Find Academic Supervisors

• Generative AI
• Computer Vision
• Deep Learning
• +6 more

Dr. Mohamed Saadeldin is an Assistant Professor at the School of Computer Science, University College Dublin (UCD). He holds a B.Sc. (Honours) in Electrical & Electronic Engineering from the University of Khartoum (2005) and a Ph.D. in Computer Science from UCD (2013). His research spans generative AI, computer vision, and foundation models, with applications in healthcare, biomedicine, robotics, and energy. Recently, he has focused on AI-driven solutions for healthcare disparities, such as automated breast cancer screening using low-cost ultrasounds, and multimodal foundation models for precision medicine. He also explores LLM-driven UAV navigation and energy grid management using transformer models. Education: B.Sc. (Honours) in Electrical & Electronic Engineering, University of Khartoum, 2005 Ph.D. in Computer Science, University College Dublin, 2013 Teaching: Coordinates modules in Computer Graphics, Data Structures and Algorithms, and Mobile Computing at UCD’s joint college in China (BDIC). His research interests include generative AI for healthcare, computer vision in robotics, and deep learning for agricultural optimization. Notable projects include vision foundation models for medical imaging, collaboration with Systems Biology Ireland on multimodal models for drug repurposing, and energy grid management via smart meter data analysis. He has authored/co-authored over 30 publications, including IEEE transactions and book chapters. Grants and collaborations involve industry partnerships on load disaggregation and academic projects like VistaMilk for dairy sector applications. His early work on ultrasonic systems for indoor localization and gesture control demonstrates his long-standing expertise in signal processing and human-AI interaction.

Soumyabrata DevView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Remote Sensing
• +6 more

Soumyabrata Dev is an Assistant Professor in the School of Computer Science at University College Dublin (UCD), where he leads the THEIA lab focusing on interdisciplinary research in computer vision, machine learning, and remote sensing. His work addresses challenges in climate science, environmental monitoring, solar forecasting, and healthcare. He holds a PhD from Nanyang Technological University (Singapore) and has held postdoctoral roles at Trinity College Dublin and ADAPT SFI Research Centre. His education includes a B.Tech. (summa cum laude) from National Institute of Technology Silchar, India, and a visiting doctoral experience at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to academia, he worked as a network engineer at Ericsson India (2010–2012). Research interests span image processing, environmental data analytics (e.g., air/water quality), solar energy forecasting, and AI-driven solutions for sustainable development. He collaborates globally with institutions in academia, industry, and government, aligning with UCD’s strategic goals for impactful innovation. He is an SFI Funded Investigator at ADAPT SFI and a UCD Climate Fellow (2024–2026). His scientific awards include the 2024 Stanford/Elsevier Top 2% Scientists List. He advises numerous PhD/MSc students on topics like coastal monitoring, air quality modeling, and AI for sustainability. THEIA Lab’s projects include solar irradiance forecasting, knowledge graph-based climate data platforms, and blockchain-enhanced healthcare systems. He teaches modules on Operating Systems, Wireless Sensor Networks, and Augmented/Virtual Reality. His work bridges theory and application, emphasizing real-world impact in climate action and renewable energy.

Kelley S. ReganView profile

Professor

• Special Education
• Learning Disabilities
• Emotional and Behavioral Disorders
• +7 more

Dr. Kelley S. Regan is a Professor in the School of Education (SOED) at George Mason University, serving as Division Director for Special Education and affiliated with the Helen A. Kellar Institute for Human disAbilities. She specializes in improving evidence-based practices for special education teachers and developing technology-based interventions to enhance writing skills for students with disabilities. Her research focuses on teacher preparation, writing instruction, and the integration of technology in education. Dr. Regan holds a PhD in Special Education from George Mason University (2005) and has extensive experience teaching students with mild disabilities, including learning disorders, ADHD, autism, and emotional/behavioral disorders. She has secured over $10 million in grants from the U.S. Department of Education and Virginia Department of Education, leading projects like Project WEGOMEGA and WEGO-RIITE to advance writing interventions and technology adoption in special education. Her publications include influential works such as The Inclusive Classroom: Strategies for Effective Differentiated Instruction and numerous articles on writing interventions, eCoaching, and teacher training. She served as editor of The Teacher Educators’ Journal and teaches courses including special education methodology and research standards for individuals with disabilities. Dr. Regan’s work emphasizes program development, teacher resilience during crises (e.g., the pandemic), and leveraging technology for equitable instruction. Key collaborations include partnerships with Virginia’s Department of Education to address teacher shortages through endorsement programs.

