PD Dr. Anne Schüler is a Researcher and Deputy Head of the Multiple Representations Lab at the Leibniz Institute for Knowledge Media (IWM) in Tübingen, Germany. She holds a PhD (summa cum laude) and habilitation in Psychology from Eberhard Karls University of Tübingen, with a focus on cognitive foundations of multimedia learning. Her work explores how multimedia principles enhance learning, particularly addressing validation processes, cross-modal integration, and the correction of misconceptions through instructional strategies like refutation videos. She has been an Equal Opportunities Officer at IWM since 2018. Her research spans cognitive psychology, educational technology, and instructional design, with a strong emphasis on empirical studies using eye-tracking and EEG. Key projects include investigating reactivation mechanisms during multimedia processing, the impact of digital distractions, and the design of adaptive multimedia systems. Her findings contribute to improving multimedia learning environments in education and professional contexts. Publications highlight themes such as text-picture integration dynamics, boundary conditions of multimedia effects, and the role of visual cues in comprehension. She has collaborated extensively with institutions like the University of Tübingen and international researchers, advancing theoretical frameworks for multimedia learning through experimental studies and data-driven insights.
Kacana Sipangule Khadjavi is a Research Fellow at the Kiel Institute for the World Economy and the Poverty Reduction Equity and Growth Network (PEGNet), specializing in development economics with a focus on large-scale land acquisitions in developing countries and their impacts on smallholder agriculture. Her research interests include FDI in land and smallholder agricultural production, the socio-economic drivers of land-use change, and the intersection between institutions, norms, traditions and household-decision making in developing countries. She primarily applies household survey data analysis and economic experiments in her work, with strong emphasis on promoting transparency and reproducibility in research as a Catalyst of the Berkeley Initiative for Transparency in the Social Sciences (BITSS). Her publication record shows consistent research output primarily focused on African contexts, with particular emphasis on Zambia and Tanzania. Recent work examines pandemic impacts on agricultural households, large-scale farming effects on smallholders, and social capital dynamics related to agricultural investments. Dr. Khadjavi has held visiting positions at the United Nations University World Institute for Development Economics (UNU-WIDER) and the Oxford Department of International Development, and was previously employed as a Research Fellow at GIGA German Institute for Global Area Studies. Her educational background includes a PhD in Economics from the University of Goettingen, a Master of Science Degree in Economics from the Free University of Amsterdam, and a Bachelor of Arts Degree in Development Studies and Economics from the University of Zambia.
Minhong Wang is a Professor at the Faculty of Education, University of Hong Kong, with additional affiliation at the University of Edinburgh's Usher Institute. With an extensive publication record spanning over two decades from 2005 to 2025, Wang has established themselves as a leading researcher in educational technology and learning sciences. Their work bridges the gap between computer science and education, developing innovative technology-enhanced learning environments that support complex skill development and knowledge construction. Wang's research interests focus on educational technology, learning analytics, computer-supported collaborative learning, and cognitive mapping approaches. Their work examines how technology can enhance problem-solving processes, support self-regulated learning, and improve educational outcomes across various contexts. Recent research has expanded into multimodal learning analytics, teacher professional development through technology, and the application of advanced computational methods to educational challenges. Wang's approach integrates theoretical frameworks with practical implementations, creating systems that transform how educators and learners interact with digital environments. Analysis of Wang's recent publications (2023-2025) reveals a strategic expansion of research scope while maintaining core educational technology focus. The work demonstrates increasing sophistication in learning analytics methodologies, with growing integration of computer vision techniques and advanced machine learning approaches. This reflects a trend toward more comprehensive multimodal analysis of learning processes, moving beyond traditional text-based interactions to incorporate visual, spatial, and behavioral data in educational contexts. The research maintains strong practical applications while advancing theoretical understanding of how technology mediates learning. Wang has collaborated extensively with researchers across multiple institutions globally, particularly in Hong Kong, mainland China, and international partners. Their work demonstrates consistent funding support through numerous research projects, though specific grant details aren't visible in the publication record. The collaborative nature of the work suggests leadership in research teams focused on developing and evaluating innovative educational technologies.
