Find Academic Supervisors

• Computer Science
• Medical Technology
• Artificial Intelligence
• +3 more

Dr. Hamit Soyel is a Research Fellow at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Dragonfly initiative. His work spans educational technology, healthcare innovation, and computer vision. His research focuses on enhancing learning through video-based methods, improving rheumatoid arthritis care via technology, and advancing facial recognition systems using geometric and algorithmic approaches. Key research themes include cognitive load optimization in educational videos, patient-clinician communication barriers in RA care, and robust image processing techniques for medical and facial analysis. His interdisciplinary approach bridges computer science with healthcare and education, aiming to develop practical technological solutions. Publications highlight trends in medical technology adoption, video instruction design, and facial expression recognition. He has contributed to patents in image enhancement and algorithms for 3D facial geometry analysis. His work reflects a commitment to both theoretical innovation and real-world applications. No scientific awards are explicitly listed, though his extensive publication record indicates recognition in his fields. He has advised no documented students but collaborates on projects involving healthcare technology and educational systems. His involvement in the Dragonfly project suggests affiliation with cross-disciplinary teams focused on interactive companions and affect-sensitive technologies. Research labs or groups are not explicitly mentioned, but his work aligns with Queen Mary's broader initiatives in AI and healthcare tech.

Evan F. RiskoView profile

Professor

• Distributed Cognition
• Effort Perception
• Education and Training
• +3 more

Evan F. Risko is a Professor and Associate Chair (Graduate Affairs) at the University of Waterloo. His research focuses on Distributed Cognition, Effort Perception, and applying cognitive psychology principles to improve education and training. He holds the Canada Research Chair in Embodied and Embedded Cognition and has received multiple awards including Early Career Awards from the Psychonomic Society, Canadian Society for Brain, and Outstanding Performance Awards from the Province of Ontario. His work is funded by NSERC, SSHRC, and other major grants. He leads the Cognition and Natural Behaviour Laboratory, exploring how humans integrate body and environment to enhance thinking. Recent studies examine lecture design, cognitive offloading effects, and metacognition in digital contexts. Education: B.A., M.A., Ph.D. from the University of Waterloo in Cognitive Psychology. His research bridges theoretical and applied domains, with a focus on optimizing learning through lecture video design, understanding effort perception, and mitigating cognitive biases. Scientific Awards: Canada Research Chair in Embodied and Embedded Cognition Early Career Award (Psychonomic Society) Early Career Award (Canadian Society for Brain, Behaviour, and Cognitive Science) 2014 & 2018 Outstanding Performance Awards (Province of Ontario) Advising & Grants: Supervises graduate students in cognitive science and education research. Major grants include NSERC Discovery Grants, SSHRC Insight Development Grants, and Canada Foundation for Innovation funds. His work on video lectures and cognitive offloading has implications for educational technology and workplace training. Labs & Teams: Director of the Cognition and Natural Behaviour Lab, collaborating on projects like 'Distributed Metacognition' and 'Effort Perception in Technology Use'. Current initiatives explore how external tools (e.g., smartphones) shape cognitive processes and learning efficacy.

Deborah BrewisView profile

Senior Lecturer

• Critical Diversity Studies
• Creative Methodologies in Management Research
• Digital Labour
• +6 more

Deborah Brewis is a Senior Lecturer (Associate Professor) in the Management Strategy & Organisation department at the University of Bath's School of Management. She holds additional roles as Senior Tutor and Provocations Essays Editor for Management Learning . Her research focuses on critical diversity studies, creative methodologies in management, and digital labor. Brewis co-founded the Building the Antiracist Classroom collective and is part of the Decolonising Alliance and VIDA. She has collaborated with institutions like University of Kent and Queen Mary University London on antiracist initiatives. Education: PhD in Business and Management from the University of Warwick (2011-2016). Current supervision includes three PhD students across internal and external programs. Research Interests: Critical analysis of inclusion/diversity practices, gender/race dynamics, intersectionality, digital identity, emotional labor, and solidarity communities. Recent work explores anti-racism strategies, postfeminist labor discourses, and embodied writing methodologies. Publications highlight themes like anti-racist pedagogy, neoliberal subjectivity, and digital exclusion. Awards include Fellowship of the Higher Education Academy. Active in editorial roles and methodological innovation, she curates dialogues on organizational learning through the Management Learning Meets... video series. Labs/Initiatives: Core member of the Centre for Future of Work, Centre for Qualitative Research, and collaborator in global anti-racism networks. Current projects involve decolonizing academic practices and developing creative research tools.

