Find Academic Supervisors

• Software Engineering
• Data Management
• Interoperability Systems
• +3 more

Dr. Roland Koppe is Head of Software Engineering at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (AWI), leading the Architecture and Portal Solutions team within the 'From Observations to Archives and Analysis (O2A)' group. His work focuses on software engineering, interoperability of heterogeneous systems, and data modeling to enable seamless data flow from sensor observations to archival and publication systems. He is a key contributor to initiatives such as the Data Portal German Marine Research, the O2A framework, and the CRITTERBASE biodiversity data warehouse. Research Interests: Software Engineering methodologies for scientific data systems, engineering management of large-scale projects, interoperability standards for marine and climate data, and FAIR data principles implementation in collaborative frameworks. His work addresses challenges in managing heterogeneous sensors, automating quality control, and integrating data across marine, polar, and climate research domains. Developed the O2A framework to streamline sensor data workflows Core contributor to the Data Portal German Marine Research Architect of CRITTERBASE for polar marine biodiversity data Lead software engineering for MOSAiC Arctic expedition data management Contributed to Digital Earth initiatives and MOSES flood modeling projects Publications focus on sensor data management systems, FAIR implementation, and interdisciplinary data integration challenges in polar and marine research. His work emphasizes scalable solutions for heterogeneous data sources and collaborative scientific workflows.

• Internet of Things
• Edge Computing
• Smart Agriculture
• +5 more

Professor Yi-Bing Lin is a distinguished faculty member in the Department of Computer Science at National Yang Ming Chiao Tung University, Taiwan, where he leads pioneering research in Internet of Things (IoT) systems and applications. His work primarily focuses on developing the IoTtalk platform and its numerous derivatives across various domains including smart agriculture, smart homes, environmental monitoring, and creative applications. His research interests span Internet of Things, Edge Computing, Smart Agriculture, Sensor Networks, AI Integration, Wireless Networking, and Smart Home Systems. Professor Lin has developed the IoTtalk framework that enables rapid development of IoT applications with numerous specialized implementations including VoiceTalk, SensorTalk, AgriTalk, and many others that address specific domain challenges. His work emphasizes practical implementations with real-world impact, particularly in precision agriculture where his team has developed systems for orchid disease detection, rice blast monitoring, turmeric farming, and watermelon ripeness prediction. Analysis of his recent publications (2023-2025) reveals a strong trend toward integrating AI with IoT systems, particularly for agricultural applications and smart environments. His work increasingly incorporates advanced techniques like continuous wavelet transform, deep learning, and computer vision to solve practical problems in precision farming and environmental monitoring. The publications also show growing interest in creative applications of IoT technology for performing arts, interactive experiences, and educational contexts. Professor Lin has received recognition through consistent high-volume publication output in top-tier venues including IEEE Internet of Things Journal, IEEE Access, and Sensors. His collaborative network is extensive, with frequent co-authorship with researchers like Yun-Wei Lin, Wen-Liang Chen, and Min-Zheng Shieh. His advising has produced numerous researchers who continue to work in IoT and related fields, with many former students maintaining collaborative relationships. Professor Lin's research has been supported by multiple grants enabling the development of practical IoT systems with real-world implementations. His lab has developed numerous specialized IoT applications through the IoTtalk framework, creating a cohesive research ecosystem. Current work shows expansion into new application domains including interactive miniature worlds, simultaneous performance across locations using IoT-based motion capture, and IoT-based musical instruments like piano playing robots and violin robots, demonstrating the versatility of his research approach.

• Analog Circuits Design
• CMOS Technology
• Signal Processing
• +3 more

Ramón González Carvajal is a distinguished academic with extensive contributions in analog and mixed-signal integrated circuit design, IoT systems, and sensor networks. His research focuses on low-voltage CMOS circuits, high-performance operational amplifiers, and energy-efficient signal processing. He has collaborated extensively with institutions on advancements in smart infrastructure and sustainable energy systems. Key research areas include: Low-power analog circuit design CMOS-based transconductors and amplifiers IoT-enabled sensor networks for industrial and environmental monitoring Blockchain scalability through sharding protocols His recent work emphasizes machine learning applications for energy economy prediction and augmented reality systems for workplace safety. Over 196 publications demonstrate his impact in circuits, systems, and emerging technologies.

