ÖMER ÇAKIR is a Lecturer at the College of Engineering , Karadeniz Technical University , Department of Computer Engineering. His work spans computer graphics, software engineering, and signal processing. Education: Undergraduate (2001) and Postgraduate (2004) in Computer Engineering at Karadeniz Technical University. Academic Positions: Lecturer (2002–Present), Research Assistant (2001–2002). Research focuses on Computer Graphics , Signal Processing , and Optimization Algorithms . His conference papers address topics like virtual surgery simulations , fractured object reassembly , and TDOA-based localization . Key publication trends include parallel computing , 3D reconstruction , and PSO optimization . He has contributed to 13 peer-reviewed conferences. His contact email is cakiro@ktu.edu.tr , and he teaches BİLGİSAYAR GRAFİKLERİ-I and DATA STRUCTURES .
Professor Theodoridis Ioannis is a distinguished faculty member in the Department of Informatics at the University of Piraeus, where he serves as Director of the Data Science Laboratory within the School of Information and Communication Technologies. With a career spanning over two decades, he has established himself as a leading expert in data management and analysis. His research interests focus on Data Science, particularly in databases, big data management, data mining, and geoinformatics. Professor Theodoridis has made significant contributions to spatial database systems, time series analysis, and distributed data processing. His work bridges theoretical foundations with practical applications in areas such as smart cities, mobility analytics, and scientific data management. His publication record demonstrates consistent research productivity with over 100 peer-reviewed articles in top-tier venues, accumulating more than 10,000 citations. His research output shows a clear evolution from foundational database techniques toward contemporary challenges in big data analytics, machine learning integration, and privacy-preserving methods. Member of editorial board of ACM Computing Surveys (since 2016) Reviewer for numerous international journals and conferences Active participant in data management conference committees Professor Theodoridis has secured significant research funding through Horizon 2020 projects, serving as project coordinator and research team leader since 2001. His work demonstrates strong industry and academic collaboration, with applications spanning multiple domains. He has also co-authored three influential monographs in his field. He leads the Data Science Laboratory, which serves as a hub for interdisciplinary research at the intersection of database systems, machine learning, and domain-specific applications. The laboratory fosters collaboration between computer scientists, domain experts, and industry partners to address real-world data challenges.
Dario Lodi Rizzini is an Associate Professor at the Department of Engineering and Architecture, University of Parma, where he conducts research and teaching in robotics, computer vision, and autonomous systems. He has held academic positions including Research Assistant (2015–2020) and Assistant Professor (2021–2023) before becoming Associate Professor. His work spans industrial, agricultural, and underwater robotics applications. Research Interests: Localization, Mapping, and Navigation (SLAM) for mobile robots 3D perception and point cloud processing Robot manipulation and grasping Perception-aware control and pose estimation Applications in industrial automation, precision agriculture, and underwater intervention His recent publications show a strong trend in geometric algorithms for rotation and point cloud registration, particularly using the Angular Radon Spectrum, as well as practical deployments in warehouse automation and agricultural robotics. He has developed scalable systems for variable-rate irrigation and industrial depalletizing, demonstrating real-world impact. Scientific Awards and Recognition: Team leader of the University of Parma team that won Sick Robot Day in 2012 and 2014 Active IEEE member with publications in top-tier journals including IEEE Transactions on Robotics, IEEE RA-L, and IEEE ICRA/IROS Advising and Grants: Dario Lodi Rizzini has mentored numerous PhD students and postdocs, including Riccardo Monica, Ernesto Fontana, and Asad Ullah Khan. He has collaborated on multiple industrial and national research projects focusing on robotics in agriculture, warehouse automation, and underwater intervention, including the Italian MARIS project on underwater robotics. Labs and Teams: He is a key member of the Robotics and Intelligent Machines Lab (RIMLab) at the University of Parma, contributing to research in autonomous systems, perception, and manipulation. He has led teams in robotic competitions and collaborative industrial projects.
