Professor Thanos Papadopoulos is a faculty member at the University of Kent , serving as Deputy Dean and Head of the Department of Analytics, Operations & Systems. He is affiliated with the Centre for Logistics and Sustainability Analytics (CeLSA) . PhD : Warwick Business School, University of Warwick MSc : Informatics, Athens University of Economics and Business Diploma : Computer Engineering and Informatics, Patras University His research focuses on Operations and Information Management , with emphasis on digital technologies in supply chains , resilience , and sustainability . Recent work explores AI, metaverse, and data-driven strategies. He has authored 150+ peer-reviewed publications and collaborates with journals like British Journal of Management as Associate Editor. Awards include Stanford's Top 2% Researchers and Clarivate Highly Cited distinctions. Professor Papadopoulos supervises students in supply chain management , big data , and sustainability . His projects address geopolitical disruptions and digital transformation in manufacturing and retail.
Andrew Head is an Assistant Professor at the University of Pennsylvania's Department of Computer Science, specializing in Human-Computer Interaction (HCI) and Programming. His work bridges interactive reading , math notation accessibility , and AI-assisted code comprehension . Affiliated with Penn HCI, PLClub, and MindCORE, he co-leads research with Danaé Metaxa and Benjamin Pierce. University of Pennsylvania Assistant Professor, Computer Science Affiliations: Penn HCI, PLClub, MindCORE His research focuses on interactive reading interfaces , AI-powered programming tools , and math notation analysis . Recent projects include: FreeForm : Interactive math notation editor Tyche : Property-based testing tools Explainable Notes : Medical note interpretation systems Publications in CHI , UIST , and ICSE demonstrate his systems-centric approach combining user studies with working prototypes. Notable awards include Best Paper at UIST 2024 and CHI 2022. Advising: Ph.D. Students: Alyssa Hwang, Litao Yan, Hita Kambhamettu, Jeff Tao, Jessica Shi Grants: $1M NSF grant for Property-based Testing Tools (2024) Teaching: Spring 2025: CIS 4120/5120 - Human-Computer Interaction Fall 2024: CIS 7000 - Interactive Reading
Daniel Schnurr holds the Chair of Machine Learning, especially Uncertainty Quantification at the University of Regensburg since August 2022, where he conducts research at the intersection of artificial intelligence, data economics, and digital market regulation. Previously, he headed the Data Policies research group at the University of Passau, building his expertise in the economic and regulatory aspects of digital markets. His educational background includes a doctorate in business informatics from the Karlsruhe Institute of Technology (2016), where he also worked for three years as a research associate at the Institute for Information Systems and Marketing. He completed his undergraduate and master's studies in Information Systems at KIT (2007-2013), with international experience at Concordia University in Canada and Singapore Management University. Professor Schnurr's research focuses on the technical, economic, and social implications of new machine learning methods and data as a decisive competitive factor and driver of innovation in digital markets. His work examines how data functions as both an economic asset and regulatory challenge, particularly in contexts of market power, competition policy, and AI governance. He investigates uncertainty quantification in machine learning systems while considering their broader economic and societal impacts. His publication portfolio demonstrates consistent output in top-tier journals including Management Science, Journal of Information Technology, and Journal of Competition Law & Economics, with recent work increasingly focusing on AI regulation, data access remedies, and uncertainty-aware AI systems. The trajectory shows evolution from telecommunications infrastructure research to contemporary digital market and AI regulation issues. As a Research Fellow at the Centre on Regulation in Europe (CERRE) since 2022, he has authored numerous policy reports addressing regulation of cloud computing services, digital platforms, and data economy frameworks. His policy contributions bridge academic research with practical regulatory implementation, particularly regarding the European AI Act and Digital Services Act. His research program involves experimental approaches to understanding data markets, human-AI interaction dynamics, and regulatory effectiveness. Through his work at CERRE and collaborations with international scholars, he contributes to shaping evidence-based digital policy in the European context while maintaining strong connections to academic research communities in information systems and economics.
