Find and connect with academic supervisors, professors, and scholars for your research journey.
Showing 721-735 of 2,453 supervisors
Profile data may be stale. It is sourced from public faculty pages.
Research Professor
Ioana Popescu is a prominent hydroinformatics researcher affiliated with the IHE Delft Institute for Water Education , where she has worked since 2001. Previously, she served as an Associate Professor at the Faculty of Hydrotechnics, Timisoara, Romania (1990-1999), and a postdoc researcher at the National Research Council of Canada (2000).
Lecturer
Paulius Rauba is a Visiting Lecturer at ISM University of Management and Economics and a PhD candidate in Machine Learning at the University of Cambridge. He holds a BSc from ISM and an MSc from the University of Oxford, where he is also an Oxford Shirley Scholar. His research focuses on fundamental machine learning, model evaluation, robustness, and quantitative social science. He teaches courses in Econometrics, Data Science, and Elements of Artificial Intelligence. Paulius leads Gauss, a company specializing in deploying machine learning models, and has advised the European Commission on AI systems. His work spans academia, industry, and international organizations, emphasizing data-driven solutions for business and social challenges. Education: BSc, ISM University of Management and Economics MSc, University of Oxford His research explores model robustness, AI applications in healthcare, and conflict analysis through statistical and neural methods. Recent articles address topics like self-healing ML frameworks and context-aware model testing. Paulius is committed to advancing AI ethics and practical deployment. Awards: Oxford Shirley Scholar As a leader in Gauss, he bridges academic innovation with industry needs, focusing on scalable AI solutions. His advisory roles and grants underscore his interdisciplinary impact.
Research Professor
John K. Tsotsos is a Distinguished Research Professor at York University's Lassonde School of Engineering, holding positions in both the Department of Electrical Engineering & Computer Science and the Centre for Vision Research (CVR). His work bridges computer science, cognitive science, and neuroscience with a focus on visual attention and active vision systems. Dr. Tsotsos's research interests center on visual attention mechanisms, active visual search, and visuospatial reasoning. His work explores how humans and machines process visual information, with applications in autonomous driving, robotics, and human-computer interaction. He investigates the computational principles underlying visual attention, comparing biological systems with artificial implementations. His research has significant implications for developing more human-like computer vision systems that can effectively navigate and interpret complex visual environments. Analysis of his recent publications reveals a strong focus on active vision systems where observers dynamically control their viewpoints during visual search tasks. His work spans both theoretical foundations of visual attention and practical applications in autonomous vehicles. A significant portion of his recent research addresses driver attention modeling, gaze prediction, and the challenges of real-world visual processing where traditional computer vision approaches often fail. His work consistently bridges cognitive theory with practical engineering applications. Dr. Tsotsos has made substantial contributions to the field of computational vision through his theoretical work on attentional mechanisms and their implementation in artificial systems. His research has influenced both academic understanding of visual processing and practical applications in autonomous systems and human-machine interfaces. As a faculty member at York University, Dr. Tsotsos contributes to the vibrant research ecosystem of the Centre for Vision Research, where interdisciplinary teams work on cutting-edge problems in visual perception, cognitive modeling, and machine vision. His work exemplifies the integration of cognitive science principles with advanced computational techniques to solve complex visual processing challenges.