Yufei Li is a Professor at Xi'an Jiaotong University's School of Computer Science and Technology, Department of Computer Science. With an extensive publication record spanning from 2007 to 2025, Dr. Li has established himself as a prominent researcher in database systems, software engineering, and machine learning applications. His work demonstrates strong interdisciplinary connections between computer science and electrical engineering, particularly in power systems applications. Dr. Li's research interests span multiple domains of computer science and engineering. His primary focus is on database systems, where he has pioneered work in LLM-based database tuning systems like GPTuner. He also has significant contributions in software configuration and performance optimization, as evidenced by his CSAT framework. His research extends to computer vision applications for security screening and medical diagnostics, as well as electrical engineering applications in power systems and UAV control. This diverse portfolio demonstrates his ability to bridge theoretical computer science with practical engineering applications across multiple domains. Analysis of Dr. Li's recent publications (2023-2025) reveals a strong trend toward integrating large language models with traditional computer science domains. His work on GPTuner represents a significant advancement in applying LLMs to database tuning, while his research on QUITE demonstrates innovative approaches to query rewriting using LLM agents. There's also a clear pattern of applying advanced machine learning techniques to solve domain-specific problems across electrical engineering, medical diagnostics, and industrial quality control. The interdisciplinary nature of his work positions him at the forefront of AI integration across multiple engineering disciplines. Dr. Li has established a productive research group with numerous doctoral students and collaborators, particularly Jiale Lao, Yibo Wang, and Jianguo Wang who frequently appear as co-authors on his recent publications. His research has been consistently funded, as evidenced by the steady stream of publications across multiple high-impact venues including IEEE Access, Journal of Systems and Software, and CVPR. His work demonstrates strong industry relevance with applications in database management, software configuration, security screening, and power systems. Dr. Li leads a research team focused on database systems and AI integration, with strong connections to both computer science and electrical engineering domains. His group appears to specialize in applying cutting-edge machine learning techniques, particularly large language models, to solve longstanding problems in database management and software engineering. The team maintains active collaborations with researchers across multiple institutions, as evidenced by the diverse author lists on his publications.
Ali Zarezade is a researcher at the Max Planck Institute for Software Systems (MPI-SWS), focusing on interdisciplinary research spanning algorithms, machine learning, and social computing. His work integrates theoretical foundations with practical applications in cyber-physical systems, distributed networks, and human-centric AI. Key research areas include human-in-the-loop machine learning, optimal control strategies for social networks, and spatio-temporal modeling of social media activity. His methods often combine stochastic control theory, sparse regression techniques, and online algorithm design to address challenges in education technology, security, and information diffusion. Prior contributions involve developing algorithms like RedQueen and Cheshire for optimizing social network activity, probabilistic models for hyperspectral unmixing, and visual tracking systems resilient to occlusions. His research bridges computational theory with real-world systems, emphasizing scalable solutions for distributed and networked environments.
Eric Losang is a Researcher in the Department of Cartography and Visual Communication at the Leibniz Institute for Regional Geography in Leipzig. His work focuses on geovisualisations, historical cartography, and atlas design. He holds a geography degree from the University of Trier and has extensive experience in electronic media, database systems, and critical cartography. Education: 1990–1998: Studies in geography, political economics, and political science at the University of Trier 1987–1989: Studies in political science, history, and media science at the University of Trier Research Interests: His work bridges historical and modern cartography, exploring geopolitical imaginaries, critical approaches to mapmaking, and digital atlas development. Notable projects include the Digital Atlas of Geopolitical Imaginaries of Eastern Central Europe and the 'GLOWA-Elbe' environmental mapping initiative. Professional Roles: Chair of the ICA Commission on Atlases (since 2023) Head of the German Cartographic Society's Atlas Cartography Commission Labs/Initiatives: Leads the 'Upheavals and Transformations' Leibniz Lab and contributes to the ScienceCampus EEGA. His work emphasizes visual communication tools for population movement analysis (e.g., 'hin&weg' project).
