Luis Miguel Hernández Acosta serves as an Associate Professor in the Department of Telematics Engineering at the University of Las Palmas de Gran Canaria (ULPGC), affiliated with both the GIR IUMA: Information and Communications Systems research group and the IU of Applied Microelectronics. His academic work spans software engineering and telematics systems within the School of Engineering. His research interests focus on Software Engineering , Mobile Computing , and Computer Vision , with significant contributions to practical applications including web/mobile platforms for service management, computer vision for medical diagnostics, and communication systems. Current projects demonstrate strong industry alignment in restaurant management, transportation optimization, and telemedicine solutions. Analysis of recent publications reveals consistent expertise in full-stack development, real-time systems, and cross-platform frameworks, with increasing integration of machine learning techniques since 2022. Key thematic trends include Practical implementation of publish/subscribe architectures for real-time notifications Computer vision applications in medical diagnostics Optimization algorithms for transportation and service platforms Advising Activities: Supervised 28 bachelor/master theses (2021-2025) Specializes in guiding telecommunications and computer engineering students Projects span mobile development (65%), web platforms (25%), and AI applications (10%) Research Infrastructure: Works within the Department of Telematics Engineering's ecosystem, leveraging resources from both GIR IUMA and the Applied Microelectronics Institute for hardware-software integration projects.
Lauren Reid is a researcher, curator, and educator specializing in Social and Cultural Anthropology, with a focus on the Social Studies of Outer Space (SSOS), Indigenous cosmopolitics, and science and technology studies (STS). She holds a PhD from Freie Universität Berlin, where she is affiliated with the Institute for Social and Cultural Anthropology within the Department of Political and Social Sciences. Currently, she serves as a guest researcher at Leuphana University's Center of Methods, teaching qualitative research approaches, and continues her curatorial work as Co-Director of insitu collective. Reid completed her PhD in Social and Cultural Anthropology from Freie Universität Berlin in 2025, following a Bachelor of Visual Arts (Honours) from Sydney College of the Arts (2007) and a dual Bachelor of Arts (Visual)/Arts from Australian National University (2006). Her academic journey reflects a unique interdisciplinary path that bridges visual arts, anthropology, and curatorial practice. Research focuses on cosmic futures, particularly examining how different cultural frameworks interpret space exploration Specializes in Thai Buddhist perspectives on space and extraterrestrial life Investigates the intersection of scientific practices and religious beliefs in cosmological understanding Develops innovative arts-based research methodologies for anthropological inquiry Examines how colonial narratives shape contemporary space exploration discourse Her publications reveal a consistent trajectory exploring cosmic imaginaries through multiple lenses, particularly contrasting Western 'frontier' narratives with alternative cosmological frameworks. The most recent work demonstrates increasing sophistication in analyzing how religious frameworks (particularly Thai Buddhism) inform approaches to space exploration, moving beyond simple dichotomies between science and religion to explore more complex entanglements. Her research consistently challenges Eurocentric narratives of space exploration while developing new methodological approaches for studying cosmic engagement. Reid's teaching practice spans both academic and professional domains, with significant experience at Node Centre for Curatorial Studies (2012-2024) and Leuphana University (2024-2025), where she develops courses on visual culture, multimodal ethnography, and curatorial practice. Her exhibition work, particularly through insitu collective, demonstrates a commitment to creating immersive experiences that translate complex theoretical concepts into accessible public formats, with notable projects including 'Beyond the Final Frontier' (2019) on cosmic futures in Thailand and 'Corridor I: Onkalo' (2016) exploring nuclear waste repositories. Her curatorial practice forms a significant dimension of her scholarly contribution, with exhibitions developed as 'fictional characters' that create immersive environments exploring psychological states and conceptual frameworks. These projects demonstrate her innovative approach to knowledge production that bridges academic research and public engagement through visual and spatial storytelling.