Associate Professor
Mark A. Minor is an Associate Professor in the Department of Mechanical Engineering at the University of Utah's College of Engineering, where he serves as Director of the Robotics Systems Lab and Coordinator of the Robotics Track within Mechanical Engineering. His research spans multiple domains of robotics including climbing robots, terrain adaptable mobile robots, virtual interfaces, autonomous vehicles, and flying robots. The Robotics Systems Lab under his direction synergizes design, modeling, and control to create novel robotic embodiments with enhanced adaptability, mobility, and immersion. Dr. Minor's research focuses on the synergistic integration of design, modeling, and control of robotic systems. His lab specializes in several types of robotic systems including climbing robots, terrain adaptable mobile robots, virtual interfaces, autonomous vehicles, and flying robots. With extensive expertise in the design and control of under-actuated nonholonomic systems, kinematic motion control, dynamic motion control, state estimation, sensor development, and data fusion, his work pushes the boundaries of what robotic systems can achieve in challenging environments. His research portfolio demonstrates a consistent focus on practical robotic applications across multiple domains. Recent work shows increasing emphasis on immersive virtual environments with wind, olfactory, and thermal displays, as well as sophisticated control systems for autonomous vehicles and terrain-adaptive locomotion. The integration of haptic feedback, multi-sensory stimulation, and soft robotics components represents an emerging trend in his research trajectory, bridging the gap between physical robotics and human perception. Dr. Minor has successfully advised numerous graduate students through completion of their degrees, with alumni now working at institutions including Harbin Institute of Technology, University of Utah, Orbital Sciences Corporation, and Western Digital Corporation. His research has been supported by prestigious sponsors including the National Science Foundation, NASA, Army Night Vision Lab, and industry partners such as ATK Launch System and Kairos Autonomi. The Robotics Systems Lab, directed by Dr. Minor, maintains several active research projects including Hybrid Mobility Research (investigating robots capable of rolling, walking, and climbing), Autonomous Vehicle Research (particularly related to the DARPA Urban Challenge), Traction Sensing and Control in Wheeled Mobile Robots, Immersive Virtual Environments (including the TreadPort Active Wind Tunnel), and Compliant Framed Modular Mobile Robots. The lab continues to push the boundaries of robotic mobility, control, and human-robot interaction.
Professor
Joni Kämäräinen is a Professor of Signal Processing at Tampere University’s Computing Sciences department under the Faculty of Information Technology and Communication Sciences. He leads the Vision Group and has a tenure-track career at Tampere University since 2012, achieving full professorship in 2020. Prior, he conducted postdoctoral research at the University of Surrey’s Center of Vision, Speech and Signal Processing and held a faculty position at LUT University. His research spans robot vision and robot learning , focusing on computer vision and machine learning applications. Key applied projects address industrial collaboration with Huawei, Nokia Technologies, and others, emphasizing robust visual perception, autonomous systems, and depth sensor integration. Notable work includes long-term visual place recognition, RGB-D tracking, and color constancy solutions. Recent publications (2023–2025) reflect expertise in digital twins for industrial manipulators, probabilistic subgoal modeling, depth-aware video deblurring, and LiDAR-place recognition datasets. His team’s outputs bridge robotics, AI, and signal processing, with interdisciplinary impacts in healthcare and autonomous navigation. Teaching responsibilities include graduate and doctoral colloquia, and the textbook Koneoppimisen perusteet (2023) . Funding sources include the Academy of Finland, EU Horizon 2020, Business Finland, Huawei, and Nokia Technologies.
Professor
Liz Moores is a Professor and Deputy Dean at the College of Health and Life Sciences, Aston University, where she leads the School of Psychology. She holds a PhD in Psychology from the University of Sheffield (1999) and has held academic roles since 2002, progressing from Lecturer to Professor. Her research focuses on higher education policy, student experience, and dyslexia-related visual attention modulation. She has received the One Aston Award (2023) for her contributions. Education: PhD in Psychology, University of Sheffield, 1999 European Postgraduate Diploma in Cognitive Science, International School for Advanced Studies, Trieste, 1998 B.A. (Hons) in Psychology, University of Sheffield, 1995 Research Interests: Dr. Moores investigates determinants of student success, equity in education, and interventions to enhance the student experience. Her work on dyslexia explores visual attention modulation in adults, including cueing, crowding, and distractor effects. She advocates for evidence-based policies to widen access to higher education and improve institutional practices. Grants & Advising: Her recent articles emphasize robust evaluation of access plans and the role of learning analytics in education. She has supervised one student and contributed to media discussions on healthcare simulation facilities and student engagement.