Prof. Sen Cheng is a Professor at the Institute of Neuroinformatics (INI), part of the Faculty of Computer Science at Ruhr-Universität Bochum. His research focuses on computational neuroscience, particularly the neural mechanisms underlying learning, memory, and spatial navigation. He leads a lab investigating hippocampal dynamics, combining mathematical modeling with optogenetic and electrophysiological data analysis. Collaborations span neuroscientists in Germany and internationally. Research interests include hippocampal replay mechanisms, episodic memory functions, and the interplay between sensory inputs and neural networks. His work bridges computational models (e.g., spiking neural networks) with experimental data from rodents and humans. Recent projects explore deep reinforcement learning agents for spatial navigation and the role of grid cells in cognitive mapping. Publications span Neuron , Current Biology , and eLife , addressing topics like hippocampal network stabilizations, spatial coding efficiency, and cerebellar contributions to fear extinction. Teaching includes courses on computational neuroscience, artificial neural networks, and mathematical psychology. Lab activities involve interdisciplinary research through colloquia like Brains in Space and supervision of master’s and bachelor’s theses in areas like reinforcement learning algorithms and embodied associative networks. The INI’s mission drives his work, linking biological insights to artificial cognitive systems design.
Prof. Panu Poutvaara is a Professor of Economics at Ludwig-Maximilians-Universität München and Director of the ifo Center for Migration and Development Economics . His work focuses on International Migration , Public Finance , and Political Economy , with notable contributions to understanding migration patterns, electoral behavior, and social security systems. Doctor of Social Sciences (University of Helsinki, 2002) Licentiate of Social Sciences (University of Helsinki, 1999) Master of Social Sciences (University of Helsinki, 1997) His research explores migrant self-selection , refugee integration , and political economy of redistribution . Recent projects include analyzing Ukrainian refugee labor market integration and economic impacts of geopolitical risks . Articles highlight trends in migration economics , voter behavior , and labor market policy . Scientific awards include the 2010 Myrdal Prize and 2008 Musgrave Prize . He has served on editorial boards of European Journal of Political Economy and CESifo Economic Studies , and taught courses on Intergenerational Transfers and Public Economics at doctoral and master levels.
Ramesh Glückler is a Postdoctoral Researcher at the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research in Potsdam, Germany, and a visiting researcher at the Institute of Tibetan Plateau Research, Chinese Academy of Sciences. His work focuses on reconstructing long-term environmental and climatic changes, particularly boreal wildfire regimes using sedimentary proxies like charcoal and molecular biomarkers. He explores fire-vegetation interactions through ecological modeling and investigates human dimensions of fire dynamics. Education: PhD in Geography/Geoecology (University of Potsdam, 2024), with expertise in paleoenvironmental reconstruction and spatially explicit modeling. Research involves collaborations across multiple institutions, including field expeditions in Siberia and the Austrian Alps. Research Interests: Wildfire regimes, paleoclimatology, boreal ecosystems, permafrost-lake dynamics, and human-environment interactions. Utilizes interdisciplinary methods combining sediment coring, isotopic analysis, and computational modeling. Key Projects: Holocene fire reconstructions in Siberia, LAVESI-FIRE model development, and collaborations on permafrost thaw lake systems. Active in international conferences like PAGES and EGU, with 17+ presentations since 2020. Awards: Heinrich Award (Paleoclimate Dynamics), Short-term Fellowship from Chinese Academy of Sciences. Data & Outreach: Deposits data in PANGAEA and Zenodo. Engages in science communication through blogs and public talks, emphasizing wildfire impacts in Arctic regions.
Prof. Thies Pfeiffer holds a professorship in Computer Science with a specialization in Human-Machine Interaction at the University of Applied Sciences Emden/Leer. His work focuses on Mixed Reality technologies (AR/VR) applied to healthcare training, industrial assistance systems, and educational innovation. He leads the research group exploring immersive learning environments and has developed tools like TrainAR for procedural training. Key areas include: Eyetracking for interaction design XR accessibility standards Multi-user VR simulations for nursing training Virtual patient avatars in psychiatry education Research initiatives include the DiViFaG project for digital health training frameworks and the Mixality platform showcasing current projects. He serves on the COGAIN Association board, advancing assistive technology research. His work bridges human factors engineering with practical applications across healthcare, education, and industry.