James FraserView profile

Professor

• Ultrafast Nanosystems
• Laser Material Processing
• Coherent Imaging
• +4 more

James M. Fraser is a Professor of Physics at Queen's University, Canada, leading an experimental research team in coherent imaging, ultrafast nanosystems, and laser processing. He holds a PhD from the University of Toronto and has pioneered real-time monitoring techniques for high-power laser manufacturing, including welding and additive manufacturing. His work bridges fundamental physics and industrial applications, with six patents and the co-founding of Laser Depth Dynamics, now part of IPG Photonics. Fraser is recognized for teaching excellence, winning the CAP Teaching Medal and 3M National Fellowship. He directs the NSERC CREATE-MAPS program, fostering interdisciplinary training in photonics and sensing for graduate students in Physics, Chemistry, and Chemical Engineering. Research interests include optoelectronic properties of carbon nanotubes, 2D materials, and laser processing dynamics. His innovations in inline coherent imaging enable real-time control of manufacturing defects and material behavior. Fraser's contributions span academic publications, patents, and industry partnerships, emphasizing both scientific discovery and practical application. Education: PhD, University of Toronto Awards: CAP Teaching Medal, 3M National Fellowship, OCE Martin Walmsley Fellowship Labs/Teams: Experimental Physics Lab, Laser Depth Dynamics (spin-off)

Mohsen SooriView profile

Assistant Professor

• Artificial Intelligence
• Manufacturing Processes
• Industry 4.0
• +3 more

Dr. Mohsen Soori is an Assistant Professor in the Department of Mechanical Engineering at the Faculty of Engineering, Eastern Mediterranean University. His research focuses on integrating artificial intelligence (AI), machine learning, and deep learning into advanced manufacturing processes, particularly in Industry 4.0 applications such as smart quality control, human-robot collaboration, and additive manufacturing optimization. He also specializes in CNC machining optimization, virtual machining systems, and error compensation in precision manufacturing. Dr. Soori holds a Ph.D. in Mechanical Engineering from Eastern Mediterranean University (2022), an M.Sc. from Amirkabir University of Technology (2012), and a B.Sc. from Shahid Rajaee Teacher Training University (2007). His academic work bridges theoretical advancements in numerical methods (e.g., variational iteration, finite element analysis) with practical industrial challenges in machining, robotics, and sustainability. His recent publications (2023–2025) emphasize AI-driven solutions for Industry 4.0, including blockchain-enabled supply chains, smart manufacturing systems, and virtual machining analytics. He has also contributed to studies on tool wear prediction, thermal management in titanium alloy machining, and sustainable CNC operations. Administrative roles and grants are not detailed in the provided text, but his involvement in academic leadership and collaborative research projects is implied through his active publication record and institutional affiliation.

Ying ZhangView profile

Professor

• Artificial Intelligence
• Wireless Sensor Networks
• Internet of Things (IoT)
• +7 more

Dr. Ying Zhang is a Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology and serves as Senior Associate Chair. She directs the Sensors and Intelligent Systems Laboratory. Her research focuses on interdisciplinary systems engineering, including wireless sensor networks, IoT, biomedical engineering, structural health monitoring, and intelligent diagnostic systems. She holds a B.S. from Tongji University and advanced degrees from the University of Illinois at Chicago, University of Massachusetts Lowell, and Ph.D. in Systems Engineering from UC Berkeley. Education: B.S., Materials Science and Engineering, Tongji University M.S., Materials Engineering, University of Illinois at Chicago M.S., Electrical Engineering, University of Massachusetts Lowell Ph.D., Systems Engineering, University of California, Berkeley Research Interests: Her work spans AI-enabled systems, MEMS, smart materials, thermal management of bioimplants, and energy-efficient wireless sensor networks. Recent projects include adaptive thermal management for implantable devices and human-in-the-loop control for HVAC systems. Awards: NSF CAREER Award (2013) Lockheed Martin Dean's Excellence in Teaching Award (2012) Hesburgh Award Teaching Fellow (2017) TechConnect Innovation Awards (2017) Grants & Labs: Leads projects funded by NSF, including adaptive thermal management for bioimplants and supercapacitor-based power management. Directs the Sensors and Intelligent Systems Lab, which collaborates on structural health monitoring, biomedical sensors, and energy harvesting.