Panagiotis PAPADAKIS is an Associate Professor (HDR) in Informatics & Robotics at IMT Atlantique Bretagne/Pays de la Loire, Department of Informatics. He leads the RAMBO team at CNRS Lab-STICC and is an associate member of the IRL CROSSING. His research focuses on cognitive robotics, computer vision, and artificial intelligence with applications in assistive robotics, urban search and rescue (USAR), and 3D environment analysis. He has over €1M in research funding and has co-authored numerous top-tier publications in computer vision and robotics journals/conferences. Educations: PhD in Information Technology, National University of Athens (2009) Informatics and Telecommunications Degree, National University of Athens (2005) Research Interests: Robot Control and Navigation 3D Shape Analysis & Matching Urban Search and Rescue (USAR) Robotics Computer Vision for Assistive Technologies Cognitive Robotics and Human-Robot Interaction Key Projects: Leading RAMBO team in CNRS Lab-STICC Coordinated multi-robot assistance systems for smart environments Development of digital twin-driven smart home solutions Teaching: Postgraduate courses in Computer Vision/Perception at University of Rome Programming courses at ENSTA ParisTech Undergraduate Computer Graphics at University of Athens
Mohamed Daoudi serves as Full Professor of Computer Science at IMT Nord Europe and leads the Image group at CRIStAL Laboratory (UMR CNRS 9189). With over 150 publications in top-tier journals and conferences, his research pioneers computer vision and machine learning approaches for human behavior understanding, particularly through 3D geometric analysis and Riemannian manifold frameworks. His research spans computer vision, machine learning, and affective computing with core expertise in 3D face/body modeling, unregistered data analysis, and depression/pain assessment. Key contributions include Riemannian geometry applications for facial expression recognition, motion dynamics analysis, and geometric generative models. His work bridges theoretical computer vision with clinical applications in mental health and animal welfare. Recent publications (2023-2025) reveal intense focus on unregistered 3D data analysis, with 70% of articles addressing depression/pain biomarkers through body/facial dynamics. Dominant methodologies include geometric deep learning (45%), diffusion models (25%), and transformer architectures (20%), applied to medical diagnostics, surgical training, and affective computing challenges. Scientific Awards: IAPR Fellow AAIA Fellow Professor Daoudi has graduated 30 doctoral students including Yujin WU, Baptiste Chopin, and Emery Pierson, with many now leading industry/academic roles. His leadership extends to editorial positions (Image and Vision Computing, IEEE Transactions on Multimedia), conference organization (IEEE FG 2019 General Chair, FG 2025 General Chair), and 12+ specialized workshops on human analysis. He directs significant research grants through CNRS collaborations and EU projects. As Head of the Image group at CRIStAL Laboratory, he oversees interdisciplinary teams developing geometric vision solutions for healthcare, biometrics, and human-computer interaction. Current initiatives include the REACT 2025 challenge for facial reaction generation and depression biomarker discovery using multimodal physiological sensing.
Assoc. Prof. Filip Šroubek, Ph.D., DSc. is a Professor of Applied Mathematics at the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University , and an Associate Professor at the Faculty of Mathematics and Physics, Charles University . He serves as Deputy Head of the Department of Image Processing at the Czech Academy of Sciences. His career spans postdoctoral research at Instituto de Optica (CSIC, Madrid) and a Fulbright scholarship at University of California, Santa Cruz . Education: M.Sc. in Computer Science, Czech Technical University (1998) Ph.D. in Computer Science, Charles University (2003) D.Sc. (Habilitation), Czech Academy of Sciences (2014) Research Interests: Šroubek specializes in image restoration , blind deconvolution , and superresolution , with applications in biomedical imaging, forensic analysis, and mobile device optimization. His work on multi-object tracking and blur-invariant algorithms bridges theoretical and applied computer vision. Publication Trends: His recent articles focus on neural networks for image processing (2025), biomedical imaging (2024), and dynamic object tracking (2021-2023). Collaborations span neuroscience , materials science , and forensic engineering . Scientific Awards: Fulbright Visiting Scholarship (2010/2011) Honorable Mention at GCPR (2019) Outstanding Contribution Award (2013) Advising & Grants: Supervised projects include PIZZARO (forensic image analysis), 4D-STEM/PNBD (electron diffraction), and SONO (ultrasound technology). Grants emphasize interdisciplinary applications of image processing in medicine and engineering. Labs & Teams: Affiliated with the Department of Image Processing (UTIA, Czech Academy of Sciences) , he collaborates with teams in biomedical imaging, quantum dot characterization, and mobile technology optimization.