Overview Prof. Iris Belle is a Professor and Vice Dean of Faculty A/Dean of Studies for Smart City Solutions (SCS) at the Stuttgart University of Applied Sciences. Her career includes roles as Founding Dean of the German-International University Cairo's Faculty of Architecture (2019–2022), Leading Consultant at Drees & Sommer (2016–2019), and Assistant Professor at Tongji University's College of Architecture and Urban Planning in Shanghai (2011–2015). She holds a PhD in Geography from Heidelberg University and completed postdoctoral research at ETH Zurich's Institute of Historic Buildings and Preservation (2007–2013). Education PhD in Geography, Ruprecht-Karls-University Heidelberg (2009) Postdoc at ETH Zurich's Institute of Historic Buildings and Preservation (2007–2013) Diploma in Architecture, Technical University of Karlsruhe (now KIT) Research Interests Belle's work focuses on Smart Urbanism , Sustainable Urban Development , and Smart City Solutions . She explores how digital technologies (e.g., BIM, blockchain) can transform construction practices and urban governance. Recent projects include analyzing Singapore's building stock sustainability, Tianjin's eco-city transition, and labor-intensive construction scenarios. Her research bridges architecture, urban planning, and environmental science to address global urban challenges. Grants & Collaborations Recipient of the Incubator Grant from Stadtmacher cn-d Platform (Robert Bosch Stiftung) for the Future of Living project (2017). Collaborations include the Future Cities Laboratory (Singapore-ETH Centre) and Tongji University's College of Architecture and Urban Planning. Affiliations Chamber of Architects Baden-Württemberg German University Association Friends of the HFT Stuttgart eV
Prof. Dr. Torben Kuhlenkasper is a Professor of Quantitative Methods in Economics at Pforzheim University's School of Business, leading the Quantitative Methods department. He holds a doctorate in Statistics and Econometrics from the University of Bielefeld (2011) and has extensive academic and professional experience across institutions like Goethe University Frankfurt and the Hamburg Institute of International Economics (HWWI). His research focuses on semi-parametric econometric methods applied to economic and business problems, including nonlinear economic interactions and policy analysis. Education: PhD in Statistics & Econometrics, Universität Bielefeld (2011) Diplom in Economics (2007) and Business Administration (2006), Universität Bielefeld Research Interests span Econometrics , Quantitative Methods , Regression Analysis , and Data Science . He develops advanced statistical techniques to analyze complex economic phenomena such as presidential popularity dynamics, fiscal policy impacts, and immigration patterns. His work has been published in journals like Journal of Applied Econometrics and Computers in Human Behavior . Notable Awards include teaching excellence awards from Pforzheim University (2016) and recognition for outstanding teaching in Goethe University's Master program (2013-2014). He has authored three influential textbooks on statistical methods using R. Academic Service includes editorial roles ( Review of Economics ), conference organization (Deutsche Statistische Gesellschaft), and media engagements (NDR Info Interview on presidential popularity). He also leads the interdisciplinary team at KuCADU , focusing on academic consulting and innovation in quantitative methods.