Amir KhajepourView profile

Professor

• Mechatronics
• Autonomous Vehicle Systems
• Vehicle Control and Safety
• +4 more

Amir Khajepour is a Professor at the University of Waterloo and holds prestigious positions as a Tier 1 Canada Research Chair in Mechatronics Vehicle Systems and a Senior NSERC/General Motors Industrial Research Chair in Holistic Vehicle Control. His research focuses on autonomous vehicle systems, mechatronics, and advanced control methodologies. Key areas include autonomous driving safety, sensor fusion, vehicle dynamics, and energy management. He leads the Mechatronic Vehicle Systems Lab, pioneering innovations in connected and automated vehicles. His work integrates machine learning, robotics, and mechanical engineering to address challenges in real-world autonomous systems, including path planning, perception reliability, and multi-agent coordination. Recent projects involve 5G-enabled mobility systems, robust tire force estimation, and game-theoretic decision-making frameworks. Khajepour’s contributions span both theoretical advancements and practical implementations, such as the WATonoBus autonomous shuttle technology. Research Highlights: Autonomous vehicle safety, sensor fusion algorithms, adaptive control systems, and energy-efficient powertrains. Grants & Awards: Canada Research Chair, NSERC/GM Industrial Chair, and multiple industry collaborations. Labs & Teams: Directs the Mechatronic Vehicle Systems Lab at the University of Waterloo. His publications emphasize real-world deployment, safety validation, and interdisciplinary approaches to advancing intelligent mobility solutions.

William MelekView profile

Professor

• Artificial Intelligence
• Intelligent Control
• Mechatronics
• +11 more

William Melek is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He serves as Director of the Laboratory of Computational Intelligence and Automation and RoboHub. His research focuses on intelligent systems, modular robotics, autonomous vehicles, and bioinformatics. He holds a B.A.Sc. in Electrical & Computer Engineering (Zagazig University, 1994), M.Sc. and Ph.D. in Mechanical Engineering (University of Toronto, 1998/2002), and a Post-Doctorate in Computer Science (Ryerson University, 2004). Education: Bachelor's: B.A.Sc in Electrical & Computer Engineering, Zagazig University (1994) Master's: Mechanical Engineering, University of Toronto (1998) Doctorate: Mechanical Engineering, University of Toronto (2002) Post-Doctorate: Computer Science, Ryerson University (2004) His research interests span artificial intelligence, intelligent control, mechatronics, automotive design, and computational intelligence. Recent work includes autonomous vehicle navigation, predictive maintenance in manufacturing, and bioinformatics-driven clinical decision support systems. He teaches courses such as ME 360 (Control Systems), ME 780 (Mechatronics), and MTE 100 (Intro to Mechatronics). Articles from 2023–2025 highlight advancements in autonomous driving decision-making, modular robotics, and 5G-enabled teleoperation systems. His lab develops algorithms for urban autonomous systems and industrial automation. He currently oversees graduate student applications in mechatronics and robotics. Labs/Teams: Laboratory of Computational Intelligence and Automation, RoboHub.

• Robotics
• Computer Vision
• Sensor Fusion
• +3 more

Adam Jacobson is a former Research Fellow at the Queensland University of Technology (QUT) Centre for Robotics, now working at Caterpillar as an Automation Engineering Specialist. He holds a PhD (QUT) and Bachelor of Engineering (Electrical) from QUT. Research Focus: Bio-inspired algorithms for robotic SLAM, sensor fusion, and underground mining automation. Key Projects: 'Infinitely Scalable Learning and Recognition Network' (funded by Asian Office of Aerospace Research and Development) and 'Automation Enabling Positioning for Underground Mining' (collaboration with Caterpillar and Mining3). His work emphasizes scalable visual place recognition, low-cost sensor integration, and overcoming challenges in dynamic environments like underground mines. Awards include an ARC Future Fellowship for 'Superhuman place recognition' research. Awards: ARC Future Fellowship, 201X (specific year unlisted). Collaborations: Harvard University, University of Notre Dame, Caterpillar, and Mining3. His research has advanced autonomous vehicle navigation, particularly in harsh environments, through innovations in multi-scale visual recognition and sensor calibration.

