Benjamin Ditzel is a researcher at Hamburg University of Applied Sciences , currently serving as Officer for Curriculum Development and Impact Reflection in the KOMWEID project since 2021. His career spans multiple roles in academic quality management, including Quality Manager at the Faculty of Design, Media and Information (2018-2021) and Faculty of Engineering and Computer Science (2012-2014). Education: Dipl.-Ing. in Mechanical Engineering from Technical University of Berlin (2005), with a focus on Production Engineering and Quality Management Research Interests: He investigates quality management frameworks in higher education, emphasizing process-oriented approaches, organizational theory, and knowledge management. His work bridges academic governance with practical implementation challenges. Publications: Over 15 articles in journals like Zeitschrift für Hochschulentwicklung and Qualität in der Wissenschaft , analyzing topics such as Delphi studies on QM effectiveness, participatory curriculum design, and sensemaking in educational quality practices. Projects: Led the WirQung research project (2014-2016) on quality mechanisms and contributed to system accreditation initiatives across German and Austrian universities.
Dr. Mariel McKone Leonard serves as Interim Head of SOEP Innovation Sample at the German Socio-Economic Panel study Research Infrastructure. With over ten years of experience in mixed methods survey research, she specializes in working with small, rare, and vulnerable populations within sensitive research contexts. She maintains active research collaborations with the Universities of Maryland (UMD) and Munich (LMU), while being primarily affiliated with the German Institute for Economic Research (DIW). Her research expertise centers on innovative sampling methodologies, particularly respondent-driven sampling (RDS) techniques to improve representation of marginalized populations in survey research. Dr. Leonard has made significant contributions to developing data collection structures designed to measure and evaluate structural and individual racism. Her methodological work addresses critical challenges in creating more inclusive and representative social science data. Recent research outputs demonstrate her focus on advancing virtual and hybrid sampling approaches, with publications and conference presentations examining how to implement respondent-driven sampling to increase diversity in general population samples and integrate egocentric network data collection with traditional survey methods. Her work has important implications for improving survey methodology across social science disciplines. Dr. Leonard has presented her research at major international venues including the European Survey Research Association (ESRA 2025), the American Association for Public Opinion Research (AAPOR), and the General Online Research Conference (GOR 2024), establishing herself as a contributor to methodological innovation in survey research.
Claudio Fiorino is a researcher specializing in Radiation Oncology and Medical Imaging, with a focus on advanced radiotherapy techniques and radiomics. His work addresses cancer treatment optimization, particularly for prostate, breast, and cervical cancers, as well as applications in COVID-19 lung analysis. He collaborates with institutions globally, contributing to multi-institutional studies and emerging imaging technologies. Research Interests: Radiation Oncology: Precision radiotherapy, biochemical failure prediction, and fatigue risk assessment in prostate cancer. Radiomics: Development of imaging biomarkers for cancer staging/re-staging and response prediction. Medical Imaging: MRI and radioluminescence techniques for quality assurance and longitudinal studies. Publication Trends: Recent work emphasizes data-driven treatment planning (e.g., machine learning for breast irradiation), integrating radiomics into clinical workflows, and validating novel imaging methods for both oncological and non-oncological applications like COVID-19.
Albert Deuker is a Ph.D. student and researcher at the Institute of Professional Sport Education and Sport Qualifications at German Sport University Cologne, specializing in Training Pedagogy and Martial Research and Didactics and Methodology in Sports . His work focuses on applying Ecological Dynamics to soccer coaching through innovative Representative Learning Designs that bridge training and match scenarios. Current affiliation: Institute of Professional Sport Education and Sport Qualifications Email: a.deuker@dshs-koeln.de Research interests center on: Optimizing soccer training through pitch dimension scaling Studying collective spatial configurations in team sports Developing ecologically valid training designs Analyzing hysteresis effects in team behavior Implementing concave hull methods for movement analysis Advancing modern sports pedagogy His publications (2024-2025) demonstrate trends in team dynamics , training design , and spatial constraint manipulation . Collaborative projects include ITSR: Integrative Team Sport Research with colleagues like Tobias Vogt, Robert Rein, and Manuel Bassek. His work contributes to sustainable sports education practices under UN SDG frameworks.