Armin Beverungen is Professor for the Sociology of Organisation and Economy at Leuphana University Lüneburg and an associated member of the Centre for Digital Cultures. His academic work spans sociology, organization studies, media studies, and science and technology studies, with a particular focus on the intersections between digital technologies and organizational forms. Dr. Beverungen received his PhD in critical management studies from the University of Leicester. His academic journey includes research and teaching positions at the University of the West of England, Leuphana University, and the University of Siegen. From September 2022 to August 2023, he was on leave at Leuphana and served as a visiting professor at the Institute for Media Studies at Ruhr-University Bochum. He also regularly teaches in the technologies section of the contextual studies program at the University of St. Gallen. His research interests center on digital (media) technologies and organization; algorithmic management, automation and artificial intelligence; and smart, logistical cities. He has made significant contributions to understanding the financialization of universities, corporate governance, business ethics, and the politics of labor. His work critically examines how digital platforms, particularly Amazon, reshape urban spaces, labor relations, and organizational forms. Beverungen has been instrumental in establishing the Centre for Digital Cultures at Leuphana over the past decade, which has expanded his research to engage more deeply with media studies and science and technology studies. Dr. Beverungen's recent publications reveal a consistent focus on the organizational implications of digital technologies, particularly examining Amazon's logistical operations and urban interventions. His work demonstrates interdisciplinary reach, connecting sociology, media studies, urban studies, and organizational theory. A significant portion of his research analyzes how algorithmic systems reshape labor, urban space, and organizational forms, with particular attention to the political dimensions of these transformations. Member of editorial collective of 'ephemera: theory & politics in organization' (10 years) Founding editor of 'spheres: Journal for Digital Cultures' Founding editor of 'Digital Cultures' book series Associate editor of 'Organization: the critical journal of organization, theory and society' At Leuphana, Dr. Beverungen serves as deputy director of the MA program in Cultural Studies: Culture and Organization, and is a member of the study commission for MA programs in the Faculty of Humanities and Social Sciences. He regularly supervises BA and MA theses and is available for PhD supervision. His current research is supported by two major projects: 'Automating the Logistical City: Space, Algorithms, Speculation' (Volkswagen Foundation) and 'Smartness as Wealth' (Volkswagen Foundation). Dr. Beverungen has been involved with the Digital Cultures Research Lab (2017-2022) and continues to contribute to digital culture studies at Leuphana University. His interdisciplinary approach bridges sociology, media studies, and organization theory, creating innovative frameworks for understanding contemporary digital transformations.
Achim Rettinger is a full professor at Trier University, leading the research group krAil (Knowledge Representation Learning). He specializes in machine learning, natural language understanding, and human-centered AI. His work focuses on expressive knowledge representations and their applications in semantic technologies. Education: Studied Computer Science at Universität Koblenz (Germany), University of Georgia (USA), and University of Alberta (Canada). PhD in machine learning at TU Munich/Siemens AG, followed by habilitation at KIT (2016). Served as interim professor at Karlsruhe Institute of Technology (2018/19). Research interests include knowledge graphs, cross-lingual semantic annotation, and data-driven analysis in political and medical domains. Notable contributions include the X-LiSA framework and work on semantic web technologies. Awards include best paper and challenge awards at ISWC and ESWC conferences. Leadership roles include senior PC member at ISWC, track chair at ESWC, and membership in AI for Good Foundation. Active in EU projects, DFG grants, and large-scale collaborative initiatives. Key projects: BreXearch (cross-lingual Brexit analysis), xLiMe System (semantic search), and medical decision support systems for liver surgery. Collaborates with interdisciplinary teams on cognition-guided surgery and data integration. Publications span top venues like ISWC, NeurIPS, ICLR, and CVPR, with a focus on semantic web, machine learning, and applied AI solutions.
Prof. Dr. Stefan Edlich is a Professor at the Beuth University of Applied Sciences Berlin, leading the Data Science Master program and the Data Science Lab. He holds a Dr. med. Ing. and has authored 13 books, including the world's first NoSQL book. His research focuses on NoSQL databases, Big Data systems, AI applications in health, industry, and education, and data quality. Edlich organizes conferences on Big Data, functional programming, and Clojure, and manages the NoSQL Archive. He has been part of the Berlin Big Data Center (BBDC) since 2014. His work spans over 60 publications, with recent contributions in AI-driven healthcare, blockchain, and distributed systems. He advises students and maintains strong industry ties with companies like Zalando, Amazon, and IBM. His teaching excellence has earned him the 'Top 25 Lecturer' award multiple times at Beuth. Edlich's collaborations include projects like the MOMO mobile app for machine learning and the BBC-DaaS open-data platform. Research interests include data science applications in biodiversity, HCI innovations, and education technology. He actively contributes to open-source projects like Clarango (Clojure driver for ArangoDB) and advocates for data literacy through the Stifterverband initiative.
