Find Academic Supervisors

• Computational Intelligence
• Machine Learning
• Time Series Forecasting
• +5 more

Dr. Hai Yan Lu is an Associate Professor at the School of Computer Science , Faculty of Engineering and Information Technology , University of Technology Sydney (UTS) . She serves as Head of Discipline for Data Analytics and is a core member of the Decision Systems and e-Service Intelligence Lab within the Centre for Artificial Intelligence at UTS. Her academic journey includes a PhD in Engineering (2002) from UTS, Master of Engineering (1988) and Bachelor of Engineering (1985) from Harbin University of Science and Technology , China. She transitioned from a Lecturer at Yanshan University to UTS in 1994. Research Interests: Computational Intelligence, Time Series Forecasting, Data Analytics, Electromagnetic Material Modeling, 3D Human Pose Estimation, Smart Energy Systems Key Projects: Smart Power Grids, Intelligent Multi-Agent Systems, Predictive Analytics for Renewable Energy, Electromagnetic Device Optimization Technical Expertise: Machine Learning, Deep Learning, Federated Learning, Multi-Objective Optimization, Granular Computing Professional Affiliations: Senior Member, IEEE Member, ACM Vice Chair, IEEE NSW Section Women in Engineering Secretary/Treasurer, IEEE NSW Computational Intelligence Chapter Her recent publications demonstrate cutting-edge work in: Regularized Deep Learning for Financial Risk Modeling GAN-based Environmental Forecasting Hybrid Forecasting Systems for Solar Energy Advanced Magnetic Material Characterization Explainable AI for Industrial Applications

• Computer Vision
• Machine Learning
• Robotics
• +6 more

Dr Mehdi Hosseinzadeh is a Postdoctoral Research Fellow at the Australian Institute for Machine Learning (AIML) within the University of Adelaide . His research sits at the intersection of Computer Vision , Machine Learning , and Robotics , with a focus on self-supervised multi-modal learning for robotics and autonomous driving applications. He earned his PhD from the University of Adelaide, where he conducted pioneering work in real-time structure and object-aware semantic visual SLAM through the Australian Centre for Robotic Vision . His research integrates advanced 3D scene understanding and object detection to enhance traditional geometric SLAM frameworks. Currently, he supervises Master’s students in the Artificial Intelligence and Machine Learning program and contributes to projects advancing robotic vision technologies. His lab affiliations include the Australian Institute for Machine Learning, located in the AIML Building (Lot 14) on the University of Adelaide campus.

• Deep Learning
• Medical Multimedia
• Explainable AI
• +5 more

Steven Hicks is a Senior Research Scientist in the Holistic Systems department at Simula Metropolitan. His work focuses on applying artificial intelligence techniques to medical and multimedia applications, with particular emphasis on explainability and transparency in AI systems. Dr. Hicks' research spans multiple domains including medical imaging, particularly in gastrointestinal endoscopy and reproductive medicine. His primary interests include Deep Learning , Medical Multimedia , Explainable AI , and Computer Vision . His work has significant applications in polyp detection, sperm analysis, ECG interpretation, and medical image segmentation, contributing to advancements in diagnostic accuracy and clinical decision support systems. Analysis of Dr. Hicks' recent publications reveals a strong focus on medical applications of AI with emphasis on transparency and explainability. His work frequently addresses challenges in gastrointestinal endoscopy, reproductive medicine, and cardiology. A notable trend is his involvement in creating benchmark datasets like Kvasir-VQA and VISEM-Tracking, and organizing challenges through MediaEval and ImageCLEF to advance the field of medical AI and establish standardized evaluation frameworks. Dr. Hicks actively collaborates with medical professionals and researchers across multiple institutions, contributing to the development of practical AI solutions for real-world medical problems. His work bridges the gap between theoretical AI research and clinical applications, with significant contributions to both technical innovations and the creation of essential resources for the medical AI community.