Assistant Professor
Lonni Besançon is an Assistant Professor of Visualization at Linköping University, Sweden, serving as a 2023 ASAPBio Fellow, Scientific Node Coordinator for the Swedish National Visualization Infrastructure InfraVis, and co-editor-in-chief of the Journal of Visualization and Interaction (JoVI). Education includes: PhD in HCI from Université Paris Saclay (2014-2017) Master of Research in HCI from Université Paris Sud (2013-2014) Exchange studies at University of Hong Kong (2013-2014) Master of Engineering from Polytech Paris Sud (2011-2014) Classe Préparatoire at Polytech Paris Sud (2009-2011) Research focuses on developing novel interaction techniques for volumetric data visualization and enhancing statistical interpretation through innovative visualizations. His work emphasizes methodological improvements in research practices, including detecting questionable research practices and enhancing transparency, robustness, and reusability of scientific outputs. Additional interests include augmented reality interfaces, collaborative visualization systems, and open science advocacy. Publications demonstrate consistent focus on augmented reality interfaces, collaborative visualization, research transparency, and statistical interpretation methods. Recent works showcase increasing emphasis on open science practices and methodological critiques, with notable contributions to understanding peer review systems and pandemic-related research evaluation. Awards and honors: ASAPBio Fellow (2023) GRD IG-RV Honorable Mention (2018) Advising and supervision includes mentorship of graduate students Xiyao Wang, Marie Cheng, and Mickael Francisco Sereno. Teaching experience encompasses courses in Interactive Information Visualization, Algorithms, Graph Theory, and Computer Security at Université Paris Saclay and Polytech Paris Sud. Leads research initiatives at Linköping Visualization Center and collaborates internationally through InfraVis. Serves on program committees for ACM IHM and IEEE EuroVis, while contributing to numerous conferences including CHI, IEEE VIS, and ISMAR.
Academic
Won-Jae Yi is an Associate Teaching Professor of Electrical and Computer Engineering at the Illinois Institute of Technology (Illinois Tech), part of the Armour College of Engineering. He holds a B.S., M.S., and Ph.D. in Computer Engineering from Illinois Tech, completed in 2010, 2012, and 2017, respectively. In addition to his teaching role, Yi serves as the Undergraduate Laboratory and Computing Facilities Supervisor in the Department of Electrical and Computer Engineering. He has over 13 years of experience in research focusing on IoT, wireless sensor networks, wearable devices for health monitoring, FPGAs, cyber-physical systems, and edge computing. Education: B.S. in Computer Engineering (cum laude, 2010), Illinois Tech M.S. in Computer Engineering (2012), Illinois Tech Ph.D. in Computer Engineering (2017), Illinois Tech Research Interests: Yi’s work spans IoT-enabled systems, AI-driven smart devices, cybersecurity for embedded systems, and assistive technologies for visually impaired individuals. His research emphasizes practical applications such as smart home automation, wearable health monitoring, and real-time data fusion for IoT systems. He consistently integrates his expertise in hardware-software co-design, including FPGAs and SoCs, to create robust, low-power solutions. Teaching Contributions: Yi teaches undergraduate and graduate courses in Software Engineering, Internet of Things, Cybersecurity, and Artificial Intelligence. His teaching excellence was recognized with the 2023 Bauer Family Excellence in Undergraduate Teaching Award. Labs and Facilities: As Laboratory Supervisor, Yi manages computing facilities and oversees the development of experimental setups for student projects in IoT, embedded systems, and AI. His lab focuses on prototyping smart systems that bridge theoretical concepts with real-world applications.
Professor
Henk Zijm is a full Professor in the Department of Industrial Engineering & Business Information Systems at the Faculty of Engineering Technology, University of Twente, and is affiliated with the Digital Society Institute. His research spans operations management, logistics, supply chain systems, and stochastic modeling, with a strong focus on practical industrial applications. His research interests include Supply Chain Management , Logistics , Inventory and Spare Parts Control , Multi-Agent Systems , and Digital Transformation in Manufacturing . He has made significant contributions to modeling complex systems under uncertainty, particularly in manufacturing and distribution networks. The 15 most recent articles reflect a consistent focus on supply chain resilience, digital coordination, and sustainable logistics. Key trends include the integration of additive manufacturing in spare parts supply, interactive tools for circular supply chains, and advanced modeling of traffic and production systems. His work bridges theoretical operations research with real-world industrial challenges. Henk Zijm has supervised 24 academic works, indicating active mentorship and PhD guidance. While no specific grants are listed, his extensive publication record and leadership in research areas suggest successful grant acquisition and project leadership. His work has strong interdisciplinary reach, particularly in digital society and systems engineering. He is associated with the Digital Society Institute at the University of Twente, which fosters interdisciplinary research on the societal impact of digital technologies. This affiliation underscores his engagement with broader technological and societal transformations.
