Thorsten Joachims is a Professor at Cornell University with a focus on machine learning, recommendation systems, and algorithmic fairness. His work spans conferences like ICML, NeurIPS, KDD, and SIGIR, emphasizing counterfactual learning, contextual bandits, and ethical AI. Key Research Themes: Fairness in rankings, reinforcement learning, position bias estimation, and NLP applications to recommendation systems. Recent Publications: 2025 work on policy decomposition for contextual bandits, 2024 studies on fairness under uncertainty, and 2023 papers on LLM steerability and bias mitigation. Awards: Recipient of the ACM SIGKDD 2020 Innovation Award . Collaborators: Regularly works with Adith Swaminathan, Tobias Schnabel, Yuta Saito, Ashudeep Singh, and Yi Su.
Prof. Dr. Marcel Prokopczuk is a full Professor of Finance and Commodity Markets at Leibniz University Hannover, serving as Dean of the Faculty of Economics and Management since 2024. He holds a Ph.D. from the University of Mannheim and is a CFA Charterholder. His research focuses on commodity markets, capital market dynamics, derivatives, risk management, and household financial decisions. Affiliations: Institute of Finance and Commodity Markets, Leibniz Research Centre Energy 2050, Hannover Center of Finance and Insurance (HCFI). Roles: Editor of the Journal of Commodity Markets , Associate Editor of the Journal of Banking and Finance , and Board Member of CEMA. Research Interests: Commodity markets, derivatives pricing, energy finance, risk management, and the impact of historical factors on financial development. He has published extensively in top journals like Review of Economic Studies and Journal of Banking and Finance . Awards: Includes the Deutsche Bundesbank Prize (2024), FIRN Annual Conference Award (2017), and Best Teaching Award (2015). Grants & Advisory: Member of the German Business Foundation and involved in energy policy initiatives. His work bridges academic research with practical applications in financial markets and commodity pricing.
PD Dr. Marco Dohle is a Senior Lecturer at the Department of Communication and Media Studies within the Faculty of Philosophy and Social Sciences at Heinrich Heine University Düsseldorf . Since 2010, he has been a staff member, completing his Habilitation in 2015. He has held substitute professorships at Johannes Gutenberg University Mainz, TU Dortmund University, and Heinrich Heine University Düsseldorf. Research Interests: Political Online Communication, Media Influence Perception, Political Consumerism, Migration and Integration Media Coverage, Sports Communication Projects: Directed DFG-funded subprojects on political online influence consequences (2011–2018), BMBF-funded migration media analysis (2017–2020), and a citizen science project on everyday political consumerism (2024–present). Education Media Management with minor in Psychology, Institute for Journalism and Communication Research, Hanover University of Music and Drama Guest semester at Örebro University, Sweden Recent Publications focus on fake news , political consumerism , media trust , and migration reporting , with interdisciplinary ties to political psychology , digital sociology , and media ethics . His work spans empirical studies on social media dynamics , audience polarization , and media's role in democratic processes . Collaborations include partnerships with Gerhard Vowe , Ole Kelm , and institutions like DGPuK and ECREA . He actively contributes to scientific conferences and editorial work in communication journals.
Prof. Dr. Claudia Bünte is a full-time Professor of Business Administration with a focus on Digital Marketing at the Berlin School of Management, SRH Berlin University of Applied Sciences. Since 2016, she has served as a Managing Partner at Kaiserscholle GmbH, Centre of Marketing Excellence. Her research prioritizes artificial intelligence applications in marketing, brand strategy, and ethical AI frameworks. Doctorate (Dr. phil.) in Marketing, University of Münster (2005) Diploma in Social and Business Communication, University of the Arts Berlin (2000) Her academic work investigates AI-driven marketing transformation, including predictive analytics, algorithmic bias mitigation, and digital brand management. Publications span AI ethics, B2B automation, and cross-industry technology adoption. She has delivered keynote speeches at institutions like the Art Directors Club Germany and AI for Business Zurich. Recent publications highlight trends in AI ecosystems, marketing automation, and ethical considerations across business sectors. Awards include being a publicly appointed marketing expert and Vice Marketing Head 2020 by One-to-One journal. Publicly appointed and sworn marketing expert (2020–present) Vice Marketing Head, One-to-One Trade Journal (2020) As a consultant and speaker, she bridges academic research and industry practice, contributing to German business publications like Horizont and FAZ Magazin. Her work emphasizes practical implementation of AI in marketing strategy and operations.