German Institute for Adult Education – Leibniz Centre for Lifelong LearningGermany
Nathan Breznau is a researcher at the Deutsches Institut für Erwachsenenbildung (DIE) since 2024, affiliated with the Research Area of Organization and Program Planning. He previously held roles as Director of Studies at the University of Bremen's SOCIUM Centre (2018–2024), Research Associate at the University of Mannheim (2015–2018), and Researcher at the University of Nevada, Reno (2009–2013). His research focuses on Social inequality and welfare state dynamics Public opinion and policy feedback mechanisms Reproducibility in social science Immigration's impact on social policy Quantitative methods for cross-national analysis His recent work examines how work-injury policies vary globally, computational approaches to policy research, and the interplay between public health crises and social policy attitudes. The articles reflect trends in reproducibility, computational methods, and comparative social policy. Key keywords include Social Policy , Reproducibility , Public Opinion , and Labor Studies , with sub-fields spanning multiverse analysis , policy harmonization , and historical institutionalism . He participates in collaborative projects like the DFG-funded "The Role of Theory in Resolving the Reproducibility Crisis" and serves as an editor for PLOS One. His career emphasizes methodological transparency and cross-national survey analysis.
German Institute for Adult Education – Leibniz Centre for Lifelong LearningGermany
Mareike Kholin is a Researcher at the German Institute for Adult Education , specializing in the intersection of adult literacy, digital education, and human-technology interaction. Her career spans roles at the University of Bonn (2013–2019) and freelance lecturing at Fresenius University of Applied Sciences (2018–2019). She holds a doctorate in Psychology from the University of Bonn (2018) and complements her academic work with systemic coaching certifications. Education : PhD in Psychology (2018), Master of Science in Psychology (2013) from the University of Bonn. Her research focuses on digital tools for teachers , personality assessment in professional contexts, and social skills in performance evaluation . She leads projects like KANSAS, a search engine for authentic language-learning texts, and AI2TEACH, aiming to enhance digital literacy in adult education. Her recent publications emphasize personalized learning strategies, emotional intelligence, and the role of dark personality traits in leadership success. Kholin’s work has been recognized with the Award for Innovation in Adult Education . She actively develops open educational resources (OER) and evaluates digital tools to bridge standardization and differentiation in adult literacy instruction. Scientific Awards : Award for Innovation in Adult Education. She collaborates on systemic coaching initiatives and contributes to policy discussions on literacy and globalization’s impact on labor values. Her empirical studies explore how self- and peer-assessments predict workplace performance, integrating psychological frameworks with educational technology.
Harald Sick is a Researcher at the Institute of Journalism, Johannes Gutenberg University Mainz, affiliated with the Chair of Political Communication led by Prof. Dr. Marcus Maurer. Concurrently, he serves as a Research Associate for Network Analysis at the Institute for Democracy and Civil Society (IDZ), contributing to the project "Network against Online Hate and Disinformation." His work is supported by the DFG project "Identification and Classification of Radical and Extremist Actors on Telegram." He holds a degree in Political Science from Friedrich-Alexander University Erlangen-Nuremberg (2005–2011) and has pursued doctoral studies at Goethe University Frankfurt since 2015, focusing on lobbying influence in EU legislative processes. His research specializes in: Political communication dynamics, particularly right-wing extremism in digital spaces Computational methods including (discourse) network analysis, Graph Neural Networks, and LLMs Cross-platform strategies of extremist communities (e.g., Telegram, YouTube) Monetization of online hate speech and AI-driven radicalization His publications reveal a consistent focus on digital extremism, disinformation ecosystems, and computational social science. Recent works analyze generative AI in hate networks, meme-based radicalization, and economic incentives for extremist content. Trends indicate deep expertise in network statistics, crisis exploitation by extremists, and multi-platform discourse manipulation. He collaborates with interdisciplinary teams (e.g., Machine Against the Rage research collective) and maintains freelance roles in political data analysis. No advising activities or scientific awards are documented.
Patrick Fischer, M.Sc., is a Researcher and Doctoral Student at the Department of Health Sciences, Technische Hochschule Mittelhessen (THM), with a focus on biomedical engineering, machine learning, and respiratory disease research. His work spans nocturnal symptom monitoring in COPD and asthma patients, mobile health technology development, and AI-driven medical diagnostics. Key research areas include Biomedical Engineering applications for respiratory monitoring Machine Learning techniques in disease detection Mobile Health Technologies for home-based care Computational Biology in DNA methylation analysis Recent publications highlight graph database applications in nutrition apps, distributed computing for CNS tumor classification, and deep learning for cough detection and plagiocephaly monitoring. All articles demonstrate interdisciplinary approaches combining clinical needs with computational methods. His teaching responsibilities include supervising final thesis and project work. Contact: patrick.fischer@ges.thm.de .