• Image Processing
• Pattern Recognition
• Multi-media
• +3 more

Seiichiro Kamata is a Professor at Waseda University's Faculty of Science and Engineering, specifically within the Graduate School of Information, Production, and Systems. He holds a Doctor of Engineering degree from Kyushu Institute of Technology and maintains an active research laboratory focused on advanced image processing techniques. His professional affiliations include the Institute of Electrical and Electronics Engineers, Institute of Image Information and Television Engineers, Information Processing Society in Japan, and Institute of Electronics, Information and Communication Engineers. Professor Kamata's research spans image processing, pattern recognition, multi-media systems, and signal processing with particular emphasis on deep learning applications. His work bridges theoretical advancements with practical implementations across medical imaging, hyperspectral analysis, and real-time computer vision systems. Recent publications demonstrate his leadership in developing novel neural network architectures for medical diagnostics, video enhancement, and document analysis. His publication record shows consistent high-impact contributions, particularly in medical image analysis (including Alzheimer's disease classification, ADHD diagnosis, and skin lesion detection) and computer vision techniques (including real-time semantic segmentation, visual tracking, and hyperspectral image classification). The research demonstrates a clear trajectory from foundational image processing algorithms toward sophisticated deep learning frameworks. Best Paper Award at ICIPRoB2020 (2020) - Constant-Time Gaussian Filtering Best Paper Award at ICSIPA2019 (2019) - Edge-guided Hierarchically Nested Network Best Paper Award at ICIEV2018 (2018) - Deep Neural Networks with Mixture of Experts Best Paper Award at Image Media Processing Symposium (2017) Best Paper Award at ICARCV2010 (2010) - Fast Polar Harmonic Transforms Professor Kamata's research group maintains a strong publication record with 266 papers and 1,622 citations (h-index: 21) as of September 2025. His work demonstrates consistent innovation in both theoretical foundations of image processing and practical applications across medical diagnostics, robotics, and cultural heritage preservation. The laboratory continues to produce cutting-edge research with recent focus on transformer architectures, multi-modal fusion techniques, and medical AI applications.

Anna WessmanView profile

Professor

• Iron Age Archaeology
• Scandinavian Archaeology
• Finnish and Baltic Prehistory
• +8 more

Anna Wessman is a Professor of Iron Age Archaeology at the Department of Cultural History, University Museum of Bergen. Her research spans Late Iron Age Finland and the Baltic region, burial archaeology, metal-detecting cultures, citizen science, and museum studies. She has led major projects like the Levänluhta water burial analysis and co-developed the semantic portal FindSampo , integrating public finds into open-access databases. PhD in Archaeology (University of Helsinki, 2010) with a focus on Iron Age burial rituals Acting University Lecturer in Museum Studies, University of Helsinki (2015-2017) Adjunct Professor in Iron Age Studies, University of Turku (2022 onwards) Her research combines ethnographic methods with isotopic analysis, examining topics like the Finnar in sagas, cremation practices, and the role of citizen scientists in archaeology. She collaborates across disciplines, including genetics (e.g., Levänluhta isotope studies) and digital humanities ( FindSampo platform). Recent articles highlight her work on metal-detected artifact networks (2025), Viking Age magic interpretations (2025), and cremation studies (2024). Her projects have been funded by the Kone Foundation, Academy of Finland, and Emil Aaltonen Foundation, focusing on community archaeology and digital heritage platforms. Wessman actively bridges academic and avocational communities, advocating for structured collaboration with metal-detectorists to enhance archaeological data. Her publications address ethical dilemmas in displaying human remains (2021) and methodological innovations like 'archaeological object interviews.' Key affiliations: University of Bergen (current), University of Helsinki (PhD), University of Turku (Adjunct Professor) Founding member of the European Public Finds Recording Network and Cultural Heritage Crime Network

• Computer System Software
• Image Processing
• Programming Languages
• +3 more

Murat IŞIK is a Lecturer in the Department of Computer Engineering at the Faculty of Engineering and Architecture, Kırşehir Ahi Evran University. He has been serving as a full-time faculty member since 2017 and currently holds additional administrative positions as Department Head (since 2025) and Research Application Center Deputy Director (since 2024). PhD in Computer and Information Engineering, Sakarya University (2011-2017) MSc in Computer Engineering, Sakarya University (2009-2011) Bachelor's Degree from Dicle University, Batman Technical Education Faculty (2002-2006) Dr. IŞIK's research spans multiple areas in computer science and engineering, with a focus on artificial intelligence applications. His primary research interests include Computer System Software, Image Processing, Programming Languages, Computer Software and Software Engineering, Machine Learning, and Artificial Intelligence. His work demonstrates a strong interdisciplinary approach, applying computer vision and deep learning techniques to diverse fields including medical diagnostics, education technology, and accessibility solutions. His recent publications show a trend toward practical applications of AI in education, healthcare, and everyday life challenges. He has developed innovative solutions such as real-time assessment systems for primary schools, assistive technology for visually impaired individuals, and classification systems using deep learning approaches. Research World Medal and Research World Excellent Paper Award (2016) Dr. IŞIK has successfully supervised multiple master's students and is actively involved in numerous research projects funded by higher education institutions. His projects range from BCI-supported deep learning models for motor/facial movement detection to AI-assisted insole production and intelligent test systems for primary school students. He has secured funding for projects extending through 2027, demonstrating sustained research productivity. He leads the Computer Engineering department's research efforts and has established collaborations with researchers both within Turkey and internationally, particularly in Iraq. His laboratory work focuses on implementing practical AI solutions with an emphasis on accessibility and educational applications.

