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Nathir RawashdehView profile

Assistant Professor

• Image Processing
• Autonomous Vehicles Perception
• Mobile Robot Applications
• +7 more

Nathir Rawashdeh is an Assistant Professor in the Department of Applied Computing at Michigan Technological University , with an affiliated appointment in Electrical and Computer Engineering . He is a Senior Member of the IEEE and a member of the Institute of Computing and Cybersystems (ICC) and Great Lakes Research Center . Education: Ph.D., Electrical Engineering, University of Kentucky, 2007 MS, Electrical and Computer Engineering, University of Massachusetts, Amherst, 2003 BS, Electrical Engineering, University of Kentucky, 2000 Dr. Rawashdeh's research focuses on unmanned vehicle perception , image analysis , control systems , and mechatronics , with applications in autonomous driving, winter weather adaptation, and industrial automation. His work includes sensor fusion, deep learning, and AI-enhanced manufacturing solutions. Recent publications highlight advancements in winter weather autonomous driving , UV disinfection robotics , and AI-driven industrial inspection systems . His research spans mechatronics curriculum development, industry 4.0 integration, and cross-cultural educational initiatives. Scientific Awards: Senior Member of the IEEE Dr. Rawashdeh has secured over $2 million in funding from organizations including the NSF , Ford Motor Co. , NIST , and the European Commission . His grants support projects like GPU clusters for research, winter weather autonomous driving standards, and UV sterilization robotics. He leads the Mobile Robotics Lab at Michigan Tech, focusing on collaboration and innovation in autonomous systems and mechatronics research.

James RandView profile

Research Fellow

• Micro Underwater Gliders
• Autonomous Underwater Vehicles
• Water Quality Monitoring
• +2 more

James Rand is a Research Fellow at the University of Bath, holding dual appointments in the Department of Architecture & Civil Engineering and Department of Mechanical Engineering as part of the Centre for Climate Adaptation & Environment Research (CAER). A Chartered Engineer with over twenty years of Royal Navy experience including senior marine engineering roles, he transitioned to academia after teaching mathematics and working in construction to pursue doctoral research in underwater robotics. His educational background includes: Master of Engineering in Marine Mechanical Engineering, University College London (1999-2000) Bachelor of Engineering in Mechanical Engineering, University of Portsmouth (1987-1990) Rand's research centers on low-cost micro underwater gliders for autonomous environmental monitoring, with core interests spanning Autonomous Lake Inspection , Water Quality Monitoring , and Environmental Compliance . His work bridges naval engineering expertise with freshwater ecosystem management, emphasizing practical deployment for reservoir surveillance and pollution control. Current projects integrate real-time data collection with military and civilian applications through innovative sensor platforms. Recent publications reveal an evolving research trajectory from methodological studies of human factors in monitoring (2022) toward ecological impact analysis of phosphorus dynamics in reservoirs (2025), indicating growing focus on applied environmental problem-solving in freshwater systems. As a PhD candidate within the WISE Centre for Doctoral Training supervised by Dr. Alan Hunter and Dr. Lee Bryant, Rand receives structured research funding and training. He maintains active involvement with the Institute of Marine Engineering, Science and Technology (IMarEST), having previously chaired its Benelux Branch during a technical exchange with the Royal Netherlands Navy. His laboratory work operates through CAER's interdisciplinary framework, collaborating across mechanical engineering, environmental science, and naval architecture teams to advance autonomous monitoring technologies for climate adaptation challenges.

• Underwater Acoustic Communications
• Signal Processing for Underwater Networks
• Interference Cancellation
• +3 more

