Valery Afanasiev is a Tenured Research Professor at the School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics (HSE MIEM) since 2012. His academic career spans over five decades, including roles at Moscow Institute of Electronics and Mathematics and part-time professorship at Moscow State University's Department of Physics since 2011. Doctor of Sciences in System Analysis, Management and Information Processing (1983) Candidate of Sciences (PhD) in Control Systems (1972) Master's Degree in Electronic Engineering (1966) His research focuses on optimal control and nonlinear systems , particularly through differential games and parametric optimization . Key contributions include viscosity solutions for Bellman-Isaacs equations and adaptive filtering algorithms for cosmic radiation parameters. Recent publications highlight his work on: Extended linearization methods for nonlinear systems Differential games with multiple pursuers and evaders Tracking problems under bounded disturbances Control of nonlinear systems with state-dependent parameters Scientific recognition includes: Best Teacher Award (2015) He supervises doctoral theses on control systems and has authored influential textbooks such as Mathematical Theory of Control Systems Design and Control of Uncertain Dynamic Objects .
Dr. Dié Wang is a Scientist at Brookhaven National Laboratory's Environmental Science and Technologies Department since 2020, with an adjunct professorship at Stony Brook University since 2024. She leads observational and modeling studies on convective cloud systems, aerosol impacts on cloud dynamics, and atmospheric radiative transfer. PhD in Environmental Science (Mention très honorable), Université Pierre et Marie Curie (2016) MSc and BSc in Meteorology and Atmospheric Science from Nanjing University of Information Science & Technology (2013 and 2010) Her research integrates advanced instrumentation, machine learning, and high-resolution modeling to investigate: Convective cloud lifecycle and detrainment processes Aerosol-cloud-precipitation interactions Climate system energy and water cycle dynamics Grid sensitivity in mesoscale convective system simulations Cloud tracking algorithm development (CoCoMET v1.0) Atmospheric radiation and microphysical parameterization Recent publications highlight her work on aerosol forcing in deep convection, sea-breeze dynamics, and machine learning frameworks for aerosol-cloud interactions. She has over 25 peer-reviewed articles, with a focus on DOE ARM facility collaborations and convective gray zone modeling. DOE Early Career Research Program funding (2021) BNL SPOTLIGHT Award (2021) CNES/French Airbus Scholarship for graduate studies (2013-2016) Top graduate at NUIST (2013) As ARM science translator and former instrument mentor for rain gauges/disdrometers, she bridges observational and modeling communities. Her work involves extensive field campaign participation (TRACER, EPCAPE) and leadership roles in ASR program working groups.
Lauri Lovén is a tenure-tracked Assistant Professor at the University of Oulu's Faculty of Information Technology and Electrical Engineering. As vice-director of the Center for Ubiquitous Computing (UBICOMP) and leader of the Future Computing Group (20+ researchers), he coordinates the Distributed Intelligence strategic research area within Finland's 6G Flagship program. Education: D.Sc.(Tech.) 2021, Docent (Edge Intelligence) 2025, University of Oulu Prior Affiliations: TU Wien (2022), ETH Zürich (2023) Research Focus: Specializing in edge intelligence and distributed AI, his work explores cognitive computing continuums across 6G networks, IoT systems, and industrial metaverse applications. Recent Trends: Recent publications reveal two key directions: 1) AI optimization for 6G wireless networks (handover management, semantic slicing), and 2) intelligent data management frameworks (data fabric, message brokers) for distributed systems. Industry Experience: Combines 20 years of software industry expertise with academic research, having served as founder, CTO, and advisor in AI startups.