• IoT and Smart Systems
• Artificial Intelligence
• Renewable Energy
• +7 more

Dr. Sahar Ahmadzadeh is an Assistant Professor in Computer Science/Data Science at York St John University's London campus, affiliated with the York Business School. She holds a Ph.D. and has held roles including Wireless Sensor Development Engineer (KTP Associate at University of Bolton), Senior Research Associate (University of East Anglia), and Research Fellow (University of Bedfordshire). Her research focuses on IoT, smart grids, energy storage systems, machine learning, and biomedical sensors, with publications in IEEE journals and conferences. She is a Fellow of the Higher Education Academy and holds a CMI Level 5 certificate in Management and Leadership. Education: Ph.D. (2017) Chartered Management Institute (CMI) Level 5 Certificate in Management and Leadership (2021) Research Interests: IoT applications in smart cities and energy systems Machine learning for cybersecurity and healthcare Renewable energy storage optimization Energy-efficient wireless sensor networks Smart grid demand response management Publications: Recent work includes studies on AI-driven energy storage expansion, malicious URL detection via ML, pandemic impacts on telecommunication networks, and IoT-enabled food waste reduction strategies. Her research bridges technical innovation with socio-economic policy analysis. Awards: Fellow of the Higher Education Academy (UK) Leadership & Grants: Secured Innovate UK funding as a KTP Associate. Active in mentoring researchers and teaching innovation.

José Luis Roda GarcíaView profile

Associate Professor

• Computer Science
• Data Science
• Bioinformatics
• +3 more

José Luis Roda García serves as an Associate Professor in the Department of Computer Engineering and Systems at the University of La Laguna, Spain. His academic work centers on the Area of Computer Languages and Systems, with active involvement in the PhD Program in Industrial Engineering, Informatics, and Environmental. Institutional correspondence is managed through jlroda@ull.edu.es. Education: PhD in Computer Science from the University of La Laguna (1998) with thesis "Nuevos modelos de predicción en computación paralela" (New Prediction Models in Parallel Computing), supervised by Dr. Casiano Rodríguez León. His research program demonstrates exceptional interdisciplinary breadth while maintaining core focus in computational disciplines. Primary expertise includes Data Science applications for public safety (e.g., R-based analysis of Canarian emergency services data), Bioinformatics tool development (notably Dockerized platforms like NanoDJ for genome assembly), and Software Engineering for scalable data infrastructure. His work consistently bridges theoretical computer science with practical implementations in medical informatics, astronomy, and social sciences, reflecting a commitment to solving real-world problems through computational innovation. Analysis of his recent publications (2021-2025) reveals three dominant trajectories: 1) Emergency management systems using data science techniques, 2) Reproducible bioinformatics workflows via containerization, and 3) Cross-disciplinary collaborations in astronomy instrumentation and medical diagnostics. This pattern highlights his role as a computational enabler across diverse scientific domains rather than a domain-specific specialist. Scientific awards: No major awards, fellowships, or honors are documented in available sources. Advising and grants: No specific doctoral students or postdoctoral researchers are listed in public records. Project involvement suggests participation in EU-funded initiatives like ERASMUS environmental programs and Canarian public data projects, though explicit grant details remain unspecified.