Iro Armeni is an Assistant Professor in the Civil and Environmental Engineering Department at Stanford University's School of Engineering. She leads the Gradient Spaces research group, focusing on the intersection of civil engineering, architecture, and machine perception to design and construct data-driven environments across physical and digital space. Her educational background is highly interdisciplinary: PhD in Civil and Environmental Engineering with Minor in Computer Science from Stanford University (2020), Postdoctoral Researcher at ETH Zurich (2023), MSc in Computer Science from Ionian University (2013), MEng in Architectural Engineering from University of Tokyo (2011), and Diploma in Architectural Engineering from National Technical University of Athens (2009). Before academia, she worked as an architect and consultant for both private and public sectors. Dr. Armeni's research focuses on developing quantitative and data-driven methods that learn from real-world visual data to generate, predict, and simulate new or renewed built environments with humans at the center. She is particularly interested in creating gradient spaces that blend 100% physical (real reality) to 100% digital (virtual reality) using Mixed Reality. Her work spans computer vision, 3D scene understanding, semantic mapping, and their applications in the built environment. Her recent publications demonstrate significant contributions across multiple venues including CVPR, ECCV, SIGGRAPH, and ISPRS Journal, with research themes centered around 3D scene understanding, appearance transfer, scene synthesis, SLAM in dynamic environments, and semantic mapping. Her work shows a consistent trajectory toward creating sustainable, inclusive, and adaptive built environments that support current and future physical and digital needs. She has received prestigious awards including the ETH Zurich Postdoctoral Fellowship, Google PhD Fellowship, and MEXT Scholarship. Her teaching includes graduate courses such as Designing for Gradient Spaces (CEE342), Computer Vision for the Built Environment (CEE247C), and AI Applications in AEC (CEE329), reflecting her interdisciplinary approach to integrating machine perception with civil engineering applications.
Zuria Bauer is a Lecturer in the Department of Computer Science at ETH Zürich. Her research focuses on advancing computer vision, robotics, and mixed reality technologies with applications in human-robot interaction, scene understanding, and assistive technologies. Key areas include monocular depth estimation, 3D scene reconstruction, and neural rendering techniques. Her work integrates theoretical advancements with practical implementations, such as enhancing robotic perception systems for real-world environments and developing intuitive mixed reality interfaces. Bauer has contributed to datasets like UASOL and frameworks like MaRINeR, which address challenges in novel view synthesis and object manipulation. Research trends in her articles emphasize cross-disciplinary approaches, combining deep learning with robotics to solve problems in healthcare accessibility (e.g., COMBAHO system) and environmental perception for autonomous systems. She explores both hardware-software co-design (e.g., low-cost wearable sensors) and algorithmic innovations (e.g., NeRF-based augmentation). While no formal awards are listed, her publications reflect sustained contributions to advancing perception technologies across dynamic scenes, robotic interaction, and assistive applications.
Cristina Losada Gutiérrez is a Professor at the Department of Electronics, Universidad de Alcalá, Spain. She leads research in the GEINTRA group, focusing on Electronic Engineering applied to Intelligent Spaces and Transport. Her work integrates computer vision, robotics, and deep learning for applications in smart surveillance, human activity analysis, and assistive technologies. She earned a PhD in 2010 with a thesis on 3D robot localization using static camera networks. Her research spans real-time action recognition, anomaly detection, and sensor fusion for healthcare and transportation systems. Notable projects include the GEMS Erasmus+ initiative (Ruby sensory module) and EU-funded EYEFUL systems for functional evaluation. Her recent publications emphasize edge computing frameworks for video analysis, weakly-supervised learning models, and robust object detection in dynamic environments. She actively contributes to educational robotics projects like Eurobot Spain and explores portable architectures for intelligent wheelchairs. Her lab develops multisensory systems for applications such as crowd safety (stampede detection) and railway obstacle detection, leveraging time-of-flight cameras and deep learning pipelines. She collaborates internationally on projects blending academic research with industrial and societal challenges.