Gokhan Serhat is a tenure-track Assistant Professor at the Department of Mechanical Engineering , KU Leuven, stationed at the Bruges Campus. He conducts research within the Mecha(tro)nic Systems Dynamics Group and the M-Group and maintains a guest-scientist affiliation with the Max Planck Institute for Intelligent Systems. Education: Ph.D. in Mechanical Engineering, Koç University, 2018 (Marie Curie Fellow) M.Sc. in Computational Mechanics, Technical University of Munich, 2013 B.Sc. in Mechanical Engineering, Middle East Technical University, 2011 Research interests span computational mechanics, numerical methods, design & topology optimization, structural dynamics, composite materials, fiber-path optimisation, functionally graded structures, and bio-mechanical/haptic modelling. His work integrates high-fidelity simulation, laminate-parameter techniques, and additive-manufacturing constraints to create lightweight, variable-stiffness composite structures and tactile/biomechanical devices. Recent articles (2022-2025) reveal a strong trajectory in composite optimisation (anisotropic topology, lamination parameters, manufacturability) alongside interdisciplinary forays into biomechanics & haptics (fingertip dynamics, tactile displays, skin simulation). The portfolio is evenly split between computational-method development and application-oriented studies in aerospace, automotive, and human-interaction domains. Scientific recognition: Marie Curie Early-Stage Research Fellow (doctoral training grant) Research funding & leadership: Promoter, Flemish project “Fiber path and topology optimization of 3D printed composites” (2023-2027) Promoter, FWO/Flemish project “Concurrent fiber path and topology optimization of 3D printed composites” (2022-2024) He teaches three courses at KU Leuven Bruges: Structural Dynamics , Aerospace Structures & Lightweight Design and Mechatronic Design , and is an active member of the Faculty Council and the Department Council.
George D Konidaris serves as Associate Professor of Computer Science at Brown University, where his research bridges artificial intelligence, machine learning, and robotics with emphasis on autonomous decision-making systems. His work focuses on developing algorithms that enable robots and AI agents to learn hierarchical structures, discover reusable skills, and operate effectively in complex environments. Education: 2010: PhD, University of Massachusetts, Amherst 2003: MS, University of Edinburgh 2001: BS, University of the Witwatersrand 2000: BS, University of the Witwatersrand His research spans reinforcement learning , robotic motion planning , and hierarchical abstraction , with significant contributions to skill discovery, temporal abstraction, and model-based methods. Current work integrates visuo-haptic perception for manipulation tasks and explores language-guided robotics using large language models. His approach emphasizes creating systems that learn compact world representations for efficient long-horizon planning in partially observable environments. Analysis of his 2025 publications reveals strong trends in model-based reinforcement learning with focus on memory mechanisms, uncertainty quantification, and hierarchical skill composition. Key themes include temporal abstraction for planning efficiency, visuo-haptic fusion for robotic manipulation, and language grounding for task specification. His work increasingly connects cognitive science concepts like theory of mind with AI capabilities. Teaching responsibilities include CSCI 1410 (Artificial Intelligence) and CSCI 2951X (Reintegrating AI), where he bridges theoretical foundations with practical robotics applications.
Prof. Dr. Alexander Ecker is Professor of Data Science at the Institute of Computer Science, University of Göttingen, and concurrently holds the prestigious Max Planck Fellow position at the Max Planck Institute for Dynamics and Self-Organization. Since 2020 he also serves on the Executive Board of the Campus Institute Data Science in Göttingen. He leads the Neural Data Science research group, comprising 14 PhD students and 2 postdoctoral researchers, focusing on the interface of machine learning and computational neuroscience. His educational background includes a Dr. rer. nat. in Neuroscience (2014) from the Graduate School of Neural and Behavioral Sciences/IMPRS, University of Tübingen, followed by post-doctoral and group-leader positions at the University of Tübingen and the Max Planck Institute for Biological Cybernetics. Research Interests Machine Learning & Deep Learning: developing novel algorithms for representation learning and generative modeling. Computational Neuroscience: large-scale data-driven modeling of visual cortical circuits. Visual Perception: bridging biological vision and computer vision via biologically inspired architectures. His work has produced a steady stream of influential publications (2019-2025) in leading journals such as Nature Communications , Nature , Nature Methods , PLOS Computational Biology , ICLR , NeurIPS , and CVPR . The publications trend toward integrating high-resolution neural recordings with state-of-the-art machine-learning models to uncover principles of sensory processing, neuron-type classification, and behavior. Scientific Awards & Honors Max Planck Fellow, Max Planck Institute for Dynamics and Self-Organization (ongoing) Executive Board Member, Campus Institute Data Science, Göttingen (since 2020) Teaching, Advising & Grants Regularly teaches advanced courses: “Deep Learning for Image Synthesis”, “Current Topics in Deep Learning”, and “Graph Machine Learning”. Supervises 14 current PhD students and 2 postdocs within the Neural Data Science Group. Offers numerous Bachelor’s and Master’s thesis projects, with topics ranging from neuronal morphology clustering to primate vocalization analysis. Leads or co-leads large collaborative consortia with labs in Göttingen, Tübingen, Baylor College of Medicine, and other institutions across the US and Germany. Labs & Teams The Neural Data Science Group operates at the Institute of Computer Science, University of Göttingen, and is tightly integrated with the Max Planck Institute for Dynamics and Self-Organization. The group maintains active collaborations with over a dozen partner laboratories, including groups led by Fabian Sinz, Andreas Tolias, Thomas Euler, Tim Gollisch, and Viola Priesemann, fostering an interdisciplinary environment that spans computer science, physics, biology, and psychology.