Martin MiddendorfView profile

Professor

• Swarm Intelligence
• Bioinformatics
• Genome Rearrangement Analysis
• +7 more

Prof. Dr. Martin Middendorf is a faculty member at the Department of Computer Science , Faculty of Mathematics and Computer Science , Leipzig University , Germany. He leads the Swarm Intelligence and Complex Systems Group and focuses on interdisciplinary research at the intersection of computational methods and biological systems. Fields of Interest Swarm Intelligence Bioinformatics Genome Rearrangement Analysis Combinatorial Optimization Evolutionary Algorithms Task Allocation in Multi-Agent Systems His recent research emphasizes mitochondrial genome annotation , predator-prey dynamics in swarm systems , and metaheuristic algorithms for dynamic optimization . Key trends include de-Bruijn graph applications , pheromone-dependent movement modeling , and automated behavior tracking in social insects . Supervised Students Dr. Nicolas Wieseke Dr. Hoang Thanh Le Dr. Fatma Turna Tobias Jagla Carsten Seemann Prof. Middendorf's group develops tools like DeGeCI 1.1 for mitochondrial gene annotation and explores swarm-controlled emergence in ant clustering systems. They apply swarm intelligence principles to solve real-world problems in vehicle routing , sewer network design , and biomedical signal processing .

Tim Wilhelm NattkemperView profile

Professor

• Bioinformatics
• Bioimage Informatics
• Computer Vision
• +6 more

Prof. Dr.-Ing. Tim Wilhelm Nattkemper leads the Biodata Mining Group at the Faculty of Engineering , Universität Bielefeld , while holding affiliations with the Center for Biotechnology (CeBiTec) and the Institute for Bioinformatics Infrastructure . His work bridges bioinformatics with marine environmental monitoring , focusing on machine learning and computer vision applications. The group specializes in multivariate bioimage analysis , developing platforms like BioIMAX for web-based high-dimensional data exploration. Research spans from MALDI imaging to deep-sea megafauna classification , integrating information visualization and web technologies . Recent projects address seafloor macrolitter monitoring , coral stress response analysis , and self-supervised learning for diatom classification. Their 15 most recent publications (2023-2025) highlight advancements in marine imaging , automated annotation systems , and AI-driven biodiversity assessment , particularly in polymetallic nodule fields. The group also tackles technical challenges like data imbalance in marine image classification and FAIR data principles implementation. As module responsible for courses like Information Visualization and Introduction to Bioinformatics , Nattkemper contributes to academic training in bioinformatics and data science . His interdisciplinary collaborations span physics , chemistry , and ecology within Bielefeld's Material World strategic research area.

Franziska KlemsteinView profile

Researcher

• Monument Preservation
• Digital Humanities
• GDR Architectural History
• +3 more

Dr. Franziska Klemstein is an active researcher specializing in monument preservation and digital humanities, with significant contributions to understanding heritage practices in the German Democratic Republic (GDR) era. Her work critically bridges historical scholarship and computational methods, particularly through the development of specialized datasets for document analysis and image retrieval in cultural heritage contexts. Her research focuses on: Monument preservation systems under socialist regimes Ethical implementation of AI in heritage documentation Diversity and inclusion challenges in conservation practices Classification methodologies for historical inventories Digital reconstruction of contested heritage sites Gender dynamics in preservation professions Analysis of Klemstein's recent publications reveals a methodological evolution from historical analysis toward technical innovation, with increasing emphasis on dataset creation (DHMTIC, DHREAAL, TexBiG) and evaluation frameworks for heritage computing. Her work consistently addresses the tension between digital efficiency and critical heritage values, particularly regarding sustainable AI implementation and inclusive documentation practices. While specific awards remain undocumented in the provided materials, her editorial leadership in significant volumes like "On the Way to a Place of Remembrance" (2024) demonstrates recognized expertise. Klemstein's collaborative projects with researchers like Tschirschwitz and Schmidgen indicate active participation in interdisciplinary teams focused on digital heritage solutions, though institutional affiliations and grant details aren't specified in the current text.