Dr. Abdou Khouakhi is a Lecturer in Remote Sensing at the Cranfield Environment Centre, Cranfield University. He holds a PhD in coastal hazards and coastal vulnerability, with extensive postdoctoral experience at the IIHR-Hydroscience & Engineering at The University of Iowa, USA, and as a research associate at Loughborough University, UK. His academic journey reflects a strong commitment to understanding environmental challenges through advanced technological approaches. Dr. Khouakhi's educational background includes: PhD in coastal hazards and coastal vulnerability, focusing on satellite and aerial remote sensing data integration with spatial modeling for coastal erosion and flood risk assessment Postdoctoral research at IIHR-Hydroscience & Engineering, The University of Iowa, USA Research associate position at Loughborough University, UK, working on EPSRC-funded projects His research centers on understanding extreme climate hazards and their present and future impacts through systems-based approaches. Dr. Khouakhi integrates Earth observation, data science, AI, and climate model data to analyze how these hazards affect population, soil, agriculture, ecology, and broader environmental systems. His work spans coastal vulnerability, flood monitoring, climate extremes, and agricultural impacts, with a particular focus on the interconnectedness of these environmental challenges. He has developed expertise in applying machine learning techniques to environmental problems and has contributed significantly to the development of real-time monitoring systems using IoT technology. Dr. Khouakhi's recent publications demonstrate a strong trend toward interdisciplinary research that combines remote sensing with machine learning to address complex environmental challenges. His work spans climate extremes, flood monitoring, agricultural impacts, and water resource management, with increasing emphasis on explainable AI approaches and compound climate extremes. His research shows a clear progression from coastal hazard assessment to broader climate impact analysis, reflecting the evolving nature of environmental challenges in a changing climate. Dr. Khouakhi actively mentors MSc students, with recent supervision topics covering landscape-scale remote sensing for conservation, agricultural water management using remote sensing, EO-based approaches for irrigated area mapping, extreme weather impacts on crop production, and advanced SAR techniques for drought detection. He has secured funding from major research councils including EPSRC, GCRF, and NERC, demonstrating the significance and relevance of his research to national and international environmental challenges. As an educator, Dr. Khouakhi leads key modules including Applied Earth Observation, Advanced GIS, Real World Machine Learning, and Environmental Risks. He has also developed specialized short courses such as 'Earth Observation Data Science' and 'R for Hydrology' to address professional development needs in the environmental sector.
Ihsan Engin Bal is a Lecturer in Construction Safety & Earthquakes at the Hanze University of Applied Sciences , affiliated with the Research Centre for Built Environment – NoorderRuimte . With a background in Civil and Structural Engineering from Karadeniz Technical University (2000), his work bridges seismic risk mitigation, timber-masonry structural systems, and digitalization of construction processes. Education: BEng in Civil and Structural Engineering (1996-2000), Karadeniz Technical University. His research focuses on earthquake engineering , particularly unreinforced masonry (URM) walls, timber structural connections, and low-cost sensor applications for construction safety. Recent projects include Hysteresis (hybrid testing of timber buildings) and Trust in Timber (bio-based construction workforce development). He explores applying digital tools like automated crack detection and vibration monitoring to enhance structural resilience. Key themes in his 2024-2025 publications include seismic performance of URM walls, noise-resistant crack segmentation via machine learning, and climate-proof infrastructure. He collaborates extensively with researchers like E. Smyrou and O. Arslan. Professor Bal actively engages in public discourse, notably analyzing Turkey-Syria earthquake vulnerabilities and advocating for improved construction practices. His work spans practical experiments, computational modeling, and policy-oriented insights for disaster prevention.
Paul Hemeren is an Associate Professor of Informatics at the University of Skövde , specializing in biological motion perception and human-robot interaction. His research spans cognitive science, artificial intelligence, and transportation safety, with emphasis on understanding how humans perceive actions and intentions in dynamic environments. Academic Background : Ph.D. in Cognitive Science (Lund University, 2008), B.A. from Hope College (USA) Current Research : Focuses on action representation, driver-cyclist interaction modeling, and multimodal perception systems Applied Projects : Developing intelligent driver support systems (I2Connect) and predictive collision detection models Methodologies : Combines experimental psychology with machine learning and computational modeling Recent publications examine kinematic primitives in action similarity judgments, attentional synchrony in films, and data-driven collision prediction models. His work bridges theoretical cognitive science with practical implementations for traffic safety and robotic systems, particularly through collaborations with Swedish research foundations and European robotics initiatives. Professional affiliations include membership in the Cognitive Science Society and European Network for Artificial Cognitive Systems. Research has been funded by Swedish insurance research funds and EU Horizon programs.
