Giles Foody is a Professor of Geographical Information Science at the School of Geography, University of Nottingham, and a member of the Rights Lab in the Faculty of Social Science. He is recognized as the UK’s most prolific and highly cited researcher in remote sensing, with a focus on interdisciplinary applications for real-world impact. Education: BSc (1st class honours) and PhD from the University of Sheffield. His research spans image classification for thematic mapping, particularly in land cover and human-induced changes. He pioneered soft image classifications, object-based methods, neural networks in remote sensing, and citizen sensors in mapping. Current projects include 'slavery from space' and Sargassum beaching analysis to meet UN SDGs. The trends in his publications highlight advancements in remote sensing, citizen science, and land cover mapping. His work integrates machine learning and geospatial analysis for social and environmental challenges. Scientific awards: IEEE Fellowship, David Landgrebe Award, Founder's Award (ISARA), multiple RSPSoc accolades, and SDG-related honors. Giles has supervised 51 research students and contributed to academic service via editorial roles, peer review leadership, and participation in national research assessment panels. His interdisciplinary work extends to European National Mapping Agencies and anti-slavery initiatives.
Professor Ioannis Katakis is a Faculty Member at the University of Nicosia, where he is affiliated with the School of Sciences and Engineering and the Department of Computer Science. He has held various academic positions across multiple institutions including Aristotle University of Thessaloniki, University of Cyprus, Cyprus University of Technology, Open University of Cyprus, Hellenic Open University, Athens University of Economics and Business, and National and Kapodistrian University of Athens. His educational background includes a PhD in Machine Learning for Automated Text Classification (2005-2009), a Master's in Information Systems (2005-2007), and a Bachelor's in Computer Science (2000-2004), all from Aristotle University of Thessaloniki. Professor Katakis specializes in several cutting-edge areas of computer science and data analysis. His primary research interests include Mining Social, Web and Urban Data , Sentiment Analysis and Opinion Mining , Data Streams , and Multi-label Learning . His work bridges theoretical machine learning approaches with practical applications in social media analysis, healthcare informatics, privacy protection, and smart city technologies. He has published extensively in top venues including CIKM, ECML/PKDD, IEEE TKDE, and ECAI. His recent publications demonstrate a clear trend toward applying machine learning techniques to real-world problems with societal impact. He has focused on areas such as GDPR compliance in smart devices, sentiment analysis in crowd-sourced content, healthcare applications including drug reaction classification and brain disease monitoring, and privacy protection in wearable technologies. His work often involves multi-modal data analysis and addresses challenges in data streams and multi-label classification. Professor Katakis has made significant contributions to his field, with his research cited over 4,200 times. He serves as an Editor for the journal Information Systems and has edited four special issues in journals such as DAMI and InfSys. He regularly contributes to the academic community by serving on program committees for major conferences including ECML/PKDD, WSDM, DEBS, and IJCAI, and by reviewing for prestigious journals like TPAMI, DMKD, TKDE, TKDD, JMLR, TWEB, and ML. He has been actively involved in European research projects, notably serving as Quality Assurance Coordinator and Senior Researcher for projects such as VAVEL (www.vavel-project.eu) and INSIGHT (www.insight-ict.eu). His grant activities demonstrate a strong focus on collaborative, interdisciplinary research with practical applications in urban data management, social media analysis, and healthcare informatics. He has organized three workshops at major conferences (ICML, ECML/PKDD, EDBT/ICDT) and has extensive experience translating research into practical applications through his involvement in European projects.
Miguel R. Rueda is an Associate Professor in the Department of Political Science at Emory University, specializing in electoral manipulation, civil conflict, money in politics, and political methodology. He holds a PhD from the University of Rochester (2014), an M.Sc. in Economics, and a B.Sc. in Economics and Mathematics from La Universidad de los Andes. Before Emory, he was a visiting scholar at Princeton University's Center for the Study of Democratic Politics (2013–2014). In Fall 2024, he will serve as a Visiting Associate Professor at Vanderbilt University. His research has been published in top journals like the American Political Science Review , American Journal of Political Science , and Journal of Conflict Resolution . Key themes include electoral fraud mechanisms, civil war dynamics, and the intersection of political methodology with empirical policy analysis. Rueda's work spans theoretical models of strategic behavior (e.g., foreign aid allocation, partisan poll-watching) and applied analyses of electoral systems, conflict outcomes, and governance challenges. His methodological contributions address econometric issues like post-instrument bias and omitted variable effects. Contact: miguel.rueda@emory.edu , 315 Tarbutton Hall, Emory University, Atlanta, GA 30322.