Touradj EbrahimiView profile

Professor

• Image and Video Compression
• Media Security
• Multimedia Signal Processing
• +5 more

Touradj Ebrahimi is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he heads the Multimedia Signal Processing Group (MMSPG) within the School of Engineering's Institute of Electrical Engineering. He holds a Ph.D. in Electrical Engineering from EPFL and serves as the Convenor of the JPEG standardization committee. His research spans AI-powered imaging, multimedia signal processing, and media security. Research Interests: Professor Ebrahimi's work focuses on next-generation image/video compression (including JPEG AI and DNA-based storage), quality of experience in immersive media, trustworthy media authentication (JPEG Trust), and explainable AI for biometric systems. His group pioneers methods for point cloud compression, deepfake detection, and privacy-preserving multimedia. Publication Trends: Recent articles emphasize AI-driven compression standards, quality assessment for emerging media (point clouds, HDR), and explainability in computer vision. Key themes include JPEG AI standardization, DNA storage for visual data, and robustness evaluation of deepfake detectors. Awards & Honors: IEEE Star Innovator Award in Multimedia IEEE and Swiss National ASE Awards ISO Certificates for MPEG-4/JPEG 2000 contributions Best Paper Award (IEEE Trans. Consumer Electronics) Fellow of IEEE and SPIE Leadership: He founded RayShaper SA, Genista SA, and Emitall SA. Represents Switzerland in ISO/IEC JTC1/SC29 and ITU, advising European Commission initiatives and venture capital firms on multimedia technologies. Facilities: Leads the MMSPG lab at EPFL, focusing on intelligent multimedia systems. The group collaborates globally on standardization (JPEG, MPEG) and EU projects.

• Multi-stable Perception
• Perceptual Inference
• Cognitive Neuroscience
• +7 more

Dr. Alexander Pastukhov is an Assistant Professor at the Department of General Psychology and Methodology, University of Bamberg. His research focuses on multi-stable perception , perceptual inference , and the interplay between attention and microsaccades . He develops open-source tools like saccadr , eyelinkReader , and bistablehistory for analyzing eye movements and perceptual dynamics. Research Interests : Multi-level mechanisms of perception and memory History effects in bistable perception Attentional allocation via microsaccade analysis Bayesian modeling of perceptual decision-making Scientific Awards : 2013 'Best of the Year' award from the Psychonomic Society for work on sensory memory and adaptation in structure-from-motion displays His recent software development includes probabilistic programming tools for 2D/3D transformations and eye-tracking analysis. He also contributes to applied data analysis teaching materials using R and Python. Collaborative projects with industry partners (e.g., BMW) and institutions (e.g., Fraunhofer, Orange Labs) highlight his research transfer efforts.

• Computer vision
• Robotics
• Machine perception
• +3 more

Christopher Hollitt is a Senior Lecturer and Programme Director of Electrical Engineering & Mechatronics at the School of Engineering and Computer Science, Victoria University of Wellington. His research focuses on developing autonomous mobile robots capable of interacting with dynamic environments through advanced visual perception systems. Dr. Hollitt holds a BE(Elec), BSc(Hon), and PhD from the University of Adelaide, Australia. His academic journey has led him to specialize in machine perception and robotic control systems. Dr. Hollitt's research interests center on machine perception, particularly machine vision, and the control of robotic and space systems. He aims to develop artificial robot 'minds' capable of perceiving and modeling the world in real time. His specific expertise includes active vision with time constraints, statistical underpinnings of active perception, vision-based estimation of robot pose, and multi-modal active perception systems. His work bridges the gap between theoretical computer vision and practical robotic applications, with emphasis on real-world implementation challenges. His publication record shows a clear progression from fundamental visual attention models to sophisticated context-aware object detection systems. Early work focused on color spaces and basic feature extraction, while recent research explores top-down contextual information integration and uncertainty modeling for improved target object detection. His approach increasingly incorporates evolutionary algorithms and probabilistic methods to create adaptive visual systems that can handle the complexities of real-world environments. Dr. Hollitt actively supervises graduate students, with current doctoral projects examining 'Low cost analysis of milk contaminants' and 'Droplet evaporation of complex fluids.' He previously supervised Jane, Celine's Master's research on spacecraft magnetic disturbance rejection. His grant history includes the 'Generic Shoulder Relief Appliance' project funded by the New Zealand Artificial Limb Service. Within the university, Dr. Hollitt contributes significantly to the academic community through his role as Programme Director and his teaching of advanced engineering courses, helping to shape the next generation of engineers and computer scientists.