Nikunj Arunkumar Bhagat serves as an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur, with a joint appointment in the Department of Biological Sciences and Biosciences. His research focuses on neural engineering, rehabilitation technologies, and biomedical instrumentation. Dr. Bhagat's research interests include Neural & Bio-signal processing, Medical Instrumentation, Brain-machine interfaces, Functional Electrical Stimulation, and Rehabilitation Engineering. His work bridges electrical engineering with neuroscience and rehabilitation medicine, developing technologies to assist individuals with neurological impairments. His publication portfolio shows a strong focus on brain-machine interfaces, rehabilitation robotics, and neural decoding techniques. The research spans from fundamental neural signal processing to practical applications in stroke rehabilitation, tetraplegia assistance, and hand movement restoration. His most recent work (2023) continues to advance state-space control approaches for neuromuscular stimulation and object detection applications for hand rehabilitation. Dr. Bhagat has established collaborative research with prominent institutions and researchers in the field of neurorehabilitation and brain-computer interfaces, as evidenced by his publications in high-impact journals such as IEEE Transactions on Human-Machine Systems, NeuroImage: Clinical, and Frontiers in Neuroscience. His academic journey includes a Ph.D. in Electrical Engineering from the University of Houston (2017), an M.Tech in Electrical Engineering from IIT Bombay (2011), and a B.E. in Electronics Engineering from Sardar Patel College of Engineering, University of Mumbai (2007).
Prof. Dr. Didier Stricker is a leading academic in computer science, serving as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) and Professor at the University of Kaiserslautern-Landau (RPTU). His career spans over two decades, including leadership roles at Fraunhofer IGD and founding the Augmented Vision research unit at DFKI/RPTU, which now includes ~30 researchers. Education: Electrical Engineering (Technical University of Grenoble, Karlsruhe) PhD: Computer Vision-based Calibration and Tracking Methods for Augmented Reality (2002, TU Darmstadt) His research focuses on virtual and augmented reality , computer vision , human-computer interaction , and on-body sensor networks . He leads major EU/national projects like LUMINOUS (Language-Augmented XR) and SHARESPACE (Ethical Hybrid Shared Spaces), with industrial partnerships including Sony, Google, and John Deere. Recent publications emphasize 3D reconstruction , neural network optimization , and XR systems . Key trends include event camera processing , scene flow estimation , and multimodal AI for industrial applications . He holds patents in AR tracking and has received the 2006 Innovation Prize from the German Society of Computer Science. Scientific Awards : Innovation Prize (2006) Best Paper/Demonstration Awards at ISMAR, EUSIPCO, CVPR, and ICRA As a reviewer for journals and conferences in VR/AR and computer vision, he contributes to shaping research standards. His lab ( AG Augmented Vision ) combines academic and industrial collaborations to advance cognitive interfaces and extended reality systems.