Giorgos SfikasView profile

Assistant Professor

• Computer Vision
• Image Processing
• Machine Learning
• +4 more

Giorgos Sfikas is an Assistant Professor at the University of West Attica and a researcher at the National Centre for Scientific Research 'Demokritos'. He holds a PhD in Image Processing and Computer Vision (University of Strasbourg, 2012), MSc in Computer Science (University of Ioannina, 2007), BSc in Computer Science (2004), and a BA in History & Archaeology (2014). His research focuses on Computer Vision, Machine Learning, Document Image Processing, and applications in Cultural Heritage. He has authored over 50 peer-reviewed publications, including best paper awards in biomedical imaging and bioengineering. Notable contributions include work on quaternionic neural networks, GANs for document processing, and the Bessarion dataset for medieval Greek inscriptions. Teaching includes courses on Computer Graphics, Machine Learning, and Photogrammetry. He leads projects in multispectral imaging, historical document analysis, and AI-driven archaeology.

J. Andreas BærentzenView profile

Associate Professor

• Computer Graphics
• Shape Modelling
• Real-Time Rendering
• +5 more

Professor J. Andreas Bærentzen is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), where he has held academic positions since 2001. His research focuses on computer graphics, shape modeling, real-time rendering, and geometry processing. He holds a MSc Eng (1998) and PhD (2003) from DTU. His work emphasizes topological adaptability in shape representation and efficient geometry processing, with notable contributions to structural topology optimization, 3D reconstruction, and virtual reality applications. Education: MSc Eng, Technical University of Denmark, 1991–1998 PhD, Technical University of Denmark, 1998–2003 Research Interests: Interactive 3D modeling and real-time graphics Topology optimization and structural infill design Shape modeling using distance fields and deformable hypersurfaces Applications in biomedical imaging (e.g., white matter dynamics) and environmental engineering (e.g., tree geometry simulation) His recent publications highlight advancements in neural network-based shape representation, skeletonization for tree reconstruction, and inverse-designed structural infill for engineering. He supervises multiple PhD students and leads projects on robotic manufacturing and virtual reality visualization. Bærentzen collaborates internationally, including visits to Stony Brook University (USA) and Padova University (Italy). Advisees & Projects: PhD Students: Rui Cui, Thomas D. V. Christiansen, Elias Theil Gæde Key Projects: 'Generative Methods for Brain Tissue Phantoms', 'Neural Form Representation', 'Graph Algorithms with Geometric Applications' His work bridges theoretical geometry processing with practical applications in architecture, biomedical engineering, and environmental science, leveraging DTU's interdisciplinary research ecosystem.

Tom GarnerView profile

Senior Lecturer

• Extended Reality (XR) Technologies
• Auditory Perception Theory
• Psychophysiological Data Collection
• +5 more

Dr Tom Garner is a Senior Lecturer in Interactive Technologies at Sheffield Hallam University and Senior Research Fellow at the Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research (CENTRIC). He holds a BA (Hons), MA, PGCE, and PhD. His research focuses on auditory perception theory, extended reality (XR) technologies for training, and psychophysiological data collection methods. Teaching responsibilities include courses like BSc Computer Science for Games and modules such as Virtual Reality Development. Key projects include the ACCOMPLICE military training system (funded by DASA) and the DentaSIM dental training simulator. He has collaborated with organizations like BAFTA, DSTL, and Epic Games. Education: BA (Hons), MA, PGCE, PhD Research Centres: CENTRIC, Advanced Wellbeing Research Centre, Industry and Innovation Research Institute His work spans serious games, VR/AR applications, and biofeedback systems. Notable publications include How the World Listens (Routledge, 2022) and contributions to the Oxford Handbook of Sound & Imagination. Awards: Fellow of the Higher Education Academy (FHEA) Current research explores asymmetric multiplayer XR systems, gesture-based interaction, and real-time psychophysiological monitoring. He supervises PhD students in HCI theory, XR platform development, and UX methodologies.