Thi Kim Anh DangView profile

Senior Lecturer

• Teacher education
• TESOL
• Education policy
• +4 more

Dr Thi Kim Anh Dang is a Senior Lecturer (TESOL and Languages Education) at Monash University's Faculty of Education. Previously, she held roles at Melbourne Graduate School of Education and La Trobe University. Her research focuses on teacher education, sociocultural theory, Indigenous education, and English-medium instruction (EMI) globalization impacts. She has published widely in international journals and authored 'Education Policy: Mapping the Landscape and Scope' (2016). Education: PhD in Teacher Education (University of Melbourne, 2014) with a sociocultural activity theoretical study of paired-placements; M.Ed (2002) on genre-based ESL writing pedagogy; B.Ed (Honours) in English Language Teaching (Vietnam National University, 1996). Research Interests: Teacher education, professional learning, TESOL, education policy, sociocultural activity theory, Indigenous education. She has consulted on projects addressing Indigenous student engagement in business education and EMI implementation strategies. Awards: Early Career Researcher Commendation (AARE 2015), Vietnam's Excellent Research Supervision Award (2007), and multiple scholarships/fellowships for academic excellence. Collaborations: Key projects include EMI professional learning programs in China and Germany, and Indigenous education initiatives in Australia. She leads the AARE Teacher Education & Research Innovation SIG.

• Biometric Recognition
• Presentation Attack Detection
• Deepfake Forensics
• +5 more

Giulia Orrù is an Assistant Professor of Computer Engineering at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering. She holds an M.S. and Ph.D. in Electronic Engineering and Computer Science from the same institution. Her research focuses on biometric recognition, presentation attack detection, deepfake forensics, and cybersecurity. She is a core member of the Pattern Recognition and Applications Laboratory (PRA lab), contributing to projects like BullyBuster (anti-bullying detection systems) and LivDet competitions (fingerprint liveness detection). Dr. Orrù has authored numerous publications in top-tier conferences and journals, with a strong emphasis on advancing secure authentication systems and combating adversarial attacks in biometrics. She actively serves as a referee for pattern recognition and cybersecurity venues. Teaching activities include courses such as Technologies for Information Security and Artificial Intelligence and Security . Research interests span multimodal biometrics, 3D face reconstruction for surveillance, AI-driven anti-bullying systems, and deepfake detection algorithms. Her work bridges theoretical advancements (e.g., diffusion models for anomaly detection) with real-world applications like forensic recognition and crowd analysis. Notable projects include the Synthetic Data for Face Recognition (SdFR) initiative and contributions to the Face Deepfake Detection Challenge. Dr. Orrù's lab explores cutting-edge techniques in EEG-based personal recognition and vulnerability analysis of medical AI systems. She maintains active participation in international research networks and has developed open-source tools for evaluating biometric system resilience against spoofing attacks.

• Medical Image Segmentation
• Motion Segmentation
• Visual Object Tracking
• +9 more

Dr. Sandeep Singh Sengar is a Senior Lecturer in Computer Science at Cardiff Metropolitan University, United Kingdom. Prior to his current role, he served as a Postdoctoral Research Fellow at the Machine Learning Section of the Computer Science Department at the University of Copenhagen, Denmark. His academic journey includes a Ph.D. in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India, and an M. Tech. in Information Security from Motilal Nehru National Institute of Technology, Allahabad, India. Sengar actively engages in research collaboration and has organized special sessions and delivered keynote presentations at international conferences. Education: Dr. Sengar holds the following academic qualifications: Ph.D. in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India M. Tech. in Information Security from Motilal Nehru National Institute of Technology, Allahabad, India Research Interests: Dr. Sengar's research focuses on advanced applications of machine/deep learning and computer vision, particularly in healthcare diagnostics and cybersecurity. His work combines theoretical methodologies with practical implementations, including: Medical Image Segmentation (e.g., brain tumors, functional connectivity) Motion Segmentation and Tracking for surveillance and activity recognition Visual Object Tracking and Recognition in dynamic environments Video Compression techniques leveraging adaptive optimization Cybersecurity frameworks targeting DDoS attack mitigation Exploring Metaverse applications in healthcare and AI ethics Publications Trends: His recent articles emphasize interdisciplinary innovation, with a strong focus on healthcare AI and cybersecurity. Key themes include hybrid neural networks for medical imaging, entropy-driven frameworks for neurological disorders, and proactive network threat detection using deep learning. He also investigates emerging technologies like the Metaverse's role in healthcare systems and generative AI's broader applications. Scientific Awards: No scientific awards were explicitly mentioned in the provided texts. Advising & Grants: While Dr. Sengar has not listed formal advisees or grant details, his research mentorship is evident through collaborative projects and conference contributions. He actively participates in organizing special sessions and peer-review processes, fostering academic-industry partnerships. Labs & Teams: Though no specific labs are named, his work aligns with Cardiff Met's research centers and innovation initiatives, such as the PDR International Centre for Design and Research and ZERO2FIVE Food Industry Centre.