Ana Maria Garcia Nolasco da Silva is an Adjunct Professor in the Department of Arts at the School of Education, Polytechnic Institute of Lisbon. Holding a Ph.D. in Aesthetics and Philosophy of Art from the University of Lisbon, she specializes in the cultural intersections between Africa and Portugal within art, design, and craftsmanship contexts. Her academic credentials include: Ph.D. in Aesthetics and Philosophy of Art, Faculty of Letters, University of Lisbon Master's in Aesthetics and Philosophy of Art, Faculty of Letters, University of Lisbon Bachelor's in Plastic Arts - Painting, Faculty of Fine Arts, University of Lisbon Her research centers on African-Portuguese cultural synergies with emphasis on Lusophone Macaronesian islands (Azores, Madeira, Cape Verde, São Tomé and Príncipe) and migration-driven cultural constellations in continental Portugal. She investigates how artisanal traditions, political gestures, and feminist perspectives manifest in contemporary artistic practices, particularly through collaborative projects and biennials in Lusophone Africa. Her work bridges visual anthropology, postcolonial theory, and sensory studies to examine haptic visuality and hybrid identities. Analysis of her 15 most recent publications reveals dominant trends in decolonial art practices, with recurring focus on São Tomé and Príncipe's cultural events, Catarina Branco's artisanal reinterpretations, and René Tavares' performance works. Her scholarship consistently explores how migration reshapes creative expression across the Lusophone Atlantic, emphasizing community-based art and feminist interventions in postcolonial contexts. No scientific awards were documented in the source material. While specific student supervision isn't listed, her academic leadership includes chairing the 2017 "Rhizomes" International Conference and co-editing conference proceedings. Her research is supported by institutional affiliations rather than externally documented grants, with active participation in international conferences across Portugal, Spain, Argentina, and Germany. She engages with collaborative networks through conference organization and cross-institutional projects, though dedicated labs or permanent research teams aren't specified in available materials.
Dr. Anna Syberfeldt is a Professor in Production Engineering at the Department of Engineering Science, University of Skövde. She leads the Virtual Production Development research group and serves as research director at the ASSAR Industrial Innovation Arena. With a background in computer science from De Montfort University and habilitation in automation engineering, her work bridges AI, robotics, and immersive technologies with industrial production systems. Professor in Production Technology Research Director at ASSAR Industrial Innovation Arena University of Skövde Affiliation Her research focuses on developing innovative industrial solutions through: Artificial Intelligence and Machine Learning Collaborative Robotics and Human-Robot Interaction Digital Twins and Simulation-Based Optimization Augmented/Virtual/Mixed Reality Applications Smart Manufacturing and Industry 4.0 Worker Well-Being and Productivity Optimization Recent publications demonstrate her leadership in simulation-based optimization, collaborative robotics, and mixed reality applications in manufacturing. Her work emphasizes creating ultra-flexible production systems through cyber-physical approaches while prioritizing environmental sustainability and human-centric design. Key trends in her research include: Unified frameworks for virtual commissioning Knowledge graph applications in production systems Multi-objective optimization balancing productivity and ergonomics Smart glasses evaluation for industrial operators Evolutionary algorithms for complex manufacturing problems Her projects demonstrate practical implementations of: MAXLabs distributed cyber-physical testbed ERAIVA posture identification software Virtual environments for human-robot collaboration testing Digital support functions for factory layout planning
Enrique Ruiz Zuniga serves as Associate Professor in Production Engineering at the University of Skövde's School of Engineering Science in Sweden, while simultaneously holding a JSPS research fellowship at Kyoto University's Systems Design Laboratory and collaborating with Japan Manned Space Systems Corporation (JAMSS). His career bridges academic research and industrial applications across Europe and Asia, focusing on optimizing complex manufacturing and logistics systems through advanced computational methods. University of Skövde, School of Engineering Science JSPS Research Fellow, Kyoto University Japan Manned Space Systems Corporation (JAMSS) collaborator Dr. Ruiz Zuniga's educational background includes a B.Eng. in industrial engineering from the