Dana Mahr is a Researcher at the Karlsruhe Institute of Technology (KIT) within the Institute for Technology Assessment and Systems Analysis (ITAS) . Her work focuses on Technology Assessment , Science and Technology Studies , and Citizen Science , with particular interests in Epistemic Diversity , Digital Health Research , and the Sociopolitical dimensions of biomedical technologies . Key research areas: Participatory research, gender in science, public trust in technology, and science communication in digital contexts Current projects: Inspiring and Anchoring Trust in Science (IANUS), Moral economies of emerging technologies, and the role of experiential knowledge in biomedical research Teaching: Has designed courses on topics like "Big Data in Medicine" and "Citizen Science" at institutions including Université de Genève and University of Lübeck Her recent publications address issues such as digital patient twins , data diaries in health platforms , and the politics of gender and reproduction . She leads discussions on disinformation, public engagement, and the ethical implications of technology in healthcare. Mahr's work emphasizes the intersection of social theory , scientific governance , and democratic participation in shaping technological futures. Notable collaborations include research with European Citizen Science Association (ECSA) and contributions to debates on transgender rights and digital health equity . Her methodological approach combines historical analysis with participatory frameworks to challenge epistemic hierarchies in scientific practice.
Sebastian Köhler is an Associate Professor of Philosophy at the Frankfurt School of Finance & Management. He teaches in the BSc in Management, Philosophy & Economics, BSc in Computational Business Analytics, and the Master of Applied Data Science. He previously served as a Wissenschaftlicher Mitarbeiter at Universität Duisburg-Essen and a Lecturer at Princeton University. His research focuses on meta-ethical questions surrounding normativity, the philosophies of Mind and Language, and the ethics of emerging information technologies. University of Edinburgh (PhD) University of Bielefeld London School of Economics University of Cambridge Köhler’s research bridges philosophical theory with practical applications in data science and AI ethics. His work on conceptual engineering addresses the challenges of defining and implementing ethical frameworks in technological contexts, particularly in autonomous systems and machine learning. Recent publications explore expressivist accounts of moral disagreement, the functional role of normative concepts, and the ethical implications of robot moral status. His scholarly contributions span leading journals such as The Journal of Philosophy, Ethics, Australasian Journal of Philosophy, Philosophical Studies, The Philosophical Quarterly, Erkenntnis, and Ratio. While no explicit scientific awards are documented, his interdisciplinary research has shaped discourse on responsible AI and the intersection of ethics and computational analytics.
Prof. Dr. Kathleen Stürmer is a faculty member at the University of Tübingen, affiliated with the Tübingen School of Education (TüSE) and the Hector Institute for Empirical Educational Research . As Deputy Director of TüSE for Internationalization since 2021, she leads initiatives to enhance global collaboration in teacher education. Research Focus: Teacher professional vision, simulation-based learning environments, diagnostic competence development, and technology integration in classrooms. Methodologies: Eye-tracking studies, meta-analytic reviews, and longitudinal analyses of teacher training efficacy. Key Projects: Observer (video-based diagnostic tool), Di-MaL (simulation framework for pedagogical diagnostics), and quality initiatives in digital distance teaching during the pandemic. Her recent publications highlight trends in educational technology (AI, tablets), teacher cognition (professional vision, attention processes), and structural innovations in teacher education programs. She actively develops standardized instruments for measuring pedagogical expertise and explores the impact of individual and contextual factors on instructional quality. Labs & Teams: She collaborates with the Hector Institute for Empirical Educational Research and leads internationalization efforts at TüSE, focusing on interdisciplinary frameworks for diagnostic competence across professions like teaching and medicine.