• Machine Learning
• Deep Learning
• Internet of Things (IoT)
• +5 more

Shahid Awan is a Lecturer at the School of Computing, Engineering and Physical Sciences. He holds a Ph.D. in Computer Science, specializing in Machine Learning, with a focus on applying intelligent systems to United Nations Sustainable Development Goals (UNSDGs), particularly in circular economy, IoT-enabled smart agriculture, and health informatics. His work emphasizes innovation, as seen in projects like 'Cricket Video Scene Categorisation' (Rector’s Award for Innovation, 2018) and predictive models for electric demand and dengue fever spread. Education: Ph.D. in Computer Science. Professional Development: Completed the 'Innovation Strategy Course' by KTN UK and 'Leadership and Management Training Modules' from Ashorne Hill Management College, UK. Research Interests: Machine Learning applications, Deep Learning, IoT, and Data Science in healthcare, sustainability, and smart systems. His publications highlight contributions to blockchain security, medical imaging analysis, and education technology. Notable Projects: Led projects on electric demand forecasting (collaborating with National Grid) and dengue fever prediction (health department). Founded the circular economy startup Circulayo, focusing on innovation strategy. Scientific Awards: Rector’s Award for Innovation (2018). Advising and Grants: Accepting PhD students and secured funding for startups like 'Electrical Demand Forecasting' through Silicon Valley pitches. Collaborates with industry partners like Crickingif and the National Grid. Labs/Teams: Active in interdisciplinary teams addressing SDGs through tech solutions, though no specific lab names are provided.

Bruno SinopoliView profile

Professor

• Cyber-Physical Systems (CPS)
• Networked Control Systems
• Smart Infrastructures
• +7 more

Bruno Sinopoli is a Professor in the Electrical and Computer Engineering Department at Carnegie Mellon University, with courtesy appointments in the Robotics Institute and Mechanical Engineering Department. He holds affiliations with ICES, CyLab, and the Pittsburgh Digital Studio (PDL), and co-directs the Smart Infrastructure Institute (SII). His research focuses on cyber-physical systems, networked control systems, and resilient infrastructure, addressing challenges in smart grids, wireless sensor networks, and cybersecurity. Education: Ph.D. (2005), M.S. (2003), and Laurea (1998) in Electrical Engineering from UC Berkeley, Università di Padova, and University of California, Berkeley, respectively. Notable awards include the George Tallman Ladd Research Award (2010), NSF Career Award (2010), and Eliahu Jury Award (2006). Research Interests include networked embedded control systems, cybersecurity for critical infrastructure, and smart city technologies. He has led projects funded by NSF, NIST, and industry, such as a $3.2M NIST grant for first responder communication systems and NSF CRISP grants for infrastructure resilience. Key contributions include frameworks for secure control systems, resilient sensor networks, and adaptive video streaming algorithms. His work bridges theoretical control systems with practical applications in energy, transportation, and urban infrastructure. Students supervised include doctoral candidates like Dragana Bajovic (A.G. Milnes Award winner) and Yilin Mo, as well as master’s students in localization and control systems. Active collaborations span robotics, mechanical engineering, and interdisciplinary initiatives in smart infrastructure.

