work emphasizes post-pandemic learning strategies for urban commuter campuses and hybrid anomaly detection models. Publications: Recent contributions include studies on malware detection using neural networks, post-pandemic education frameworks, and multi-robot coordination algorithms. Her work bridges theoretical advancements with practical applications in security and education. Awards: Recognized with the 2023 Women of Color Rising Star Award for her contributions to STEM education and research. Grants & Leadership: Secured multiple NSF grants, including funding for HBCU learning communities in computing, cybersecurity research centers, and AI-cybersecurity partnerships. Her leadership extends to academic program development and curriculum innovation. Labs/Teams: Involved in NSF-supported initiatives such as the Cyber Security Research and Development (CSRD) Center and the AI-CyS research partnership, fostering collaborative research ecosystems.

• Artificial Intelligence
• Machine Learning
• Anomaly Detection
• +3 more

Dr. Victoria J Hodge is a Research Fellow in the Department of Computer Science at the University of York, affiliated with the Centre for Assuring Autonomy (CfAA). She holds a PhD in Computer Science from the University of York and has industry experience in software architecture for medical diagnostics and industrial anomaly detection systems. Her research focuses on artificial intelligence (AI), anomaly detection, machine learning, and safety assurance for autonomous systems, particularly in robotics. Her work emphasizes through-life safety assurance of AI-driven autonomous systems, including robotics platforms operating in uncertain environments. She has authored over 70 publications across disciplines like AI, machine learning, robotics, and safety engineering. Notable projects include SCALOFT (drone safety analysis) and ASUMI (UAV safety assurance in mining). Her research trends show a strong emphasis on interdisciplinary applications of AI, with recent focus on autonomous systems in high-risk environments (e.g., mining, healthcare) and real-time decision support systems. Collaboration with industry ensures practical impact in domains like medical diagnostics and industrial automation.

Christopher KittsView profile

Professor

• Robotics
• Multi-robot Systems
• Control Systems
• +7 more

Christopher Kitts is the William and Janice Terry Professor of Mechanical Engineering at Santa Clara University's School of Engineering, where he also serves as Associate Dean of Research and Faculty Development and Faculty Director of the Ciocca Center for Innovation and Entrepreneurship. His external appointments include Associate Researcher at the Monterey Bay Aquarium Research Institute (MBARI) and Visiting Researcher at Lawrence Livermore National Laboratory, reflecting his interdisciplinary work in field robotics. He earned his Ph.D. and M.S. in Mechanical and Aerospace Engineering from Stanford University, M.P.A. in International & Defense Policy from the University of Colorado, and B.S.E. in Mechanical & Aerospace Engineering from Princeton University. Prof. Kitts' research centers on field robotics for scientific discovery and education, with key focus areas: Multi-robot systems design and coordination Collaborative Human/Cobot Control architectures Model-Based Anomaly Management for spacecraft Advanced robotic platforms for underwater, terrestrial, aerial, and space environments His recent publications (2022-2025) demonstrate growing emphasis on human-robot interaction through transformer networks and emotion detection, alongside continued innovation in marine robotics and adaptive navigation for environmental monitoring. Scientific recognition includes: ASME Fellow and AIAA Associate Fellow Multiple Santa Clara University awards across teaching, research, and service NASA Group Achievement Awards (8 total) Industry honors including Edison Innovation Award and AIAA National Award His program has secured tens of millions in funding from government agencies and industry partners for student-operated NASA spacecraft missions and MBARI marine robotics projects, resulting in documented scientific discoveries like tsunami wave evidence in Lake Tahoe. He directs the Robotic Systems Laboratory and Santa Clara's Maker Lab, creating hands-on educational frameworks that integrate entrepreneurial thinking with engineering practice.

• Robotics
• Computer Science
• Mechanical Engineering
• +8 more

Luis Enrique Moreno Lorente is a Full Professor in the Department of Systems Engineering and Automation at Carlos III University of Madrid, where he leads research in the Robotics Lab. He is affiliated with the Pedro Juan de Lastanosa Institute of Technology Development and Innovation and the Research Institute for Higher Education and Science (INAECU). Research Focus: Robotics, Soft Robotics, Control Systems, and Human-Machine Interaction Key Applications: Neurorehabilitation, Unmanned Aerial Vehicles, and Industrial Automation Research Trends in his recent work include: Soft robotic actuators using Shape Memory Alloys (SMA) Advanced path planning for UAV teams and Mars rovers Integration of Gaussian processes and evolutionary algorithms Wearable rehabilitation devices controlled by sEMG signals Mechanical design optimization for high-displacement actuators Supervised Theses cover topics like Global localization algorithms Evolutionary optimization techniques Intelligent actuator systems Cerebral palsy rehabilitation robotics Key Grants include projects funded by the European Commission, Arquimea Aerospace, and Spanish government initiatives in robotics and rehabilitation.

• Autonomous Vehicles
• Distributed Networks
• Intelligent Control
• +2 more

Dr. Junyan Hu is a researcher at the Department of Computer Science , Durham University. His work focuses on autonomous vehicles , distributed networks , intelligent control , and swarm robotics . Research Interests include: Autonomous Vehicles Distributed Networks Intelligent Control Multi-Agent Systems Swarm Robotics Recent Article Trends highlight applications in: Real-Time Multi-Robot Navigation Deep Reinforcement Learning for Traffic Signals Time-Optimal Swarm Trajectory Planning Decentralized Control with Fault Tolerance

Roi YehoshuaView profile

Academic

• Robotics
• Artificial Intelligence
• Adversarial Systems
• +3 more

Roi Yehoshua is an Associate Teaching Professor in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on adversarial robotics, multi-robot systems, and path planning. He has contributed to advancing algorithms for robotic coverage in dynamic environments, emphasizing real-time decision-making and adversarial modeling. His work spans theoretical foundations, algorithm development, and experimental validation. Key areas include adversarial game theory in robotics, multi-agent coordination, and optimization of coverage strategies. He has also explored risk-minimizing path planning and safety metrics in adversarial scenarios. Yehoshua’s publications since 2010 highlight a consistent focus on robotic systems under adversarial conditions, with early work extending to evolutionary algorithms and population fitness analysis. His research integrates robotics, artificial intelligence, and computer science to address challenges in autonomous systems.