Dr. Katharina Ulmschneider is a Senior Research Fellow and School of Archaeology Archivist at Worcester College, University of Oxford. She specializes in archaeological archives, early medieval archaeology of northwest Europe, and the interpretation of historic visual materials including lantern slides and glass plates. Associate Member of the Archives and Records Association Member of the Oxford Centre for Late Antiquity Member of the Oxford University Heritage Network Fellow of the Society of Antiquaries Her research explores the evolution of landscapes, settlement hierarchies, and material culture in Northern Europe, with particular focus on economic systems, coinage, and the integration of metal-detector finds into archaeological narratives. She leads interdisciplinary projects such as the HEIR (Historic Environment Image Resource) - an image database tracking global environmental changes through historic photographs - and the Jacobsthal Project , examining the work of German refugee archaeologist Paul Jacobsthal. Recent publications highlight her work in digital archiving, ceramic provenance studies, and public engagement. Funded by the Reva and David Logan Foundation, Fell Fund, and Citizen Science Alliance, her exhibitions include collaborations with institutions in China and Austria. Scientific Awards: Fellow of the Society of Antiquaries
Yoshihiro Banchi serves as an Assistant Professor (non-tenure-track) at the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University. His academic career spans human-computer interaction with specialization in virtual and mixed reality systems. Dr. Banchi is an active member of the Virtual Reality Society of Japan, Japanese Society for Artificial Intelligence, Japan Office Studies Association, and Japan Ergonomics Society, demonstrating his interdisciplinary approach to research. Dr. Banchi's research focuses on Human-Computer Interaction, Virtual Reality, Mixed Reality, and Human Factors and Ergonomics. His work investigates user experience in immersive environments, physiological responses to visual stimuli, and motion sickness mitigation strategies. He has developed innovative approaches using deep learning to predict user discomfort and optimize VR/MR experiences. His research bridges computer science, psychology, and engineering to solve practical challenges in immersive technology design. Analysis of Dr. Banchi's publication record reveals a consistent trajectory of interdisciplinary research with increasing emphasis on practical applications. His work spans fundamental studies of human perception in VR environments to applied sports data analytics. Recent publications show growing integration of deep learning techniques with physiological measurements for real-time user state estimation, particularly in automotive contexts and sports performance analysis. Dr. Banchi's scientific achievements have been recognized through multiple prestigious awards: Winner of the 2024 Sports Data Science Competition eSports Division 2025.01 Japan Statistical Society Sports Data Science Subcommittee Visualization of Players' Attack Intentions in Preemptive Attacks in "Puyo Puyo" 2023 Sports Data Science Competition Basketball Division Excellence Award 2023 Sports Data Science Competition Judo Division Grand Prize 2022 Sports Data Science Competition Judo Division Grand Prize 11th Sports Data Analysis Competition, Baseball Division, Grand Prize 10th Sports Data Analysis Competition, Gateball Division, Excellence Award As an educator, Dr. Banchi teaches courses including Human Factors and Ergonomics in Data Science across multiple Waseda University schools, Basic Experiments in Science and Engineering, Virtual Reality, and the Endowed Lecture by Sony Group. His research program includes multiple internally funded projects examining human state estimation, visual usability in XR, and ergonomic data augmentation technology. His work frequently involves industry collaboration, particularly with Sony Group, reflecting his commitment to translating academic research into practical applications. Dr. Banchi's research environment focuses on the intersection of human perception and immersive technologies, with particular attention to motion sickness mitigation, user experience optimization, and practical applications of VR/MR in sports analytics and automotive contexts. His team employs a multidisciplinary methodology combining physiological measurements, eye tracking, deep learning algorithms, and user-centered design principles to advance the field of immersive human-computer interaction.
Professor Mark Hansen is a distinguished academic at the University of the West of England (UWE Bristol), holding a professorship in the Department of Engineering, Design and Mathematics within the Faculty of Environment and Technology. He is a key member of the Centre for Machine Vision at the Bristol Robotics Laboratory, where his work bridges theoretical computer vision with practical applications across multiple industries. His research portfolio spans academic and commercial projects, with a strong emphasis on translating laboratory innovations into real-world solutions through close industry partnerships. Professor Hansen earned his academic credentials from prestigious institutions, completing a BSc(Hons) in Psychology and an MSc in Computer Science at the University of Bristol before earning his PhD at UWE in 2012 with a thesis titled "3D Face Recognition Using Photometric Stereo." His educational background in both psychology and computer science has uniquely positioned him to develop biometric systems that incorporate human perception principles. Professor Hansen's research interests center around computer vision and machine learning, with particular expertise in photometric stereo techniques for 3D acquisition. His work spans multiple domains including agricultural technology (agri-tech), livestock welfare monitoring, microplastic detection, and precision farming systems. He has pioneered applications of photometric stereo for face recognition, plant phenotyping, and animal biometrics, demonstrating exceptional versatility in applying core computer vision techniques to diverse problems. His research consistently emphasizes practical implementation, with numerous projects resulting in commercialized technologies