Professor Heiko Beyer holds a chair position at the Department of Sociology IV within the Faculty of Arts and Humanities and Social Sciences at Heinrich Heine University Düsseldorf. His academic work spans multiple domains of contemporary sociological inquiry with particular emphasis on prejudice studies, political sociology, and the sociology of religion. Beyer maintains an active research profile with numerous publications in leading sociological journals and serves as principal investigator for several major research projects funded by prestigious German research institutions. Professor Beyer's research interests form a cohesive body of work examining various dimensions of social prejudice and political attitudes. His scholarship demonstrates particular expertise in antisemitism studies, where he has developed innovative methodological approaches to measuring contemporary manifestations of anti-Jewish sentiment. His work also explores anti-Americanism as a comparative framework for understanding prejudice, examining the "elective affinities" between different forms of resentment. Additional research areas include the sociology of social movements, the intersection of religion and politics in Europe, and human rights implementation in diverse social contexts. Beyer's methodological approach combines quantitative survey research with qualitative analysis, often employing experimental designs to uncover the social context dependence of prejudicial attitudes. An analysis of Professor Beyer's recent publications reveals a clear trajectory toward increasingly sophisticated examinations of antisemitism in contemporary Germany. His work has evolved from theoretical examinations of antisemitism's historical development to nuanced empirical studies capturing its current manifestations across different social milieus. A distinctive feature of his recent scholarship is the examination of how global events, particularly conflicts in the Middle East, create "spaces of opportunity" for antisemitic expressions. He has also pioneered research on the relationship between political Islam and Jewish experiences in Germany, producing some of the first systematic studies on how radical Islamic ideologies impact Jewish life. His methodological contributions include developing new antisemitism scales and employing factorial survey experiments to measure latent attitudes. Professor Beyer currently leads three major research projects: "Antisemitism in the General Population of North Rhine-Westphalia" (funded by the State of North Rhine-Westphalia, 2022-2024), "Social Contexts of Equality Practices" (a Heisenberg project funded by the German Research Foundation, 2019-2024), and "The Impact of Radical Islam on Jewish Life in Germany" (funded by the Federal Ministry of Education and Research, 2020-2024). These projects collectively represent significant contributions to understanding prejudice, human rights implementation, and minority experiences in contemporary German society. His research often involves collaboration with interdisciplinary teams and has practical implications for educational programs combating antisemitism and promoting social equality.
Dr. Isabella Kasselstrand is a Senior Lecturer in the Department of Sociology at the University of Aberdeen, part of the School of Social Science. She holds a PhD in Sociology from the University of Edinburgh (2014) and has prior faculty roles at California State University, Bakersfield (Associate Professor) and Pitzer College (Visiting Position). Her research focuses on secularization, secularity, and nonreligious identities, employing quantitative and mixed-methods approaches with a regional emphasis on Northern Europe, particularly Scandinavia and Scotland. Key research areas include religious indifference, immigration impacts on religiosity, social trust dynamics, and cultural religion practices. She co-authored the book Beyond Doubt: The Secularization of Society (2023) and serves as Co-Editor of Secularism & Nonreligion , and on editorial boards of Sociology of Religion and Journal for the Scientific Study of Religion . She also holds the role of Publications Officer for the British Sociological Association's Sociology of Religion Study Group. Teaching expertise includes research methods, social inequality, and introductory sociology courses at both undergraduate and postgraduate levels. Her recent publications analyze trends in secular spirituality, public perceptions of women's empowerment, and comparative secularization patterns. She actively supervises PhD students focusing on quantitative methods and secularization themes.
Douglas Yu is a Professor in the School of Biological Sciences at the University of East Anglia (UEA), where he also serves as Principal Investigator and Director of the Ecology, Conservation, and Environment Center (ECEC), a joint venture with the Kunming Institute of Zoology. He is a member of the Centre for Ecology, Evolution and Conservation and the Organisms and the Environment research group. His research focuses on cooperation in ecological systems, particularly mutualisms between species and conservation as cooperation between humans and nature. Key methodologies include environmental DNA (eDNA), metabarcoding, and game theory. He co-founded NatureMetrics to commercialize biodiversity monitoring tools. His work spans tropical ecology, conservation genetics, and human-wildlife conflict resolution, notably in the Amazon. His recent research outputs highlight trends in molecular biodiversity assessment, landscape-scale eDNA analysis, and integrating remote sensing with ecological data. He leads multiple NERC-funded projects and industry collaborations focused on pollination services, cocoa sustainability, and statistical frameworks for eDNA. He is actively involved in scientific governance, serving on the NERC Biomolecular Analysis Facility Steering Committee and UKRI grant panels. He also contributes to public discourse through media appearances on topics like leech-based disease surveillance and bee conservation. He teaches courses in evolutionary biology, conservation genetics, and statistical modeling using R. He welcomes PhD and postdoctoral researchers, especially those interested in fieldwork in East Asia.