Dr. Theresa Züger is an interdisciplinary researcher leading the AI & Society Lab at the Alexander von Humboldt Institute for Internet and Society (HIIG). She investigates how AI systems can be designed to serve the common good, focusing on initiatives that promote sustainability, strengthen social inclusion, and enable technology reuse through open systems. Her work addresses societal challenges associated with artificial intelligence at political, social, and cultural levels, contributing to accurate assessment of AI's societal implications. Züger received her Ph.D. in Media Studies from Humboldt University in Berlin in 2017 with her dissertation 'Reload Disobedience,' focusing on digital forms of civil disobedience. Previously, she earned an M.A. in Theatre, Film and Television Studies as well as German and Philosophy from the University of Cologne. She also headed the office responsible for the German government's Third Engagement Report on behalf of the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ). Her research centers on Public Interest AI, examining how AI development and deployment can benefit society rather than primarily maximizing profit. Current projects include 'Impact AI' (funded by Volkswagen Foundation), which develops auditing methods to assess AI projects' impact on public interest and sustainability, and 'Human in the Loop,' investigating how automated decision-making processes should be designed for successful human-machine interaction. She previously led the 'Public Interest AI' project, developing a theoretically grounded understanding of public interest AI and creating prototypes like a web accessibility tool and fact-checking application. Analysis of her recent publications reveals a consistent focus on bridging AI technology with societal values. Her work spans technical aspects of AI implementation, ethical considerations, and practical applications that serve public interests. Key trends include human-AI collaboration frameworks, accessibility enhancements, critical examination of AI hype, and theoretical foundations for public interest-oriented AI development. Züger serves as Vice-Chair of the UNESCO Commission on Communication and Information and participates in several juries including the Deep Tech Award, Digital Places – Land of Ideas, and the Civic Innovation Fund. She is also a regular event moderator for organizations like the Berlin-Brandenburg Media Authority, re:publica, and transmediale. As project leader of Impact AI and head of the AI & Society Lab, Züger directs significant research initiatives with funding from organizations like the Volkswagen Foundation. Her work involves extensive collaboration with academic and practical partners across Europe and globally, particularly through projects addressing women in tech and international AI governance. The AI & Society Lab functions as an interdisciplinary interface for new research approaches and knowledge transfer in AI, promoting inclusive, human rights-friendly, and sustainable AI strategies in Europe.
Juan F. Sequeda is the Principal Scientist and Head of the AI Lab at data.world, with a PhD in Computer Science from the University of Texas at Austin. He co-founded Capsenta, a spin-off from his research on semantic data virtualization. His work bridges academia and industry through roles in the Property Graph Schema Working Group, LDBC Graph Query Languages task force, and W3C standards editing. Education : PhD in Computer Science (2015) from University of Texas at Austin His research focuses on Knowledge Graphs, Semantic Web, and Ontology-Based Data Integration. He develops technologies for graph data management and semantic query processing, with applications in constitutional data analysis (Constitute.org) and enterprise data virtualization (Ultrawrap, Gra.fo, G-CORE). Recent publications analyze composable graph query languages (G-CORE, 2018) and optimize SPARQL execution on relational data (Ultrawrap, 2013). Awards include NSF Graduate Fellowship (2010-2013), ISWC2014 Best Student Paper, and 2015 Institute for Applied Informatics Best Transfer Project. Scientific Awards : NSF Graduate Research Fellowship (2010-2013) 2nd Place, 2013 Semantic Web Challenge Best Student Research Paper, ISWC2014 2015 Best Transfer and Innovation Project (Institute for Applied Informatics) UT Graduate Diversity Fellowship (2008-2009) National Instruments Scholarship (2007-2008) Intel Foundation Fellowship (2007) He actively contributes to program committees (ISWC, ESWC, WWW) and workshop organization (COLD, AMW2018 General Chair). Contact: juan@data.world (work), juanfederico@gmail.com (personal).