that address real-world challenges in agriculture and environmental monitoring. Analysis of Professor Hansen's recent publications reveals a strategic expansion of his core expertise in photometric stereo and 3D vision into increasingly diverse application domains. While maintaining his foundational work in biometrics and face recognition, he has successfully transitioned these techniques to agricultural contexts (pig and cow identification), environmental monitoring (microplastic detection), and sustainable food production systems (aquaponics optimization). His publication pattern shows a clear progression from fundamental computer vision research to applied interdisciplinary work addressing global challenges in food security, environmental sustainability, and animal welfare. Highly commended prize for innovation at the National Potato Industry Awards for the Harvesteye system Associate Editor for Elsevier's Computers and Electronics in Agriculture Featured on BBC Click for 3D Handprint Recognition research Featured on Netflix's "Connected" S1Ep1 for Pig Face Recognition work Professor Hansen has supervised six PhD students to completion with projects including "3D video based detection of early lameness in dairy cattle" and "3D plant phenotyping system using photometric stereo," and currently supervises seven additional PhD students through UWE, the Farscope CDT and SWBio schemes. His research is supported by substantial grant funding from diverse sources including InnovateUK, BBSRC, AHRC, EPSRC, JPIAMR, and international collaborations with institutions such as Imperial College, Notre Dame University, Bristol University, Manchester University, SRUC, and others. Current major projects include Intellipig (pig health monitoring), Mealworm protein production automation, FARM interventions to Control Antimicrobial Resistance, Pig ID tracking systems, and microplastic monitoring in home environments. Professor Hansen leads research within the Centre for Machine Vision at the Bristol Robotics Laboratory, a world-class facility that fosters interdisciplinary collaboration between computer scientists, engineers, and domain experts from agriculture, environmental science, and healthcare. His team includes three dedicated research staff working on 3D Face Recognition, Photometric Stereo, 3D acquisition technologies, reflectance mapping, and agri-technology applications. The collaborative nature of his work is evident in the extensive network of academic and industry partners spanning multiple continents, reflecting the practical impact and interdisciplinary relevance of his research.
James Blake is a Research Fellow at the University of Warwick, UK, specializing in optical imaging of satellites and space debris. His research focuses on developing computational methods for satellite tracking and orbit determination using observational data. Dr. Blake's primary research interests include optical imaging , satellite tracking , space debris monitoring , and orbit determination . His work combines astrodynamics with statistical methods to improve accuracy in predicting satellite positions and tracking space objects. His technical expertise is evident in his GitHub repositories, which include computational tools for satellite observation and orbit analysis. Dr. Blake has developed a TLE-based MCMC fitter, tools for identifying visible satellites, and algorithms for angles-only orbit determination. Dr. Blake maintains professional communication through his university email address J.Blake@warwick.ac.uk and is actively engaged in developing computational methods for space situational awareness.
Dr. Moriba Jah is a Professor of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin, where he holds the Mrs. Pearlie Dashiell Henderson Centennial Fellowship in Engineering. He serves as Director of the Jah Decision Intelligence Group (JDIG) within the Oden Institute for Computational Engineering and Sciences, and as Lead for the Space Security and Safety Program at the Robert Strauss Center for International Security and Law. Dr. Jah is also a member of the ICES Core Faculty and a Distinguished Scholar at the Robert Strauss Center. Dr. Jah's research focuses on computational astronautics and space situational awareness. His Jah Decision Intelligence Group works on: Non-gravitational Astrodynamics and Multi-body Orbital Dynamical Systems Modeling Multi-source Information Fusion and Multi-sensor/target Tracking Artificial Intelligence, Machine Learning, and Semantic Reasoning applications for space domain awareness Space Object Taxonomies, Classification, and "Biometric" Identification Methods Space Traffic and Debris Modeling, including Space Object Aging Effects Development of ASTRIAGraph, an RDF-based Knowledge Graph for Space Traffic monitoring Dr. Jah maintains an active publication record with numerous contributions to the field of space situational awareness and astrodynamics. His work bridges computer science, aerospace engineering, and international space policy, addressing critical challenges in space sustainability. Dr. Jah has received numerous honors and recognitions: Fellow of TED Fellow of American Institute of Aeronautics and Astronautics (AIAA) Fellow of American Astronautical Society (AAS) Fellow of International Association for the Advancement of Space Safety (IAASS) Fellow of Royal Astronomical Society (RAS) Fellow of Air Force Research Laboratory (AFRL) Elected Academician of the International Academy of Astronautics (IAA) Mrs. Pearlie Dashiell Henderson Centennial Fellowship in Engineering Dr. Jah has secured significant funding for his research, which has enabled him to establish the Jah Decision Intelligence Group and develop the Space Object Situation Room visualization laboratory. He mentors students and young professionals, with some receiving prestigious scholarships like the Secure World Foundation IAC Young Professionals Scholarship. Dr. Jah leads the Jah Decision Intelligence Group (JDIG), which is developing ASTRIAGraph - the first RDF-based Knowledge Graph for Space Traffic monitoring. His group is establishing a state-of-the-art visualization laboratory called the Space Object Situation Room to better understand relationships between objects in space and support decision-making processes for space traffic management.