Sible Andringa is Professor of Second Language Pedagogy at the University of Amsterdam's Faculty of Humanities, officially inaugurated on June 16, 2023. Dr. Andringa serves as Academic Director of the Institute for Dutch Language Education (INTT), Coordinator of the Language Learning, Literacy and Multilingualism research group, and Coordinator of the Master's program in Dutch as a Second Language and Multilingualism. Dr. Andringa's research focuses on second language acquisition and bilingualism, specifically investigating the added value of explicit instruction, how input distribution affects language learning outcomes, and the role of awareness in language learning trajectories. Key ongoing projects include the Meta-LLL project examining how literacy shapes language learning, the SLA4All initiative for reproducing SLA research with non-academic samples, and the OASIS project creating accessible research summaries for practitioners. Previously, Dr. Andringa led Project MIND studying bilingual daycare effects and contributed to the Stilis project on listening proficiency. As General Editor of the Dutch Journal of Applied Linguistics (DuJAL), Dr. Andringa promotes open science principles in language research. Recent publications demonstrate a focus on addressing sampling biases in SLA research, open access publishing ethics, and practical applications of language acquisition research for educational settings. Academic Director, Institute for Dutch Language Education (INTT) Coordinator, Language Learning, Literacy and Multilingualism research group Coordinator, Master's program Dutch as a Second Language and Multilingualism General Editor, Dutch Journal of Applied Linguistics (DuJAL) Member, Mastery Team for Modern Foreign Languages Member, OASIS project team Member, IRIS database advisory group Dr. Andringa supervises PhD candidates including Kyra Hanekamp and Darlene Keydeniers, particularly in research related to bilingual daycare environments and language development. The research program has received funding from the Dutch ministry of Social Affairs for Project MIND and continues to secure support for ongoing projects examining language learning mechanisms. Dr. Andringa leads the Language Learning, Literacy, and Multilingualism research group which investigates language and literacy acquisition across the lifespan, with emphasis on how language skills are learned, maintained, and used in educational contexts. The group meets weekly to discuss projects, plans, funding opportunities, and research topics while promoting collaboration, methodological innovation, and open science principles.
Prof. Rajiv Sinha is a Professor in the Department of Earth Sciences at Indian Institute of Technology Kanpur . With a PhD from the University of Cambridge (1992), his career spans over two decades at IITK, including roles as Head of Department since 2014. Education: PhD (University of Cambridge, 1992), M.Tech (University of Roorkee, 1987), B.Sc (Patna University, 1983) Key Affiliations: Member of International Association of Sedimentologists, SEPM, Quaternary Research Association, and Indian Professional Societies Research Focus: Specializing in river science , Prof. Sinha investigates fluvial geomorphology , sedimentology , and natural hazards like Kosi floods . His work integrates remote sensing and GIS for climate change and paleoclimate reconstruction , notably studying the Ganga river system and its anthropogenic impacts . Scientific Leadership: His publications (2013-2017) reveal: Anthropocene river systems (2016) Indus Civilization paleohydrology (2017) Kosi megafan dynamics (2015) Monsoon evolution (2010, 2014) Groundwater management (2016) Awards & Recognitions: Pandit Girish Ranjan Chair Professorship (2013) National Mineral Award (2002) Alexander von Humboldt Fellowship (2000) UGC Research Fellowship (1988) University Gold Medal (1987) Collaborative Network: Partners include University of Durham , Imperial College London , and Institute du Physique de Globe, Paris . Currently leading Ganga River Basin Management studies and river science initiatives at IITK.