Hwajung Hong is an Associate Professor in the School of Interactive Computing at Georgia Institute of Technology's College of Computing. With a prolific publication record spanning from 2009 to 2025, Dr. Hong has established herself as a leading researcher at the intersection of Human-Computer Interaction, accessibility, and mental health applications. Her work frequently appears in top-tier venues including CHI, CSCW, and DIS, with growing emphasis on AI/LLM applications in recent years. Dr. Hong's research focuses on designing technology for vulnerable populations, particularly individuals with autism spectrum disorder, mental health challenges, and neurodiverse communities. Her early work centered on social computing applications for autism support, evolving toward more comprehensive systems addressing mental wellness, stress management, and relationship dynamics. Recent publications demonstrate a strategic pivot toward leveraging large language models for healthcare interventions, communication support, and bias mitigation. Analysis of her 15 most recent publications reveals a strong trajectory toward AI-mediated interventions across multiple domains - from mental health support for Korean investigative officers to communication tools for minimally verbal autistic children. Her work consistently emphasizes user-centered design, cultural sensitivity, and practical implementation in real-world contexts rather than purely theoretical approaches. Dr. Hong has mentored numerous graduate students who have become productive researchers in their own right, with Kwangyoung Lee, Dasom Choi, and Hyunseung Lim appearing as frequent collaborators on recent publications. Her research program demonstrates remarkable continuity in addressing human-centered challenges while adapting methodologies to incorporate emerging technologies.
Prof. Dr. Marc Godau serves as Professor and Head of the Institute for Talent Research in Music (IBFM) at the University of Paderborn, while also acting as Speaker for Empirical music education with special consideration of school and pop cultural contexts. His academic work bridges music pedagogy with digital cultural studies, focusing on how contemporary technologies reshape musical practices and education. Godau's research centers on post-digital music education , critically examining algorithmic influences on creative processes, platform-mediated music practices (particularly TikTok and Instagram), and the sociomaterial dimensions of informal learning. He challenges traditional 'liveness norms' in music education that marginalize digital and popular cultural forms, advocating for pedagogical approaches that embrace cultural diversity and technological innovation in both school and informal settings. Analysis of his publication trajectory reveals consistent focus on digital transformation in music education, with recent work exploring YouTube tutorials, app-based music creation, and platform musicianship. His scholarship demonstrates how social media algorithms reshape songwriting subjectivity while highlighting tensions between institutional music education frameworks and emerging digital practices. As Principal Investigator for the KuMuS-ProNeD project (Professional networks for digital innovations in teacher training for art, music and sports), Godau drives systemic change in educator development. His teaching portfolio includes forward-looking courses such as 'Making and learning music in (post)digital culture' and 'Musical & Educational Influencers – Music Education of the Future?', positioning him at the vanguard of reimagining music pedagogy for digital generations.
Dr. André Artelt is a researcher at the University of Bielefeld within the Faculty of Engineering and affiliated with the Machine Learning Group at the Center for Cognitive Interaction Technology (CITEC). His work focuses on Explainable AI (XAI), particularly counterfactual explanations, and their applications in critical infrastructure like water distribution networks. Current Research: Explainable AI Counterfactual explanations Water network monitoring Physics-informed graph neural networks Scientific Contributions: His recent publications explore reinforcement learning for water pump scheduling, scalable graph neural networks for water systems, and benchmark frameworks like EPyT-Flow. He investigates how training data affects explanation quality and develops tools for robust counterfactual reasoning. Awards: Project Lamarr Fellowship
Lakhmi C. Jain is a distinguished academic affiliated with the University of South Australia. As a Professor, she has made significant contributions to the fields of Artificial Intelligence, Computational Intelligence, and Fuzzy Systems. Her research spans neural networks, decision support systems, robotics, and data analysis, with a focus on interdisciplinary applications. Her career includes over 445 publications, including books like Complex Networks in Software, Knowledge, and Social Systems (2019) and E-Learning Systems - Intelligent Techniques for Personalization (2017). She has held editorial roles in journals such as the International Journal of Intelligent Decision Technologies (IDT) and the Journal of Intelligent & Fuzzy Systems. Jain's work emphasizes practical applications of computational intelligence, including efforts in software development, biomedical signal processing, and multi-agent systems. She has collaborated extensively with researchers globally, contributing to advancements in AI-driven technologies and decision-making frameworks.