University of Malaga, Spain, a BSc in automation engineering from the University of Skövde, Sweden, followed by an MSc in industrial informatics and a 2020 PhD in informatics from the University of Skövde, completed in partnership with Xylem Water Solutions Manufacturing. His doctoral research focused on facility layout design using simulation-based optimization methodologies. His primary research interests encompass the design, verification, and improvement of logistics, robotics, and complex production systems, with methodological expertise in Lean Production, Discrete-Event Simulation, System Dynamics, Simulation-Based Optimization, and the Functional Resonance Analysis Method. Dr. Ruiz Zuniga's work demonstrates a consistent focus on international collaboration and practical implementation of theoretical models in real-world industrial settings across healthcare and manufacturing sectors. Analysis of his publication record reveals an evolution from foundational work in facility layout design toward more recent explorations of AI integration, human-centered design, and resilient production systems. His research shows increasing sophistication in combining simulation approaches with functional analysis methods, with a growing emphasis on human factors and system resilience in complex production environments. REFUSE (2023-2026): Resource efficient use of reconfigurable machining systems Dynamic SALSA (2023-2024): AI scheduling for assembly and logistics systems Envisioned world problems (2021-2023): Functional approaches for system design Emergency Department Modeling (2012-2016): Healthcare production systems Dr. Ruiz Zuniga has coordinated international engineering programs in Industrial Engineering, Product Design Engineering, and Mechanical Engineering (all 60 credits), while teaching courses including Introduction to Lean Philosophy, Methods Engineering, Mechatronics/Electronics, and Production and Logistic Simulation. His work demonstrates a strong commitment to bridging theoretical research with practical industrial applications in production engineering through international collaboration and methodological innovation.
Dr. Sihao Sun is a Researcher in Robotics at the Cognitive Robotics Department , Delft University of Technology. He focuses on planning, estimation, and control of aerial robotic systems, with notable contributions to fault-tolerant control algorithms and perception systems for quadrotors under extreme conditions. PhD in Aerospace Engineering (2020), Delft University of Technology Postdoctoral Researcher at University of Twente (2022-2023) and University of Zurich (2020-2021) His research spans Aerial Robotics , Robotics Perception , and Incremental Nonlinear Control , with applications in Multi-robot Systems , Agile Flight Control , and Aerodynamic Modeling . His recent work explores uncertainty modeling for meta-adaptive control and collaborative aerial manipulation. His 15 most recent articles emphasize robustness in fault-tolerant quadrotor systems, sensor-driven control, and high-speed flight dynamics. He has received the Veni grant (Dutch Research Council, 2024) and a Best Paper Award (IEEE Robotics and Automation Letters, 2020). Current projects include Accurate Aerial Manipulation under Uncertainties and High Efficiency Air Cargo Design . Key students include Jack Zeng (MSc, Cum-Laude distinction) and Fang Nan (ETH Medal winner).
Yongluan Zhou is a Professor at the Department of Computer Science , University of Copenhagen , where he co-heads the Data Management Systems Lab (DMS Lab) and serves as Head of Studies for the MSc in Computer Science . His academic journey includes a PhD from the National University of Singapore (NUS) (2007), a postdoc at ETH Zürich (2007–2008), and prior roles as Associate Professor at University of Southern Denmark (SDU) (2008–2017). PhD in Computer Science, National University of Singapore (2002–2007) Postdoc, ETH Zürich (2007–2008) Zhou's research focuses on database systems and distributed systems , with recent emphasis on event-driven systems , scalable stream processing , and big graph analysis . His work bridges theoretical foundations and practical implementations, addressing challenges in data consistency, fault tolerance, and resource optimization in cloud and microservice environments. The trends in his 15 most recent publications (2025–2024) highlight advancements in asynchronous choreographies , blockchain consensus protocols , GPU-accelerated graph processing , and microservices data management . These works integrate formal methods with empirical validation, emphasizing scalability, security, and efficiency in distributed environments. He actively contributes to academic governance as a member of the DEBS Steering Committee (2024–), SSDBM Steering Committee (2022–), and the EDBT Association Executive Board (2020–).