Research Fellow
Dr Abdullah Nazib is a Research Fellow at Queensland University of Technology (QUT) in the Faculty of Engineering, School of Electrical Engineering & Robotics. His research focuses on applying advanced computational techniques to medical imaging challenges, particularly in cancer detection and treatment planning. His research interests include: Medical image registration and segmentation Deep learning architectures for healthcare applications 3D medical image analysis Prostate cancer detection and grading Organ segmentation for radiation therapy Radiomics-based diagnostic systems Analysis of Dr Nazib's publication history reveals a clear evolution from general computer vision research toward specialized medical applications. His recent work demonstrates significant contributions to uncertainty quantification in medical image segmentation and multimodal learning approaches for diagnostic imaging. The 2024 publications particularly highlight his focus on clinically relevant applications with immediate potential impact on cancer diagnosis and treatment planning. His collaborative research network includes strong partnerships with Dr Fookes, Dr Perrin, and other members of QUT's biomedical imaging group, reflecting an interdisciplinary approach that bridges computer science, engineering, and clinical medicine to develop practical AI solutions for healthcare challenges.
Professor
Prof. Dr. Jörg Henseler is Full Professor and Chair of Product–Market Relations at the Department of Design, Production and Management, Faculty of Engineering Technology, University of Twente, Netherlands. He also holds visiting positions at NOVA Information Management School, Universidade Nova de Lisboa, Portugal, and as Distinguished Invited Professor at the University of Seville, Spain. University: University of Twente School: Faculty of Engineering Technology Department: Department of Design, Production and Management Chair: Product–Market Relations Visiting Professor: NOVA Information Management School, Portugal Distinguished Invited Professor: University of Seville, Spain His research focuses on composite-based structural equation modeling (SEM) , particularly partial least squares (PLS) path modeling , emergent variables , and methodological innovations in empirical research. He bridges design and behavioral sciences through advanced statistical modeling, with applications in marketing, management, and information systems. His recent publications emphasize methodological rigor in PLS-SEM, including consistent PLS (PLSc) , confirmatory composite analysis (CCA) , HTMT for discriminant validity , and second-order modeling . These works highlight trends toward improved model assessment, validity testing, and theoretical integration in composite-based approaches. Highly Cited Researcher by Clarivate/Web of Science Ranked among the top 100 most influential researchers in the Stanford/Elsevier Top 2% Scientists List 2024 Repeated 'Teacher of the Year' award recipient Prof. Henseler contributes extensively to the scientific community as a reviewer, editorial board member, and guest editor. He chairs the scientific advisory board for the ADANCO software and organizes the PLS School , offering seminars on PLS path modeling. He has authored over 130 journal articles and the authoritative book Composite-Based Structural Equation Modeling . His work supports researchers in applying robust, theory-driven methods in empirical studies. He leads methodological innovation in composite-based modeling, with strong ties to software development and global academic outreach. His research group and collaborations focus on advancing SEM techniques for complex, real-world applications in business and engineering contexts.
Senior Lecturer
Dr Jiacheng Tan is a Senior Lecturer in the School of Computing at the University of Portsmouth , where he has been a faculty member since 2002. He is actively involved in research and PhD supervision, with a strong focus on intelligent systems and robotics. Dr Tan earned his BEng in Mechanical Engineering from Jilin University of Technology (1983), an MSc in Mechatronics from Xidian University (1989), and a PhD in Computer Graphics from De Montfort University (2001). Prior to joining Portsmouth, he served as a Visiting Researcher in robotics at the University of Salford (1996–1997) and a Research Fellow in artificial intelligence at the Open University (2000–2002). His research centers on computer vision, intelligent robot control, 3D graphics, and human-robot interaction . He investigates how robots can understand and act upon natural language commands by grounding spatial relations, recognizing objects, and reasoning about tasks in unstructured environments. His work integrates fuzzy logic, knowledge engineering, and machine learning to enable robots to learn from demonstrations and interact meaningfully with humans. The trends in his publications reveal a consistent focus on robotics and intelligent systems , evolving from early work in virtual environments and telerobotics to recent contributions in cloud-based scientific visualization and machine learning applications in astrophysics. His interdisciplinary research spans computer science, control theory, and cognitive systems. Dr Tan has not received any explicitly mentioned scientific awards in the provided text. He serves as a PhD supervisor and has contributed to multiple research projects, including the development of integrated AI frameworks for robotic manipulation. While specific grant details are not listed, his collaborations and publications suggest active involvement in funded research initiatives. He has worked with researchers across institutions on topics ranging from scientific visualization to intelligent interfaces. Dr Tan is affiliated with the Computational Intelligence Research Group at the University of Portsmouth. His lab work involves developing virtual environments, symbolic representations of 3D scenes, and natural language interfaces for robot control, supporting both academic research and practical applications in automation.