Mengyu XuView profile

Associate Professor

• High-Dimensional Statistics
• Time Series Analysis
• Covariance Matrix Estimation
• +5 more

Dr. Mengyu Xu is an Associate Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF). She holds a Bachelor's degree from Renmin University of China (2010), and a M.S. and Ph.D. from the University of Chicago (2012 and 2016). Her research focuses on high-dimensional statistical methods, time series analysis, and machine learning applications in diverse fields such as gas turbine performance prediction, terahertz spectroscopy of molecular crystals, and financial market dynamics. She is affiliated with the College of Sciences at UCF and teaches courses in statistics. Her research interests include covariance matrix estimation, dynamic network recovery from high-dimensional time series, distribution theory of quadratic forms, and hypothesis testing. Notably, she has contributed to advancements in fentanyl detection via terahertz spectroscopy and anomaly detection in industrial systems. Her work bridges statistical theory with practical applications in engineering, finance, and chemistry. Publications highlight her expertise in high-dimensional data analysis, machine learning integration with traditional statistical methods, and the development of novel methodologies for real-world challenges such as drug identification and predictive maintenance in gas turbines. She has explored asymmetric self-exciting processes in Bitcoin returns and contextual factors influencing student performance in online education environments. Labs/Teams: While no specific lab or team names are listed, her work suggests collaboration with interdisciplinary groups in data science, engineering, and computational chemistry at UCF.

• Digital Health
• Artificial Intelligence
• Generative AI (GenAI)
• +8 more

Associate Professor Georg Grossmann is affiliated with the School of IT and Mathematical Sciences at the University of South Australia (UniSA), within the Advanced Computing Research Centre. He holds roles as the Research Degree Coordinator for Maths & Stats and Systems Engineering at UniSA STEM, and co-directs the Digital Health Innovation and Clinical Informatics (DHICI) Lab. His research focuses on Digital Health, Artificial Intelligence (AI), Industry 4.0, and interoperability solutions for complex systems. He is also a member of the AI & Software Engineering Lab in the Industrial AI Research Centre, addressing challenges in data integration and business process modeling. Research Interests: Georg's work spans process and data interoperability, AI-driven systems, generative AI (GenAI), and digital transformation. He explores applications in healthcare (e.g., clinical decision support systems), industrial IoT (IIoT), and cultural heritage management. His methodologies include multi-level modeling, knowledge graphs, and semantic frameworks to enhance system interoperability and decision-making. Labs & Collaborations: He leads the DHICI Lab and collaborates with institutions like MIMOSA, Practera, and BAE Systems. His projects include frameworks for predictive maintenance in Industry 4.0, adaptive clinical decision systems, and NLP-based artifact management in museums. He has secured grants from the South Australian Premier’s Research and Industry Fund and the Australian Government’s Department of Industry. Teaching & Supervision: As a Research Degree Supervisor, he guides students in areas like enterprise modeling, software engineering, and AI applications. He also contributes to courses on Business Process Management and Software & Data Modeling.

• Extended Reality (XR)
• Human-Computer Interaction (HCI)
• Privacy and Security
• +3 more

Ass.-Prof. Dr. Pascal Knierim is an Assistant Professor at the Department of Computer Science, University of Innsbruck. He leads the Interactive Graphics and Simulation Group , focusing on Extended Reality (XR), Human-Computer Interaction (HCI), and privacy in digital environments. His research explores the societal impact of emerging technologies, including thermal imaging, drones, and AI integration with XR. Key areas of investigation include user perception in content blocking (e.g., 'Ad-Blocked Reality'), social behavior in VR (e.g., 'Navigating the Virtual Gaze'), and ethical design of mixed reality systems. His work bridges theoretical research with practical applications, such as privacy-aware smart home interfaces ('PriKey') and biometric identification via thermal imaging ('HotFoot'). Knierim’s publications often highlight trends in XR’s ethical implications, such as dark patterns in MR, and the intersection of AI with immersive technologies. His lab emphasizes collaboration, evidenced by contributions to frameworks like 'Lenssembly' for AR-based assembly instructions. His office hours are Monday to Friday, 09:00–13:00, and he is located at ICT 3N08, Technikerstraße 21a, Innsbruck.