Thorsten Schmidt is Professor of Mathematical Stochastics at the University of Freiburg, succeeding Prof. Ernst Eberlein in the summer semester of 2015. He also serves as Senior Financial Engineer at MathFinance. Previously, he held professorships at Chemnitz University of Technology (2008-2015), Technical University Munich (2008), and University of Leipzig (2004 onwards). From 2017-2019, he was a Research Fellow at the Freiburg Institute for Advanced Studies (FRIAS) in a joint research group with the University of Strasbourg and USIAS on the topic of Linking Finance and Insurance. His research focuses primarily on financial and actuarial mathematics, stochastic processes, and statistics, with recent work on machine learning methods and their applications in financial mathematics and AI regulation. In Freiburg, his goal with his young team is to tackle complex challenges with improved mathematical models and apply these methodologies to various fields. Key Research Areas: Financial mathematics and credit risks Pricing and hedging of derivative financial products Statistics of stochastic processes Energy markets and nonlinear filter theory Machine learning applications in finance and insurance His recent publications show a strong trend toward integrating machine learning with traditional mathematical finance, particularly in risk management, insurance-finance arbitrage, and robust financial modeling. His work increasingly addresses ethical considerations in AI applications within finance, reflecting his broader interest in responsible AI development. Notable Awards: IDA Award Finance (2015) FRIAS-USIAS Research Fellow (2017/2018) IDA Award Machine Learning and AI (2020) MAPFRE Research Grant (2020) Luis Bachelier Fellow (2021) As Editor-in-Chief of Statistics and Risk Modeling and Associate Editor for Mathematical Finance and International Journal of Theoretical and Applied Finance, Schmidt plays a significant role in academic publishing. He leads the CRC 'Small Data' research center with Harald Binder, focusing on medical problems where disease progression must be estimated with few data points per patient. His LeanAI project, funded by the Vector Foundation, explores the connection between machine learning and theorem-proving software LEAN, aiming to develop AI that can translate between mathematics and formal proof systems. His laboratory work centers around the application of stochastic methods combined with machine learning to solve problems in finance and insurance where data is limited ('Small Data' initiative), with significant funding from DFG (€12 million for CRC Small Data) and the Carl Zeiss Foundation.
Professor Sylvia Walby is a faculty member at Royal Holloway, University of London, within the Department of Law and Criminology, School of Law and Social Sciences. She holds the Alexander von Humboldt Foundation Anneliese Maier Research Award, hosted by the University of Duisburg-Essen (2018–2025), and has held visiting positions at institutions including UCLA and Harvard. Current research focuses on violence and society, including gender dimensions, trafficking, and complex systems theory. Her work contributes to Sustainable Development Goals (SDGs), particularly those addressing gender equality and reduced inequalities. Key publications include Trafficking Chains: Modern Slavery in Society (2024) and methodological contributions to violence measurement. Her research spans criminology, sociology, and gender studies, emphasizing policy engagement and data-driven approaches. Recent articles analyze violent crime trends, trafficking data integration, and violence measurement in crime surveys. These works highlight intersections of gender, policy, and statistical methodologies. Scientific awards include Fellowships from the British Academy and Academy of Social Sciences, an OBE, and an honorary doctorate from Queen’s University Belfast. She has served as Chair of the REF2021 Sociology Sub-Panel and held leadership roles in the International Sociological Association and European Sociological Association.
John J. Curtin is a Professor in the Department of Psychology at the University of Wisconsin-Madison, where he directs the Addiction Research Center. His work bridges clinical psychology, computer science, and engineering to develop innovative digital solutions for mental health and addiction treatment. Dr. Curtin's research focuses on digital therapeutics and personal sensing technologies for substance use disorders and mental illness. His laboratory develops software applications that provide evidence-based interventions, treatment management tools, and enhanced communication with care providers. He specializes in algorithm development for moment-to-moment psychiatric risk prediction and just-in-time personalized interventions that adapt to both patient characteristics and their current context. His research program is highly interdisciplinary, collaborating with the Center for Health Enhancement Systems Studies, computer science, geography, and electrical and computer engineering departments. Dr. Curtin's work combines machine learning approaches with novel data streams from geolocation, cellular communications, social media activity, and wearable biosensors to create more effective and personalized treatment approaches. Dr. Curtin has secured continuous funding from the National Institutes of Health (NIAAA, NIDA, NCI and NIMH) since 1998. His current research examines machine learning-assisted precision medicine for smoking cessation, contextualized daily prediction of lapse risk in opioid use disorder, and dynamic real-time prediction of alcohol use lapse using mobile health technologies. His laboratory has produced numerous publications advancing the field of digital mental health interventions, with a particular focus on using technology to deliver precisely tailored treatments at the right moment for individuals struggling with substance use disorders.