Pedro Arroz Correia Bonifácio Serra is a researcher in the Department of Electrical and Computer Engineering at Universidade Lusófona, specializing in Guidance, Navigation, and Control (GNC) systems for aerospace and robotic applications. His work is closely aligned with European Space Agency (ESA) missions such as e.Deorbit, COMRADE, GUIBEAR, and HERACLES, focusing on active debris removal, on-orbit servicing, and autonomous spacecraft operations. Research Interests: His primary research areas include Guidance, Navigation and Control (GNC), space robotics, autonomous systems, image-based visual servo control, fault-tolerant control, and nonlinear control systems. He has made significant contributions to the development and validation of control architectures for capturing tumbling satellites and enabling autonomous landing of UAVs and spacecraft. The most recent publications reflect a strong emphasis on space safety, debris removal technologies, and computational GNC for complex space missions. His work bridges theoretical control design with practical ground validation, particularly in the context of ESA-led projects. The recurring themes across his publications include autonomous rendezvous, manipulator control for space robots, and robust GNC under uncertain conditions. Scientific Contributions: Key contributor to ESA's e.Deorbit mission studies, focusing on capture and deorbiting of defunct satellites like Envisat. Developed and tested GNC systems for the HERACLES lunar ascent element. Involved in the COMRADE project for combined control of robotic spacecraft and manipulators. Worked on GUIBEAR project for bearings-only rendezvous navigation. Advising and Grants: While no formal students are listed, his research is supported by major European space initiatives, likely involving collaborative grants from ESA and industrial partners such as Airbus. His work involves experimental validation and prototype development, indicating access to advanced research funding and facilities. Labs and Teams: Although specific lab affiliations are not mentioned, his involvement in projects like WMS LEMUR and e.Deorbit suggests collaboration with ESA’s GNC teams and space robotics laboratories focused on on-orbit servicing and debris removal technologies.
Professor
Prof. Andrzej Dudek is a faculty member at the Department of Econometrics and Informatics, Wrocław University of Economics – Jelenia Góra Branch. His research focuses on advanced data analysis methodologies, including symbolic data analysis, machine learning applications, and statistical modeling. Dudek has contributed to the development of R packages such as IFMCDM and mdsOpt, which support multi-criteria decision making and multidimensional scaling. His work addresses challenges in outlier detection, clustering, and predictive modeling across domains like tourism, healthcare, and finance. Recent studies explore consumer behavior shifts during the pandemic, AI-driven medical modeling, and robust regression techniques for noisy data. Key research areas include econometric modeling, computational statistics, and the integration of machine learning with traditional statistical methods. Dudek’s interdisciplinary approach spans from theoretical algorithm development to practical applications in industry and public health. He actively contributes to academic conferences and publishes in leading journals, demonstrating expertise in both methodological innovation and real-world problem-solving.
Professor
Mohamed Shehata is a Professor in the Department of Computer Science, Mathematics, Physics, and Statistics at the University of British Columbia's Irving K. Barber Faculty of Science. He holds an adjunct professorship at Memorial University of Newfoundland's Computer Engineering Department. His research focuses on computer vision, biomedical applications, and intelligent camera systems. He earned his B.Sc. (Zagazig University), M.Sc. (Zagazig University), Ph.D. (University of Calgary), and P.Eng. licensure. Previously, he worked at Intelliview Technologies Inc. as Vice President of Engineering and Research. He has held roles as an assistant and associate professor at Memorial University before joining UBC in 2019. He serves as Editor-in-Chief of the IEEE Canadian Journal of Electrical and Computer Engineering and has contributed to over 70 peer-reviewed publications. His work spans video surveillance systems, domain generalization, and medical imaging applications. Education: B.Sc. (Honors), Zagazig University M.Sc., Computer Engineering, Zagazig University Ph.D., University of Calgary Research Interests: He explores cutting-edge topics like federated learning for domain adaptation, biomedical image analysis, and lightweight neural networks for embedded systems. His recent work emphasizes cross-domain generalization and few-shot learning for medical diagnostics and object tracking. Professional Contributions: Dr. Shehata has supervised graduate students and led projects in computer vision applications. His publications bridge theoretical advancements with practical systems like drone-based surveillance and IoT healthcare devices. He actively contributes to IEEE committees and academic journal editing.
Showing search results up to the first 750 matches. Narrow your search with filters to find more specific results.