• Web Engineering
• Web Measurement
• Web Security
• +3 more

Dr Yanlong Zhang is a Senior Lecturer at Manchester Metropolitan University. He holds a PhD in Software Engineering and a PGCE in Higher Education, complemented by industry experience as an Assistant Engineer, Engineer, and Teaching Assistant. His research focuses on web engineering, including web measurement, security, and games design, with particular attention to software metrics and user interface design. Teaching responsibilities include undergraduate modules on web design and development, computer systems, game design, and human-computer interaction, as well as postgraduate courses in information systems. His work explores GUI generation using GANs, structural similarity in source code, and navigability metrics for websites. Research outputs span topics like melanoma classification via image similarity and quality analysis of software architectures. His publications demonstrate expertise in both theoretical frameworks (e.g., HASARD model) and applied systems (e.g., MEIC design). Office hours are Monday 10-11, 1-2, and Thursday 10-11. Proficient in English, Chinese, and basic Japanese/German, Dr Zhang contributes to education and industry through his roles as a Fellow and teaching-focused academic. His work bridges software engineering principles with practical web development challenges.

Rawan AlghofailiView profile

Assistant Professor

• Augmented Reality (AR)
• Virtual Reality (VR)
• Human-Computer Interaction (HCI)
• +3 more

Dr. Rawan Alghofaili is an Assistant Professor in the Department of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. She specializes in Augmented Reality (AR), Virtual Reality (VR), Human-Computer Interaction (HCI), and Eye-tracking technologies. Her work emphasizes user-centered design principles and accessibility, with applications in assistive technology and virtual training systems. Education: PhD in Computer Science (2022), George Mason University MS in Computer Science (2018), University of Massachusetts-Boston MEng in Computer Science (2014), Cornell University BS in Information Technology (2011), King Saud University Research Interests: Dr. Alghofaili's research focuses on advancing AR/VR systems through innovative interaction techniques, including gesture-based input, error-aware mediation, and gaze-tracking applications. She explores how these technologies can enhance accessibility for individuals with communication challenges and improve virtual training environments. Her work often intersects with assistive technology, spatial computing, and user behavior analysis. Publications Trends: Her recent work spans topics such as flying creature animation paths in outdoor AR, mixed reality AAC applications for expressive language support, and environment-aware 3D sketching tools. Earlier contributions include VR navigation aids and reviews of skill training applications in healthcare and retail. Professional Activities: She serves on program committees for prestigious venues such as IEEE VR, Eurographics, and CHI. Her current focus includes establishing remote VR training facilities and developing error-detection systems in gesture input. Labs/Teams: Her research group likely focuses on XR applications, HCI innovations, and assistive technology solutions, though specific lab names are not explicitly stated in the provided data.

Amber WagnerView profile

Lecturer

• Computer Science Education
• Human-Computer Interaction
• Accessible Computing
• +3 more

Dr. Amber Wagner serves as Co-Director in the Department of Computer Science at the University of Alabama at Birmingham (UAB), within the College of Arts and Sciences. She holds a Ph.D. from the University of Alabama, alongside M.S. and B.S. degrees in Information Systems and Computer Science from Kennesaw State University. Her work focuses on computer science education, human-computer interaction, and accessible computing, particularly addressing underrepresented groups and students with disabilities in STEM fields. Dr. Wagner has received teaching awards from Kennesaw State University and Birmingham-Southern College. Her research includes projects on pseudorandom number generators, accessible programming tools for motorically challenged students, and strategies to increase diversity in computing. She actively supports student organizations and mentors undergraduate researchers exploring topics like robotic arms and human trafficking data analysis through computational methods. Her publications emphasize inclusive educational technologies, tactile and voice-based programming interfaces, and regional initiatives to expand STEM accessibility. She advocates for policy-driven solutions to enhance representation of disabled students in computing through collaborative statewide programs. Education: Ph.D., University of Alabama, Computer Science M.S., Kennesaw State University, Information Systems B.S., Kennesaw State University, Computer Science Key Contributions: Developed tactile input systems (CodeBox64) and voice-based programming tools (Myna) Pioneered screen-free coding activities for early childhood education Advances disability inclusion in STEM through regional collaboration Awards: Teaching Excellence Award, Kennesaw State University Innovative Pedagogy Award, Birmingham-Southern College