• Coastal Hazards
• Coastal Processes
• Geographic Information Systems (GIS)
• +5 more

Associate Professor Hannah Power is a coastal morphologist and geologist at the University of Newcastle , affiliated with the School of Environmental and Life Sciences and the Earth Sciences department. She specializes in coastal processes, sediment transport, and climate change impacts on coastal environments, with a focus on hazards like tsunamis and storm surges. Her work bridges field studies, remote sensing, and numerical modeling, and she actively collaborates with government agencies for coastal management. PhD in Coastal Geomorphology, University of Queensland BSc (Marine Science) Honours, University of Sydney Research Interests : Coastal hazard assessment (tsunamis, storms, sea level rise) Swash zone and surf zone hydrodynamics Coral reef wave interactions and sediment transport Continental shelf wave dynamics and climate drivers Coastal management policy and science communication Recent article trends show a focus on continental shelf waves , tsunami modeling , and intermittent estuaries under climate change. Her publications emphasize hydrodynamic modeling , field measurements , and remote sensing across diverse environments. Scientific Awards : 2021 Science Technology Australia Superstars of STEM 2020 Newcastle Herald Hunter Hero Award Finalist 2015 APEC ASPIRE Finalist 2021 Australian Institute of Policy and Science Young Tall Poppy Award Hannah's teaching integrates science fundamentals, critical thinking, and evidence-based solutions. She contributes to undergraduate and postgraduate courses, emphasizing coastal dynamics and climate adaptation. Her NSW Coastal Council role (2020) informs policy on collaborative coastal management. Labs & Teams : Collaborates with the Environmental and Climate Change Research Group (ECCRG), Australian Forum for Operational Oceanography, and multidisciplinary teams for field experiments and modeling.

• Digital Health Innovation
• eHealth and Telemedicine
• Social Media in Healthcare
• +3 more

Dr. Krestina Amon is a Senior Lecturer at the University of Sydney's Faculty of Health Sciences within the Biomedical Informatics and Digital Health (BIDH) department. She is a core member of the Cyberpsychology Research Group (CRG), focusing on digital health innovations, social media's role in health and education, and technology-based interventions for mental health. Her work spans child/adolescent mental health, serious games for healthcare training, and social media's impact on professional and peer interactions. Dr. Amon holds a PhD and a First Class Honors degree in Behavioural Health Science, alongside a Senior Fellowship from the Higher Education Academy (SFHEA). Her teaching includes coordinating the units BIDH3008 Digital Health in Practice and BIDH5000 Digital Health Innovation and Implementation . Her research emphasizes: Technology-driven mental health programs for youth Social media platforms for healthcare professional collaboration Impact of biofeedback games on ADHD symptom management Digital recruitment strategies in health studies Awards include the 2024 SEMCAN Good Mentor Award and 2013 Faculty Dean’s Citation for Teaching Excellence. Current projects investigate healthcare professionals' use of online platforms for peer education and interprofessional learning, alongside Pacific Island adolescents' digital health literacy. Her work bridges clinical practice, technology development, and educational innovation. Notable contributions include the Kids Helpline Circles social network platform for mental health support and studies on YouTube/Instagram content analysis for health communication.

• Multimedia Computing
• Computer Vision
• Computer Graphics
• +7 more

Professor Zhiyong Wang is a faculty member at the School of Computer Science, University of Sydney, serving as Deputy Director of Sydney Informatics Hub and Director of the Multimedia Computing Laboratory. His research focuses on multimedia computing, including information retrieval, computer vision, AI, and applications in agriculture, healthcare, and environmental monitoring. He holds a B.Eng., M.Eng. from South China University of Technology, and a Ph.D. from The Hong Kong Polytechnic University. His work bridges theoretical advancements and real-world applications, with over 200 peer-reviewed publications. He is a member of IEEE and former President of Australia Pattern Recognition Society (APRS). Research Interests: Enabling computers to understand and create multimedia content, with emphasis on human-centric computing, remote sensing, and interdisciplinary applications. Notable areas include action recognition, medical image analysis, and environmental monitoring. Current Roles: Leads the Multimedia Computing Lab, collaborates with Sydney Institute of Agriculture and Brain and Mind Centre. Teaches COMP5216 (Mobile Computing), COMP5405 (Digital Media Computing), and COMP5425 (Multimedia Retrieval). Students: Supervises 9 Ph.D. students focusing on topics like precision agriculture, biomedical engineering, and AI-driven video analytics. Key projects include soil moisture forecasting, biomechanical risk analysis for knee osteoarthritis, and explainable machine learning.