Prof. Dr. Helen Baykara-Krumme is a full-time Professor of Sociology with a focus on Migration and Participation at the Institute of Sociology, University of Duisburg-Essen since March 2019. She serves as Managing Director of the Institute of Sociology (2020-2022), Chair of the Faculty of Humanities Ethics Committee since 2020, and Chair of the InZentIM Board since 2024. Her research spans migration, transnationalization, integration, and participation, with specialized focus on family processes in migration contexts, life course analysis, aging in migration contexts, migration-related organizational change, migration-disability intersections, and urban research methodologies. Education: Sociology, Statistics, and Agricultural Sciences (1995-2002, Free University & Humboldt University Berlin); PhD in Philosophy (2007, Free University Berlin); Habilitation (2017, Chemnitz University of Technology) Research Leadership: Coordinated BMBF-funded ZOMiDi project on civil society responses to migration diversity; edited Organisationaler Wandel durch Migration? (2022); contributed to the Ninth Family Report of the Federal Government (2016-2021) Methodological Expertise: Quantitative survey methods, intergenerational solidarity analysis, urban ethnography, and intersectional frameworks Awards: Fellow of the International Max Planck Research School LIFE (2002-2006) Teaching: Supervises final theses, leads courses on migration and globalization, and maintains regular consultation hours
Felipe Thomaz is an Associate Professor of Marketing at Saïd Business School, University of Oxford, and Deputy Director of the Oxford Future of Marketing Initiative. He holds a PhD in Marketing from the University of Pittsburgh and previously taught at the University of South Carolina. His research focuses on marketing strategy, AI ethics, illicit markets, and ESG integration, with notable contributions to frameworks like Ad Net Zero for net-zero advertising emissions. He collaborates with UN agencies, NGOs, and tech companies to address global sustainability goals and wildlife trafficking networks. Education: PhD in Marketing (University of Pittsburgh), MSc in Marketing & Finance (University of Pittsburgh), BSc in Animal Sciences (University of Florida). Research interests include digital marketing channels, brand performance via social networks, AI-driven marketing strategies, and conservation science linked to wildlife trade. His work bridges academia and industry, resulting in spinouts and IP transfers from Saïd Business School. Key projects include: Ad Net Zero: Global standard for reducing advertising emissions UN collaboration on wildlife trafficking through dark web analysis UNESCO partnerships on eliminating stereotypes in advertising His interdisciplinary approach spans marketing, mathematics, and conservation science, with publications in top journals like Journal of Marketing and Conservation Science and Practice .
Salvatore Ruggieri is a Full Professor in the Department of Computer Science at the University of Pisa, where he teaches in the Master Programme in Data Science and Business Informatics. He is affiliated with the KDD LAB, a joint research group of ISTI-CNR and the University of Pisa, and actively contributes to national and European AI initiatives such as XAI, NoBIAS, TAILOR, and SoBigData.eu. His research focuses on data mining and knowledge discovery, with a strong emphasis on ethical AI. Key areas include discrimination discovery and prevention, fairness, privacy, explainable AI (XAI), causal inference, and classification algorithms. He has led significant projects such as ENFORCE, a national FIRB project on legal and computational enforcement of non-discrimination and privacy rights in ICT systems (2010–2014), and has served as program chair for the XIII Italian Symposium on Artificial Intelligence (2014). The recent publications (2018–2023) highlight a consistent trend in interpretable and fair machine learning, including selective classification, stability of interpretable models, and causal reasoning for fairness. His work often involves collaboration with leading researchers like Dino Pedreschi and Riccardo Guidotti, and appears in top venues such as AAAI, IEEE TKDE, and WIREs. His scientific honors include the award for the best Ph.D. thesis in Theoretical Computer Science from the Italian Chapter of EATCS. Best Ph.D. Thesis in Theoretical Computer Science, Italian Chapter of EATCS He advises and collaborates with numerous researchers in the KDD LAB and has contributed to major grants and research initiatives in AI and data science. He is involved in educational programs, including the National Ph.D. in Artificial Intelligence - Society, and promotes interdisciplinary research at the intersection of computer science, law, and ethics. Ruggieri is a member of the KDD LAB, where he leads research in ethical and transparent AI. He is also part of large collaborative networks such as SoBigData.eu and HumanE-AI-Net, which aim to build socially responsible and human-centered AI systems.
Martin Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in Social Statistics, Clinical Epidemiology, and Industrial Labor Relations. Since joining Cornell in 1987, he has developed methodologies spanning Bayesian inference, tensor analysis, and machine learning applications in biomedicine and finance. His research integrates statistical theory with computational innovations, particularly in high-dimensional modeling and quantum-inspired algorithms. Recent work focuses on geometric approaches to tensor decomposition, misclassification correction methods, and phylodynamic models incorporating dormancy effects. Professor Wells teaches statistical methodology across disciplines including law, medicine, and biology, adapting analytical frameworks to diverse research contexts. His interdisciplinary collaborations extend to Weill Medical College and the School of Industrial and Labor Relations.