Yen-Chia Hsu is an Assistant Professor at the Informatics Institute, University of Amsterdam, where they teach courses in Information Visualization and Data Science. Previously, they served as a Postdoctoral Researcher at the Department of Sustainable Design Engineering, Faculty of Industrial Design Engineering, TU Delft, and as a Project Scientist in the CREATE Lab at Carnegie Mellon University (CMU). Their academic journey reflects a unique interdisciplinary background bridging computer science and architectural design. Dr. Hsu earned their Ph.D. degree in Robotics in 2018 from the Robotics Institute at CMU, where they conducted research on using technology to empower local citizens and communities. Prior to that, they received their Master's degree in tangible interaction design in 2012 from the School of Architecture at CMU, where they studied and built prototypes of interactive robots and wearable devices. Before CMU, they earned a dual Bachelor's degree in both architecture and computer science in 2010 at National Cheng Kung University, Taiwan. Dr. Hsu is a computer scientist with an architectural design background whose research focuses on Community-Empowered Artificial Intelligence (AI) , where they co-design, implement, deploy, and evaluate interactive AI systems that empower communities, especially in addressing environmental and social issues. Their work spans both social and technical aspects of community engagement with technology. On the social side, they have proposed an alternative framework called Community Citizen Science (CCS) , which extends traditional citizen science methods to a hyper-local scale, emphasizing continued community engagement after technology interventions. On the technical side, they investigate human feedback in AI pipelines and algorithms that enable machine learning models to incorporate different types of human input. Dr. Hsu's scholarly output demonstrates a consistent focus on applying computer vision, machine learning, and data science to environmental monitoring and community empowerment. Their recent work shows an evolution from developing specific tools for pollution monitoring toward more comprehensive frameworks for community engagement with AI systems. A notable trend is the increasing emphasis on empathy-centered design and policy implications of community-driven data collection systems. Their research bridges the gap between technical innovation and social impact, particularly in the domains of air quality monitoring and environmental justice. Outstanding Student Academic Achievement (2005, 2006, 2007) from Department of Architecture, National Cheng Kung University, Taiwan Third Prize, National Country House Design Competition (2008) from Ministry of the Interior, Taiwan Best New Artist, The National Golden Award for Architecture (2009), Taiwan Webby People's Voice Award, Best Use of Video or Moving Image (2014) Best Paper Honorable Mention Award (Top 5%) at ACM CHI Conference (2017) Best Paper Honorable Mention Award (Top 2.5%) at ACM IUI Conference (2019) Prize for Community Collaboration, The Constellation Prize (2020) Dr. Hsu has been actively involved in numerous research projects that bridge academia and community action. Their work on the Smell Pittsburgh platform, which allows citizens to report pollution odors to regulators, has been particularly influential in environmental advocacy. They have collaborated with organizations including ACCAN, PennEnvironment, GASP, Sierra Club, ROCIS, Blue Lens, LLC, PennFuture, Clean Water Action, and Clean Air Council. Their research has received support from the Heinz Endowments and has been featured in TIME, Pittsburgh Post-Gazette, PC Magazine, and other media outlets. Dr. Hsu also maintains an active open-source presence, with several tools and datasets released to support community-driven environmental monitoring. Dr. Hsu leads projects that focus on developing tools for community engagement at scale, including COCTEAU, an empathy-based tool for decision-making, and Project RISE, which recognizes industrial smoke emissions. Their work connects with the Multimedia Analytics Lab Amsterdam, where they contribute to data science education and research. Their approach emphasizes co-creation with communities rather than top-down technology deployment, positioning them at the forefront of human-centered AI research with real-world social impact.