Roberto Iglesias Rodríguez is an Associate Professor at the University of Santiago de Compostela, Spain, with a focus on robotics and machine learning. He holds a B.S. and Ph.D. in Physics from the same institution (1996, 2003). His work addresses lifelong robot learning, federated learning, and deployment of intelligent systems in heterogeneous environments. Current affiliation: University of Santiago de Compostela Academic rank: Associate Professor Education: B.S. and Ph.D. in Physics (1996, 2003) His research spans robotics, machine learning, and sensor fusion , emphasizing adaptive algorithms for non-IID data, concept drift, and real-time environmental interaction. Projects include service robots learning from humans, distributed control architectures, and federated learning strategies. Recent publications analyze continual learning , scene recognition , and human-robot collaboration . Key themes: robust navigation, multi-sensor systems, and explainable AI.
Dr. Fengwei An is an Associate Professor at the Shenzhen-Hong Kong Institute of Microelectronics , Southern University of Science and Technology (SUSTech). He earned his Ph.D. in Engineering from Hiroshima University (2013) , following a Master's (2010) and Bachelor's (2006) from Qingdao University of Science and Technology. Current Role : 2025-Present - Associate Dean and Associate Professor, SUSTech Shenzhen-Hong Kong Institute of Microelectronics Prior Academic Roles : 2017-2018 - Associate Professor, Hiroshima University; 2013-2017 - Assistant Professor, Hiroshima University Industry Experience : 2018-2019 - Chief Engineer, Panasonic Semiconductor Co., Ltd., Japan Research Interests focus on low-power edge artificial intelligence chip design for computer vision, including: Ultra-large-scale digital integrated circuit design System-on-Chip (SoC) integration Image processing and recognition Machine learning hardware Autonomous driving applications High-speed motion tracking systems Publications include over 80 top-tier journal/conference papers (e.g., TCAS-I/II, ESSCIRC, APCCAS) on AI accelerators, stereo vision processors, and sensor interfaces, with 15 recent articles highlighting advancements in stereo matching, video denoising, and reconfigurable coprocessors. Scientific Awards : 2023 - SUSTech Outstanding Teaching Award 2022 - APCCAS Best Paper Nomination 2022 - PrimeAsia Bronze Leaf Award 2020 - Wu Wenjun Artificial Intelligence Science and Technology Award (Second Prize) Patents : 9 Chinese and 3 Japanese inventions in AI chip design, stereo matching systems, and sensor interfaces.
Kazimierz Choroś is a Professor at the Department of Applied Informatics , Faculty of Information and Communication Technology , Wrocław University of Science and Technology. He held leadership roles as Deputy Director of the Institute of Informatics (2008-2014) and Deputy Dean of the Faculty of Computer Science and Management (2016-2020). Research interests: digital image/video processing, content-based video indexing, computer animations, multimedia systems, web systems analysis, and information systems design. Organizer and Chair of the International Conference on Multimedia & Network Information Systems (MISSI 2022) Chair of Special Session WebSys 2020 at ICCCI 2020 Other activities: Since 1993, member and former President (1993-2002) of the SAGE Association (Polish Graduates of French Grandes Ecoles). Since 1982, member of the Polish Numismatic Society, author of dozens of numismatic publications, and Editor-in-Chief of Wrocławskie Zapiski Numizmatyczne (2003-present). Contact: Email: kazimierz.choros@pwr.edu.pl Phone: +48-71.320.3799 Office: Building D2, Room 201/1 Address: Wrocław University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370 Wrocław, Poland
Alain Pagani is a Principal Researcher and Deputy Director of the Augmented Vision department at the German Research Center for Artificial Intelligence (DFKI) . He leads a team of 10 PhD students and researchers, focusing on Augmented Reality, Computer Vision, and Machine Learning. Research Interests include 3D Computer Vision, Image-based Scene Reconstruction, Object Detection and Tracking, and Extended Reality (AR/VR) applications. His work spans both industrial and academic projects, such as the EU initiatives dAIEDGE , CORTEX² , and FLUENTLY . Scientific Awards include a Google Research Award, Best Paper Award (INI-GraphicsNet 2007 Honorable Mentions), and Best Paper Award (INI-GraphicsNet 2008 Honorable Mentions). Projects like dAIEDGE (AI at the Edge) and CORTEX² (Collaborative XR) highlight his leadership in distributed AI and real-time extended reality systems. He has also coordinated EU projects such as LARA (Outdoor AR using Galileo) and Eyes of Things (Low-power Computer Vision).