Przemyslaw MusialskiView profile

Associate Professor

• geometric design
• computer graphics
• digital fabrication
• +1 more

Przemyslaw Musialski is an Associate Professor of Computer Science at New Jersey Institute of Technology (NJIT), USA. His research focuses on geometric design, computer graphics, digital fabrication, and machine learning, aiming to develop algorithmic solutions for computational design and fabrication processes. Previously, he led the Computational Fabrication group at TU Wien's Center for Geometry and Computational Design (GCD), serving as an assistant professor there. He holds a PhD in Computer Science from TU Wien (2010) and an MSc in Media Sciences from Bauhaus University Weimar (2007). His academic journey includes roles at VRVis Research Center, Arizona State University as a postdoc, and KAUST as a visiting researcher. His work bridges computational geometry, fabrication-aware design, and AI applications in architecture and engineering. Notable contributions include methods for procedural facade generation, elastic geodesic grid structures, and neural surface reconstruction techniques. He actively contributes to international conferences and journals in computer graphics and geometric design. Research interests emphasize geometric algorithms, digital fabrication workflows, and integrating machine learning to enhance design automation. His lab explores applications in architectural design, 3D printing, and interactive modeling tools.

Zhihao YaoView profile

Assistant Professor

• Computer Security
• Operating Systems
• Mobile Computing
• +3 more

Zhihao Yao is an Assistant Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). His research focuses on secure systems design, mobile security, and hardware-software co-design for trustworthy computing. He holds a Ph.D., M.S., and B.S. in Computer Science from the University of California, Irvine (2023, 2020, 2017 respectively). His work emphasizes minimizing trust in computing systems through physically isolated hardware, secure code generation, and privacy-preserving technologies. Notable contributions include developing frameworks like Hora for life-critical smartphone applications, Casper for LLM privacy protection, and ProvCam for verifiable video capture systems. He received the 2023 Best Artifact Award at ACM MobiSys for impactful research contributions. Education: Ph.D. in Computer Science, University of California-Irvine (2023) M.S. in Computer Science, University of California-Irvine (2020) B.S. in Computer Science, University of California-Irvine (2017) Recent work explores fuzzer-assisted security testing for WebGL, real-time anomaly detection in energy systems, and minimizing trusted computing bases (TCBs) in mobile devices. His research bridges theoretical security principles with practical implementations across hardware, operating systems, and application layers. Awards: 2023 Best Artifact Award, ACM MobiSys Teaching includes advanced courses on operating systems principles. His lab develops novel solutions for securing modern computing environments through interdisciplinary approaches.

• Software Engineering Education
• Computational Technology in Education
• Machine Learning Applications
• +5 more

Saheed Popoola, PhD, is an Assistant Professor at the University of Cincinnati's CECH - School of Information Technology. His research spans software engineering education, computational technology in K-12 classrooms, and model-driven engineering. He actively explores strategies to enhance collaborative learning environments through student-driven software projects and investigates challenges in open-source development and cybersecurity incident analysis. His work bridges empirical software engineering practices with educational technology, focusing on topics such as static analysis tool efficacy, user sentiment analysis in software communities, and ensemble learning techniques for network security. He has contributed to tools like Loupe for model analysis and has examined LabVIEW/Simulink model evolution patterns. Recent studies include the impact of computational thinking in K-12 education, early heart disease detection via machine learning, and strategies for managing diverse classroom environments. His research emphasizes practical applications in both academic and industrial software development contexts. Notably absent from the provided data are specific details about grants, awards, or direct student advising. However, his involvement in initiatives like the student software solutions center highlights a focus on experiential learning and community-driven development practices.