• Social Cognition
• Early Childhood Cognition
• Social Development
• +5 more

Dora Kampis serves as a Tenure Track Assistant Professor in the Department of Psychology within the Faculty of Social Sciences at the University of Copenhagen. Her research focuses on the cognitive mechanisms underlying human social nature, spanning from infancy through adulthood. Her primary research interests include Social Cognition , Early Childhood Cognition , Social and Cognitive Development , and Developmental Cognitive Neuroimaging . Using behavioral methods (eye-tracking, looking time studies, interactive paradigms) and neuroimaging (primarily EEG), she investigates how social cognitive abilities emerge and develop, examining their interactions with perception and memory systems. Her work bridges ontogenetic and phylogenetic perspectives to understand the foundations of adult human cognition. Analysis of her recent publications (2021-2024) reveals a strong focus on infant social cognition, particularly perspective-taking abilities, self-other distinction, memory development, and semantic processing in preverbal children. Her research employs rigorous experimental designs with infants aged 14-36 months, often involving collaborative international studies. Key trends include investigating altercentric biases, cognitive flexibility in changing contexts, and the emergence of theory of mind precursors. Dr. Kampis maintains active research collaborations across multiple countries, as evidenced by her international co-authorship patterns. Her work has gained significant attention in the scientific community, with several publications covered by news outlets and discussed on academic social media platforms.

• Robotics
• Computer Vision
• Simultaneous Localization and Mapping (SLAM)
• +6 more

Niko Sünderhauf is a Professor in the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT), specializing in robotics, computer vision, and autonomous systems. His research spans visual place recognition, simultaneous localization and mapping (SLAM), neural radiance fields, and out-of-distribution detection for robotics applications. His research interests focus on enabling robots to understand and navigate complex environments through advanced computer vision techniques. He has made significant contributions to visual place recognition, particularly for handling viewpoint and environmental changes. His work on switchable constraints has improved robustness in SLAM systems, while his more recent research explores neural radiance fields, Gaussian splatting, and integrating large language models with robotic perception. Prof. Sünderhauf's publication record demonstrates consistent research productivity with 115 publications spanning from 2005 to 2025. His recent work shows a clear progression from traditional SLAM techniques toward more advanced neural scene representations and integration with large language models. His research has been published in top venues including IEEE ICRA, CVPR, IROS, and the International Journal of Robotics Research. Among his scientific contributions are novel approaches to visual place recognition that work across seasons and viewpoints, robust SLAM techniques that handle outliers and non-linearities, and recent innovations in neural scene representations for robotics. His work on switchable constraints has been particularly influential in the robotics community. Prof. Sünderhauf actively supervises PhD students including Dimity Miller, Krishan Rana, and Jad Abou-Chakra, who frequently appear as first authors on publications. His collaborative network includes researchers from QUT and international institutions, demonstrating strong research leadership in the robotics community.

Assaf HarelView profile

Associate Professor

• Cognitive Neuroscience
• Visual Recognition
• Visual Expertise
• +6 more

Assaf Harel is an Associate Professor in the School of Professional Psychology at Wright State University, where he investigates the neural basis of visual recognition in real-world contexts through a neuroergonomic approach. Education: PhD in cognitive neuropsychology from the Hebrew University of Jerusalem (Israel) Post-doctoral research fellowship at the National Institute of Mental Health (NIMH) at the National Institutes of Health (NIH) His research centers on visual expertise, object and scene recognition, augmented cognition, categorization, perceptual learning, and top-down control mechanisms. Dr. Harel employs interdisciplinary methods to bridge theoretical neuroscience with real-world applications, examining how brain activity generates high-level visual cognition during everyday tasks. Analysis of his 2012-2018 publications reveals consistent focus on the temporal dynamics of scene processing using EEG, the impact of task context on object recognition, and neural mechanisms of visual expertise. His work frequently integrates fMRI, EEG, psychophysics, and eye tracking to explore how top-down cognitive factors modulate visual processing across cortical regions. No scientific awards were documented in the provided materials. Details regarding student advising, grant funding, or mentorship activities were not specified in the source text. Dr. Harel directs the Human Neuroscience and Visual Cognition Lab, which utilizes multimodal cognitive neuroscience techniques to study perception-cognition interactions in ecologically valid settings, with applications in aviation ergonomics and human performance optimization.