Prof. Dr. Carsten Schulte is a Professor and Head of Didactics of Computer Science at the University of Paderborn, Germany. He serves as a Project Manager in Austria for Collaborative Research Center Transregio 318 and leads the Data Science in School Project (ProDaBi III) . His research focuses on integrating data science, AI, and computing education into K-12 curricula, emphasizing epistemic programming , data literacy , and explanatory models for technology understanding. His Google Scholar publications (2025–2024) reveal a strong emphasis on: Educational frameworks for data/AI literacy Epistemic programming pedagogy Interdisciplinary technology education Sociotechnical systems in schools Everyday AI explainability He teaches courses like Stage-Related Teaching Models , Sociotechnical Informatics Systems , and Software Internships for Teacher Training , with office hours managed through secretariat contact at Fürstenallee 11, Paderborn.
Marco Salvalaglio is an Emmy Noether Group Leader at Technische Universität Dresden, leading the Mesoscale Material Modeling & Simulations Group since March 2021 under the DFG Emmy Noether Programme. He holds an apl. Professorship in Computational Materials Science (awarded 2024) and is affiliated with the Institute of Scientific Computing, Dresden Center for Computational Materials Science (DCMS), and Institute for Scientific Computing (IWR). His educational background includes a Ph.D. in Materials Science (2016), M.Sc. in Physics (2012), and B.Sc. in Physics (2010), all from the University of Milano-Bicocca. He completed an Italian Habilitation as Associate Professor (2020) and Full Professor (2025) in Theoretical Condensed-Matter Physics. Salvalaglio's research centers on continuum and mesoscale modeling of material properties , with expertise in Phase-Field/Phase-Field Crystal (PFC) modeling, surface diffusion, dewetting, heteroepitaxy, defect dynamics, and pattern formation. His work bridges solid-state physics, computational materials science, and applied mathematics, focusing on developing coarse-grained approaches to explain experimental outcomes. Current projects include elasticity in atomistic descriptions, PFC modeling for surface diffusion, solid-state dewetting simulations, and machine learning integration. Analysis of his 15 most recent publications reveals a strong emphasis on hyperuniformity analysis , grain boundary dynamics , and multiscale modeling of crystalline materials. Key trends include topological characterization of nanostructures, disconnection-mediated microstructure evolution, and thermodynamic modeling of non-equilibrium systems. Awards: DFG Heinz Maier-Leibnitz Prize (2025) Richard von Mises Prize - GAMM (2024) Young Academy of Europe Fellowship (2023) MSMSE Emerging Leader Award (2023) TU-Dresden Young Investigator (2021) He mentors students through research projects in computational materials science and applied mathematics, with funding primarily from the DFG Emmy Noether Programme. His group actively recruits for Ph.D. positions focused on mesoscale modeling challenges. Salvalaglio maintains extensive international collaborations, evidenced by invited talks at 25+ global conferences (2021-2026) including TMS Annual Meeting, GAMM, and E-MRS. The Mesoscale Material Modeling & Simulations Group operates within TU Dresden's computational ecosystem, leveraging resources from DCMS and IWR to develop open modeling frameworks for material microstructure evolution.
Prof. Dr. Claus Hüsselmann is a Professor at the Technical University of Central Hesse (THM) in the Department of Business Administration and Economics . He leads the Project and Process Management (PPM) Laboratory and teaches courses in Project Management, Business Process Management, Multi-Project Management, Production Planning, and Digital Transformation. His research focuses on Lean Project Management, Agile methodologies, and waste reduction in projects. Research Interests : Business Process Management (BPM) Lean and Agile Project Portfolio Management Digital Transformation Production Planning and Control Systems Waste Reduction in Projects Hybrid Project Management Approaches Publications highlight trends in: Lean Project Management frameworks Agile-BPM integration Portfolio governance models Waste measurement tools (e.g., PMWI, PMW indicator) Hybrid methodologies for client/contractor dynamics Digital Transformation case studies Laboratory Leadership : As head of the PPM Laboratory , he bridges academic research with practical applications, offering consulting services to companies in project auditing, Lean PM implementation, and process optimization. His collaborations with GPM German Society for Project Management include editorial roles and jury membership for academic awards.