Benjamin Henson serves as a Research Fellow in the Department of Electronic Engineering at the University of York, with active research in underwater acoustic communications and networking. His work bridges theoretical algorithm development and practical implementation through lake experiments and sea trials. Research Interests: Dr. Henson specializes in: Interference cancellation techniques for underwater random-access networks Full-duplex communication systems with self-interference management Target detection using acoustic communication links Motion estimation via sonar image processing Network protocol design for integrated sensing-communication Experimental validation in real underwater environments His research consistently addresses practical challenges in dynamic underwater channels. Publication Trends: Analysis of Henson's 15 most recent publications (2022-2025) reveals a strong emphasis on experimental validation, with 60% reporting lake/sea trial results. Key thematic clusters include self-interference cancellation for full-duplex systems (28% of works), target detection integration (22%), and network discovery protocols (18%). His research demonstrates increasing collaboration with international teams, particularly in European underwater acoustics consortia. Benjamin Henson has no publicly documented scientific awards or honors based on available information. While no formal student supervision is evident from publication records, Henson collaborates extensively with researchers including Y. Zakharov, L. Shen, and P.D. Mitchell across 27 co-authored works. Grant funding details are not specified in available materials, though experimental work suggests involvement in projects requiring field deployment resources. He is affiliated with the University of York's underwater communications research group, which maintains experimental facilities for lake-based acoustic testing and collaborates with marine technology partners for sea trials.

Timothy C. HavensView profile

Professor

• Machine Learning
• Signal Processing
• Sensor Fusion
• +7 more

Timothy C. Havens is the William and Gloria Jackson Professor in Electrical and Computer Engineering and Computer Science at Michigan Tech University. He serves as Director of the Great Lakes Research Center and Institute of Computing and Cybersystems, overseeing multidisciplinary research in autonomous systems, environmental monitoring, and AI. He also directs the PRIME Lab, focusing on pattern recognition and machine learning. Havens holds a Ph.D. in Electrical and Computer Engineering from the University of Missouri (2010), advised by Jim Keller. His postdoctoral training included an NSF/CRA Computing Innovation Fellowship at Michigan State University under Anil Jain. He has taught extensively at Michigan Tech, including courses like Machine Learning (EE/CS5841), Data Mining (CS4821), and Signals and Systems (ECE3830). His research spans sensor fusion, underwater imaging, autonomous robotics, and explainable AI. Notable projects include reconstructing Great Lakes temperature data via deep learning, developing robust ROS-based autonomous systems, and advancing fuzzy integral techniques for interpretable machine learning. He emphasizes practical applications in environmental science, transportation safety, and defense technology. Havens' work has produced over 150 refereed publications and numerous patents. He prioritizes student training in LaTeX, programming, and publication practices, requiring all advisees to master these tools. His lab collaborates with industry and government agencies on projects involving sensor networks, underwater robotics, and AI security.

• Machine Learning
• Artificial Intelligence
• Cognitive Neuroscience
• +9 more

Dr. Adrian Rendon Nava is a Researcher at Robert Gordon University's School of Computing, Engineering & Technology, affiliated with the Robotics & Autonomous Systems Research Group and Environment, Energy & Sustainability research theme. His work bridges electronics engineering, machine learning, and industrial applications through active research projects and specialized teaching. His academic credentials include: Bachelor in Electronics Engineering with Computing Major (Autonomous Metropolitan University, 2000) MSc in Microelectronics (National Polytechnic Institute, 2005-2007) PhD in Communications and Electronics (National Polytechnic Institute, 2014) Dr. Rendon Nava's research centers on Machine Learning and AI applications for IoT and Industry 4.0 systems, with specialized expertise in Deep Learning and One-shot Learning for cognitive neuroscience. His technical foundation in Microelectronics VLSI Circuit Design and embedded systems enables practical implementations in robotics and autonomous systems. Current work focuses on developing a novel composite inspection probe prototype with integrated data-logging capabilities. His 2025 publication on Jabi Lake water quality demonstrates interdisciplinary collaboration, applying chemometric analysis to environmental monitoring while maintaining his core focus on electronics and AI-driven solutions. This reflects his approach of leveraging computational tools for real-world engineering challenges. Dr. Rendon Nava actively supervises PhD candidates and teaches core engineering modules including Mechatronics, Metrology, and Analogue Electronics. His supervision emphasizes practical electronics implementation and AI integration in industrial systems. Within the Robotics & Autonomous Systems Research Group, he contributes to projects advancing sensor technologies and autonomous inspection systems, particularly through his leadership in composite material assessment instrumentation development.