Dr. Mohamed Al-Hussein is a Professor and NSERC Industrial Research Chair in the Industrialization of Building Construction at the University of Alberta’s Department of Civil and Environmental Engineering. His work focuses on advancing modular and offsite construction technologies through automation, lean principles, and Building Information Modelling (BIM). PhD, Construction Engineering & Management, Concordia University (1999) MASc, Construction Engineering and Management, Concordia University (1995) MSc, Civil Engineering, University of Architecture & Civil Engineering, Bulgaria (1988) BSc, Civil Engineering, University of Architecture & Civil Engineering, Bulgaria (1983) Dr. Al-Hussein’s research spans five key domains: Modular Construction: Pioneering high-efficiency offsite building systems, including rapid assembly of student dorms and mid-rise residential buildings. BIM & Digitalization: Developing 3D/4D modeling frameworks, automated design systems, and digital twin applications for construction optimization. Environmental Sustainability: Quantifying CO2 emissions, exploring nano energy storage, and advancing solar PV integration in residential construction. Urban Planning: Specializing in age-restricted community design, municipal infrastructure maintenance, and housing affordability analysis related to paving standards. Construction Safety: Applying ergonomic risk assessment tools and virtual reality to enhance worker safety and reduce construction-related hazards. His 400+ peer-reviewed publications reflect cutting-edge applications of AI, deep learning, and simulation across construction processes. Recent work explores metaverse integration, blockchain collaboration tools, and advanced crane operation optimization using reinforcement learning. As Editor-in-Chief of the International Journal of Industrialized Construction , Dr. Al-Hussein remains a global authority in this field. He has developed industry-transforming technologies like the Quikmod-2 modular lift frame and PCL lift frame project , with real-world implementations ranging from Shell Scotford complex equipment replacement to CBC News and Forbes featured projects.
Dr. A. Yousefzadeh is an Assistant Professor in Edge AI at the University of Twente (joined February 2024), affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) within the Department of Computer Architecture Design and Test for Embedded Systems. He holds a Ph.D. in Neuromorphic Engineering from IMSE (Instituto de Microelectrónica de Sevilla), where his thesis focused on bio-inspired vision processing. His research specializes in neuromorphic computing systems, with emphasis on: Designing ultra-low-power AI processors and event-based vision systems Developing hardware accelerators for spiking neural networks (SNNs) Edge AI deployment for sensor-based applications Hardware-software co-design for energy-efficient computing His publication trends (2015-2025) reveal core foci on neuromorphic processor architectures (e.g., SENECA, NeuronFlow), event-based vision processing, hardware-aware neural network optimization, and 3D integration techniques. Recent work explores activation sparsification in transformers and hybrid analog-digital neuromorphic systems. Prior to academia, he contributed to industry neuromorphic projects: Architected the NeuronFlow processor at GrAI Matter Labs (acquired by Snap) Led SENECA processor development at imec's Hardware Efficient AI group He currently leads research on next-generation edge AI processors at UT's Embedded Systems lab.
Dr. John A Greenwood is a MRC Career Development Fellow at the Department of Experimental Psychology, University College London . His research focuses on the mechanisms of visual perception and clinical disorders of vision , particularly amblyopia. He leads the Eccentric Vision Lab ( eccentricvision.com ), which investigates crowding effects, spatial vision topologies, and cortical processing idiosyncrasies. Key Research Themes: Visual crowding, interocular suppression, orientation selectivity, and neural correlates of perception Methodologies: fMRI adaptation, psychophysical experiments, and computational modeling His work reveals that crowding is a regularization process altering object appearance, and that binocular treatments for amblyopia improve compliance without reducing suppression. He has published extensively in Scientific Reports , Journal of Vision , and Investigative Ophthalmology & Visual Science . Scientific Awards: MRC Career Development Fellow
Berkay Aydin is a faculty member at Georgia State University's College of Arts & Sciences, Department of Computer Science. He received his Ph.D. and M.S. in Computer Science from Georgia State University (2017, 2016) and a B.S. in Computer Engineering from Bilkent University (2012). As a senior member of the Data Mining Lab (DMLab), his research focuses on spatiotemporal data analysis, deep learning, and data integration pipelines for solar big data. B.S., Computer Engineering, Bilkent University, 2012 M.S., Computer Science, Georgia State University, 2016 Ph.D., Computer Science, Georgia State University, 2017 His research explores heterogeneous large-scale solar data processing through techniques like: Spatiotemporal frequent pattern mining Time series mining and indexing Deep learning for solar event analysis Frequent pattern mining in non-relational databases Data integration pipelines for solar datasets Computer vision for evolving region trajectories Publications demonstrate expertise in transforming solar big data through novel algorithms in spatiotemporal analysis and co-occurrence pattern detection.