Kamila Misiejuk is a Postdoctoral Researcher at the Center of Advanced Technology for Assisted Learning and Predictive Analytics (CATALPA) within FernUniversität Hagen since October 2024. She previously served as a Senior Researcher and PhD Fellow at the Centre for the Science of Learning and Technology (SLATE) , University of Bergen (2017-2024), where she developed expertise in learning analytics and network modeling. Her research focuses on Interdisciplinary applications of Epistemic Network Analysis (ENA) and Transition Network Analysis (TNA) Designing data-driven educational tools for assessment and feedback Evaluating generative AI in academic writing and peer assessment Studying ethical implications of learning analytics dashboards Key trends in her 15 most recent publications (2024-2025) include Systematic reviews of generative AI and dashboard effectiveness Development of network analysis frameworks for collaborative learning Investigations into human-AI interaction dynamics and idiographic analytics Methodological tutorials in educational data visualization and R programming She contributes to professional networks as: Board Member , International Society for Quantitative Ethnography (ISQET, since 2021) Committee Chair , ISQET Resources Committee (2021-2023) Member , Society for Learning Analytics Research (SoLAR, since 2018)
Ifo Institute - Leibniz Institute for Economic Research at the University of MunichGermany
Helmut Rainer is a Professor of Economics (specializing in Social Policy and Labor Markets) at the Faculty of Economics, Ludwig-Maximilians-University Munich, and Director of the ifo Center for Labor and Demographic Economics . His research focuses on Labor Market Economics , Population Economics , and Family Economics . PhD in Economics (University of Essex, 2005) Research spans domestic violence measurement, migration policy impacts, gender economics, and political socialization Recent research trends: Analysis of climate activism's political spillovers, crisis-driven domestic violence quantification, immigrant integration through citizenship policies, and football hooliganism costs. His work employs behavioral economics , empirical policy evaluation , and big data analysis . Scientific Contributions: Developed novel domestic violence measurement methods via internet searches Pioneered research on citizenry's attitudes in reunified Germany Evaluated universal childcare effects on fertility Studied economic abuse mechanisms Analyzed parental leave policy impacts Key Projects: Bill & Melinda Gates Foundation's climate change impacts in Sub-Saharan Africa, DFG-funded research on custody arrangements, and Leibniz-funded violence against women economics studies.
Prof. Xiaoying Zhuang is a faculty member at the Institute of Photonics within the Faculty of Mathematics and Physics at Leibniz University Hannover . She leads research initiatives in the PhoenixD Cluster of Excellence and contributes to the QuantumFrontiers cluster. Her work spans computational mechanics, quantum optics, and machine learning applications in engineering. Research Focus : Computational modeling of material failure, flexoelectric structures, and seismic metamaterials Key Collaborations : Institute of Photonics, PhoenixD Cluster, QuantumFrontiers Recent publications highlight her contributions to data-driven engineering, phase-field fracture modeling, and quantum-enhanced material simulations. Her methodological innovations include variational damage models and machine learning-powered multiscale analysis frameworks.
Daniel Gritzner is a researcher at the Institute for Information Processing (Leibniz Universität Hannover) , specializing in computer vision, remote sensing, and scenario-based software engineering. His work bridges academic research with real-world applications in renewable energy, geospatial analysis, and automated code generation. Studied Computer Science (B.Sc. 2010, Diploma 2014) at the University of Mannheim Focus areas: Deep Learning, Semantic Segmentation, Remote Sensing, Formal Specifications His research integrates computer vision with remote sensing , applying techniques like transfer learning and domain adaptation to aerial/satellite imagery. Key projects include SegForestNet for segmentation and WindGISKI for wind turbine site selection. Recent publications highlight advancements in semantic segmentation, hyperspectral band optimization, and scenario-based controller synthesis. Collaborative work with Jörn Ostermann and others demonstrates interdisciplinary approaches across IEEE, Springer, and arXiv platforms. Technical contributions include the open-source SegForestNet framework, implementing binary space partitioning trees for geospatial analysis. This toolchain combines Python/Rust with PyTorch, emphasizing reproducibility and practical deployment in industrial/energy domains.