Peter Lum is a Professor of Biomedical Engineering at The Catholic University of America, where he serves as Chair of the Biomedical Engineering department. He also directs the Center for Applied Biomechanics and Rehabilitation Research at MedStar National Rehabilitation Hospital and holds a position as Research Health Scientist at the Washington DC Veterans Affairs Medical Center. Dr. Lum's research focuses on rehabilitation robotics, human motor control, and neurorehabilitation. His work includes: Developing robotic devices for rehabilitation of upper extremity function after neurological injury Studying motor learning and performance limitations in amputee populations Advancing telerehabilitation technologies Creating innovative interventions like the MIME robotic system and HEXORR (Hand EXOskeleton Rehabilitation Robot) Dr. Lum's publication record shows a strong focus on robotic rehabilitation for stroke patients and amputees. His work spans from fundamental motor control studies to clinical trials of robotic interventions. He has published extensively on upper limb rehabilitation, exoskeleton development, and the neural mechanisms underlying motor recovery after neurological injury, with his papers cited over 7,000 times. His scientific achievements include: Over $18 million in external grant funding as principal investigator or co-investigator Professor Robert Meister Distinguished Faculty Fellowship (2020) Pioneering the first controlled study demonstrating advantages of robotic arm therapy compared to conventional therapy Leadership of the Rehabilitation Engineering Research Center established in 2018 with a five-year DHHS grant As an advisor, Dr. Lum has mentored 8 PhD students to completion and currently advises 3 more PhD students. His research program bridges engineering principles with clinical rehabilitation needs, translating laboratory discoveries into practical applications that improve movement function for individuals with neurological injuries.
Noga Collins-Kreiner is a distinguished Professor in the Department of Geography and Environmental Studies at the University of Haifa, Israel. She holds leadership positions as Head of the Haifa and Galilee Research Institute and Vice-President of the Israeli Geographical Association (IGA), positioning her at the forefront of geographical research in Israel. With over two decades of scholarly contributions, her academic profile represents significant expertise in tourism geography and cultural studies. Professor Collins-Kreiner's research focuses primarily on pilgrimage studies, with special attention to Jewish holy sites in Israel, religious tourism, and the intersection of tourism with archaeology. Her work spans multiple dimensions of tourism studies including dark tourism, souvenir studies, cultural tourism in the digital age, and volunteer tourism. She has developed influential classification systems for Jewish pilgrimage sites and examined how contemporary tourism phenomena interact with sacred spaces and heritage conservation. Her publication record from 1999-2023 reveals consistent scholarly output with evolving research interests that now include examining the impact of global events like the Covid-19 pandemic on religious tourism. Her most recent work explores volunteer tourism motivations and the altruistic dimensions of this growing tourism segment in Israel. Professor Collins-Kreiner employs methodologically diverse approaches including field observation, structured questionnaires, in-depth interviews, and participant observation. Her research on Dharamsala tourism involved extensive fieldwork with Western tourists, while her souvenir studies combined quantitative and qualitative methods to track how objects gain memorial significance over time. Her conceptual contributions include examining the relationship between dark tourism and pilgrimage, proposing refined terminology for tourism phenomena, and highlighting the shift from 'product' to 'experience' in contemporary tourism development. Her work on religious tourism and archaeology identifies critical conflicts between these fields and suggests pathways for more integrated planning that considers archaeological, religious, political, and tourism needs. Through her leadership roles and scholarly contributions, Professor Collins-Kreiner has established herself as a significant voice in geographical studies of tourism, particularly regarding the complex interplay between sacred spaces, heritage, and contemporary tourism practices.