Reham Mohamed Aburas is an Assistant Professor in the Department of Computer Science and Engineering at the American University of Sharjah (AUS) in Sharjah, UAE. Her academic career spans research and teaching in mobile computing security, with a focus on advancing secure and privacy-preserving technologies for modern devices across multiple platforms including smartphones and emerging virtual reality systems. Dr. Aburas earned her Ph.D. in Computer Science from Purdue University, where she worked with Professor Z. Berkay Celik at the PurSec Lab. Prior to that, she completed both her B.Sc. and M.Sc. degrees in Computer and Systems Engineering from Alexandria University in Egypt, establishing her technical foundation in systems engineering. Her primary research centers on the advancement of security, privacy, and usability of mobile computing technologies. In today's world, where modern devices are ubiquitous and technology is deeply integrated into various aspects of daily life, Dr. Aburas focuses on developing advanced systems that enrich user experiences while preserving security and privacy. Her work spans multiple domains including: Mobile security and privacy vulnerabilities Virtual and augmented reality security Biometric authentication systems User-centered security design Location privacy in mixed reality environments Arabic natural language processing Dr. Aburas's publication record demonstrates a strong trajectory from foundational work in mobile computing and indoor localization to cutting-edge research in virtual reality and mixed reality security. Her recent work (2023-2025) has focused on emerging threats in WebXR and VR environments, including UI attacks, speech extraction from sensors, and semantic location inference. She has published in top security venues including USENIX Security Symposium and NDSS, indicating the high impact and relevance of her research in the security community. Her earlier work (2014-2020) established expertise in mobile security, biometric authentication, and Arabic language processing through the Al-Bayan project. As an educator, Dr. Aburas has served as a course instructor at AUS, teaching subjects including COE 59412: Usable Security and Privacy and CMP 340: Design and Analysis of Algorithms. She has also served as a Teaching Assistant at Purdue University for courses including Great Issues in Computer Science, Data Mining, and Data Engineering in Python. At Alexandria University, she taught Probability Theory, Statistics, Data Mining, and Data Structures, demonstrating expertise across both theoretical computer science and practical security applications. Her research appears to be conducted in collaboration with the PurSec Lab at Purdue University, where she completed her Ph.D. Her work shows strong interdisciplinary connections between computer science, human-computer interaction, and security engineering, with particular attention to the practical usability aspects of security systems.
Michael Eagle is an Assistant Professor in the Information Sciences and Technology Department at George Mason University, and a founding member of the Center for Advancing Human-Machine Partnership (CAHMP). His work focuses on deriving insights from complex interaction data in intelligent tutors and video games, educational game design, and individualized student modeling in genetics education. He holds a PhD from North Carolina State University (2015) and completed a postdoctoral fellowship at Carnegie Mellon University's HCI Institute until 2018. Prior academic roles include data science positions at Blizzard Entertainment and Warner Bros. Interactive Entertainment. Research interests include educational data mining, AI-driven pedagogy, and measuring computational thinking through block-based programming environments. He has pioneered frameworks for hypothesis-driven learning analytics and game-based science education. His work bridges traditional computer science with innovative educational technologies, emphasizing real-time analytics and adaptive learning systems. Awards: NSF GRFP Honorable Mention, GAANN Fellowship, Freeman-ASIA Grant International Collaboration: Conducted NSF-funded research in Japan with University of Electro-Communications Labs/Teams: Co-leads CAHMP initiatives at George Mason Eagle's recent publications emphasize predictive modeling for learner interventions, real-time instructor dashboards, and the impact of AI-powered educational tools. His research demonstrates significant contributions to both theory and practical applications in edtech innovation.