Markus Zanker is a Professor in the Department of Knowledge Engineering within the Faculty of Computer Science at Free University of Bozen-Bolzano, Italy. With an extensive publication record spanning over two decades, he has established himself as a leading expert in recommender systems research, with particular expertise in context-aware, group, and knowledge-based recommendation approaches. His work bridges theoretical foundations with practical applications across diverse domains including tourism, healthcare, and e-commerce. Zanker's research interests center on advancing the theoretical underpinnings of recommender systems while addressing practical challenges in real-world deployments. His recent work has focused on causal decision-making frameworks for recommendation, intent-aware systems, and the integration of generative AI in group recommendation scenarios. He has made significant contributions to explainable recommendation systems, medical recommendation applications, and tourism recommendation systems, demonstrating both theoretical rigor and practical impact. His recent publication portfolio reveals a strong trend toward addressing fundamental challenges in recommendation science, including the growing emphasis on causal reasoning to move beyond correlation-based approaches, the integration of generative AI capabilities for more sophisticated group decision support, and the development of frameworks for ethical and socially beneficial recommendation systems. His work increasingly bridges the gap between traditional recommendation algorithms and emerging AI paradigms while maintaining focus on real-world applicability. Zanker is actively involved in the academic community as a workshop organizer, having co-chaired the Knowledge-aware and Conversational Recommender Systems (KaRS) workshop and the Recommenders in Tourism (RecTour) workshop for multiple consecutive years at major conferences including RecSys. His research has been supported through collaborations with numerous international researchers and institutions, focusing on both theoretical advances and practical implementations of recommendation technology across multiple application domains.
Affiliations & Roles Cornelia Sindermann is an Independent Research Group Leader of the Computational Digital Psychology Team within the Stuttgart Research Focus 'Interchange Forum for Reflecting on Intelligent Systems for Diversity, Demography, and Democracy (IRIS3D)' at the University of Stuttgart. She holds associated roles in the Cluster of Excellence SimTech and the International Max Planck Research School for Intelligent Systems. Previously, she served as a Postdoctoral Researcher and Lecturer at Ulm University (2019–2022) and conducted research at the University of Toledo (2021–2022). She also held a Visiting Professorship at the University for Continuing Education Krems (2023). Education PhD in Natural Sciences (2019), Ulm University MSc in Psychology (2016), Ulm University BSc in Psychology (2014), Ulm University Research Focus Her work investigates the interplay between intelligent systems and human cognition, particularly focusing on how algorithm-driven platforms influence political opinion formation , disinformation spread , and democratic capabilities . Methodologically, she combines experimental designs , survey data , and digital trace analysis to study topics like filter bubbles, microtargeting, and the data economy. Key themes include: — Cognitive processing of online information — Effects of AI-driven content curation — Polarization and echo chambers — Ethical implications of social media business models Publications & Awards With over 80 peer-reviewed papers, her work spans journals in psychology, media studies, and political science. Awards include the 2019 Teaching Excellence Bonus (Ulm University) and grants from the Vodafone Foundation and DAAD . Notable publications address topics like fake news susceptibility, personality-driven social media addiction, and oxytocin’s role in trust and deception. Team & Collaborations Her research group at IRIS3D collaborates with experts in computer science, political science, and ethics. They actively seek to recruit researchers with backgrounds in psychology, computational methods, and digital policy. Current projects include developing tools to enhance democratic literacy and analyzing AI’s role in political discourse.