Karen QuintilianiView profile

Professor

• Applied Anthropology
• Refugee Studies
• Diaspora Communities
• +4 more

Dr. Karen Quintiliani is a Professor in the Department of Anthropology at California State University, Long Beach (CSULB), within the College of Liberal Arts. Her research focuses on refugee and immigrant communities, particularly Cambodians in Long Beach, with expertise in applied anthropology, community-based service, and archival projects. She holds a B.A. in Sociology from Loyola Marymount University (1985), an M.A. in Applied Anthropology from CSULB (1995), and a Ph.D. in Anthropology from UCLA (2003). Her research interests include transnational diaspora, social welfare policy, gender and sexuality, refugee health, youth cultures, and program evaluation. She leads collaborative projects like the HERE LAB (exploring homelessness outreach) and the Cambodian Community History and Archive Project (CamCHAP) , a digital ethnography highlighting Cambodian Long Beach history through multimedia archives. These initiatives emphasize applied research and community partnership. Dr. Quintiliani’s work bridges academia and practice, training students in ethnographic methods while addressing real-world challenges such as homelessness and educational access. Her publications focus on Cambodian diaspora experiences, welfare policy impacts, and LGBTQ+ identities within the community. She collaborates with local agencies, including the City of Long Beach’s Health and Human Services Department, to develop evidence-based solutions. Notable projects include evaluating homeless outreach strategies and documenting Cambodian American political activism. Her efforts prioritize empowering marginalized communities through research that informs policy and fosters cultural preservation.

• Machine Learning
• Computer Vision
• Medical Imaging Analysis
• +5 more

Almabrok Essa is an Assistant Professor in the Department of Mathematics, Computer Science, and Data Science at John Carroll University. His research focuses on advanced machine learning techniques applied to medical imaging, computer vision, and signal processing. He holds a faculty position at Dolan Science Center E207 and can be reached via email at aessa@jcu.edu. His work bridges theoretical computer science with practical applications in healthcare, environmental monitoring, and security systems. Research interests include deep learning architectures for medical diagnostics (e.g., chest X-ray analysis and skin lesion segmentation), steganography for secure image transmission, and remote sensing technologies for geospatial analysis. He has pioneered methods like Multibit LSB matching for data hiding and developed frameworks like COVID-CLNet for pandemic response. His contributions span over 20 peer-reviewed articles from 2015 to 2025, showcasing innovations in face recognition algorithms, brain signal analysis, and environmental pattern recognition. Notable applied projects include real-time heart/respiration monitoring systems and automated machinery threat detection for infrastructure protection. His research demonstrates strong interdisciplinary potential, combining computational methods with domains like biomedical engineering, environmental science, and cybersecurity.

• Machine Learning
• Medical Image Analysis
• Computer Vision
• +5 more

Junxi Chen is an academic affiliated with Dalian University of Technology's School of Software. His research focuses on advanced machine learning techniques, medical image analysis, and computer vision applications in healthcare. He has contributed significantly to adversarial machine learning, robust deep learning models, and medical image segmentation. His work bridges theoretical advancements with practical applications in medical diagnostics and data security. Key research areas include adversarial attacks/defense mechanisms, medical imaging segmentation (e.g., skin lesions, tumors), and innovative neural network architectures like UNet variants. He also explores secure data-hiding techniques in encrypted images and hybrid memory systems optimization. Publications span top venues such as CVPR, IEEE Transactions, and Medical Image Analysis journals. Collaborations with institutions like Dalian University of Technology and international co-authors highlight his global research impact.

Georgios SiolasView profile

Researcher

• machine learning
• text mining
• information retrieval
• +6 more

Georgios Siolas is a Senior Researcher at the Artificial Intelligence and Learning Systems Laboratory (NTUA-ISLab), part of the School of Electrical & Computer Engineering at the National Technical University of Athens (NTUA). He holds a BSc in Electrical & Computer Engineering from NTUA (1998), an MSc in Cognitive Science from Sorbonne Université (1999), and a PhD in Computer Science (2003). His research focuses on machine learning, text mining, information retrieval, and semantic web technologies, with applications in computer vision, recommender systems, and social network analysis. He develops intelligent systems for cultural heritage management, smart tourism platforms, and sign language recognition. Key contributions include innovations in neural architecture search, deep learning for hyperspectral imagery, and plagiarism detection in imbalanced datasets. His work integrates semantic technologies with pervasive computing for smart home environments.