Kokou Chéridhan LISSASSIView profile

Researcher

• Human-Robot Interaction
• Robotics
• Autonomous Mobile Robots (AMRs)
• +3 more

Kokou Chéridhan LISSASSI is a PhD researcher at Université Paris-Est Créteil Val-de-Marne (UPEC) affiliated with ICAM, focusing on the Societal and Technological Transitions of Companies research axis. His work emphasizes Human-Robot Interaction (HRI), Robotics, and Industry 4.0 applications. He is based at the Grand Paris Sud campus. Education : Bachelor's in Industrial Computing (EPSIEL, Morocco, 2017–2020) Master's in Electronic, Energy Electric, and Automatic Systems (Evry University, France, 2020–2022) Research Contributions : Developed autonomous navigation systems for omnidirectional robots using ROS2 and SLAM with LiDAR sensors. Created a Digital Shadow for UR5e robotic arms in Gazebo simulations, enabling real-time synchronization with physical robots. Optimized human-robot collaboration in industrial settings via multi-robot systems and gesture recognition for intuitive control. Teaching & Mentorship : Delivers lectures on ROS middleware and supports student projects in robotics. Mentored an internship resulting in a publication at FAIM 2023. Labs & Collaboration : Completed an internship at LISSI Laboratory (Université Paris Est Créteil), focusing on HRI with Turtlebot3 robots.

• Computer Science
• Information Security
• Wireless Sensor Networks
• +5 more

Dr. Jarrod Trevathan is a researcher at James Cook University, with a career spanning computer science, environmental monitoring, and information security. His work focuses on wireless sensor networks, virtual research environments, and online auction systems. He has collaborated extensively with colleagues like Trina Myers and Wayne Read. Research Highlights: Developed auction-based protocols for sensor network resource allocation Created middleware platforms for heterogeneous sensor integration Built Web2.0 disaster response systems (Riskr) Contributed to semantic enablement of virtual research environments Explored behavioral aspects of online auction fraud Teaching Innovations: Applied process-oriented guided inquiry learning to large IT courses Integrated active learning techniques for online ICT education

• Electrical and Electronic Engineering
• Communications Technologies
• Materials Engineering
• +7 more

Dr. Amir Ebrahimi is a Senior Research Fellow at the School of Engineering, RMIT University. His research focuses on microwave-based sensing technologies, metamaterials, and their applications in biomedical engineering, environmental monitoring, and communications. He holds an ORCID identifier (0000-0002-0858-4958) and is open to supervising Masters and PhD students in areas such as microwave sensors for concrete structures, IoT antennas, and microfluidic devices. Research interests include Electrical Engineering, Communications Technologies, Materials Engineering, Optical Physics, and Analytical Chemistry . His work bridges theoretical design and practical implementation, addressing challenges in sensor sensitivity, material characterization, and reconfigurable RF systems. Recent projects include developing wearable sweat sensors, detecting honey adulteration via microwave techniques, and designing graphene-based terahertz absorbers. Though no scientific awards are explicitly mentioned, his contributions span over 100 peer-reviewed articles and innovative sensor prototypes. Dr. Ebrahimi supervises research projects on flexible electronics, microwave-enabled microfluidics, and metamaterial antennas. He collaborates on lab-on-a-chip technologies for cancer cell detection and nano-scale vacuum circuits for satellite communications.

Jerome MertzView profile

Professor

• Biomedical Optics
• Microscopy Development
• Volumetric Imaging
• +5 more

Jerome Mertz is a Professor in the Department of Biomedical Engineering at Boston University, where he leads the Biomicroscopy Lab developing novel optical techniques for biological imaging. His research focuses on advancing microscopy capabilities for deep tissue and high-speed applications. Research innovations include: Advanced volumetric imaging techniques for capturing dynamic biological processes Adaptive optical systems for aberration correction in complex media Novel approaches for imaging through scattering tissues including oblique back-illumination microscopy High-speed imaging technologies enabling kilohertz-rate voltage imaging in vivo Dr. Mertz has received significant recognition including the Aimeé-Cotton Prize (2002) and Fabry-de-Gramont Prize (2001). His recent publications (2024-2025) demonstrate strong focus on developing scattering microscopy techniques, voltage imaging in thick tissues, and super-resolution methods. Earlier work established foundations in adaptive optics and interferometric approaches. Current projects involve three-photon subcortical imaging, optical scan multiplier development, and HiLo microscopy enhancements. The Biomicroscopy Lab maintains active collaborations with neuroscience groups for in vivo applications.