Albert M. Lai, PhD, is a Professor of Medicine and Computer Science & Engineering at Washington University in St. Louis, serving as Chief Research Information Officer (CRIO) for the School of Medicine and Deputy Director of the Institute for Informatics, Data Science and Biostatistics (I²DB). He leads WashU Medicine's data warehousing and informatics services, driving innovation in clinical research infrastructure. His expertise spans biomedical informatics, natural language processing (NLP), and telemedicine. Dr. Lai is also Deputy Faculty Lead for WashU’s Digital Transformation initiative, focusing on secure AI integration with sensitive healthcare data. He holds affiliations with the Institute for Public Health, Siteman Cancer Center, and the Center for Applied Health Informatics (CAHI). Research Interests: Dr. Lai develops informatics infrastructure to support clinical trial prescreening, leveraging NLP and machine learning for phenotype extraction from EHR data. He also explores telemedicine, mobile health applications, and EHR-driven cardiovascular health interventions for cancer survivors. His recent work addresses AI ethics in healthcare, including responsible data sharing and bias mitigation in generative AI models. Key Contributions: Over 77 peer-reviewed publications across clinical informatics, AI in healthcare, and pandemic response strategies. His projects include EHR-based cardiovascular health tools, SARS-CoV-2 surveillance in schools, and machine learning models for predicting transplant outcomes. Active mentorship of PhD/MSTP students in translational informatics and data science. Labs/Teams: Leads the Informatics Services Core and collaborates with the CRITICAL consortium for intensive care analytics. Engages in multi-institutional initiatives like the Greater Plains Collaborative for cancer data integration.
Aniket 'Niki' Kittur is a Professor in the Human-Computer Interaction Institute at Carnegie Mellon University's School of Computer Science. His research focuses on AI-augmented cognition, exploring how human and machine intelligence can collaborate to enhance creativity, decision-making, and innovation. He leads projects like the Semantic Reader and Skeema browser extension, aiming to reduce cognitive overload through intelligent systems. Education: BA in Psychology & Computer Science from Princeton University; PhD in Cognitive Psychology from UCLA. His work bridges HCI, crowdsourcing, and cognitive science, with 100+ publications and 17 best paper awards. He advises industry partners including Google, Microsoft, and Toyota while maintaining a lab focused on real-world impact. Research interests center on accelerating knowledge acquisition via systems that scaffold sensemaking (e.g., Selenite for web exploration) and fostering analogical innovation through crowdsourced/AI hybrid approaches. Notable contributions include CrowdForge (human-machine workflows) and Kinetica (touch-based data visualization). Awards include NSF CAREER Award, Allen Newell Award, and CHI Academy membership. His lab's Skeema tool has achieved 79% 30-day retention in beta, reflecting impactful user-centered design principles. Current projects emphasize LLM integration for composite cognition, aiming to create systems where 'LLMs + Humans > Either Alone.' Funding来自NSF, NIH, ONR, and industry partners like Bosch and Wikimedia. Teaching includes PhD bootcamps and user-centered research courses. Over 100 students have contributed to his projects, many advancing to tech leadership roles.
Julian Berger is a postdoctoral researcher at the Max Planck Institute for Human Development in the Center for Adaptive Rationality , where he explores how to enhance decision-making through hybrid human-AI systems. He is also a fellow of the Joachim Herz Foundation and has received funding from the Foundation of German Business and the Danish Data Science Academy. Education: M.A. Psychology in Business and Economics, Universidade Catolica Portuguesa (2021) B.A. Politics, Administration and International Relations, Zeppelin Universität (2018) His research spans human-AI collaboration , collective intelligence , and interpretable machine learning . A recurring theme in his work is developing methods to combine human expertise with AI capabilities for accuracy in domains like medical diagnostics , credit scoring , and football analytics . He has authored publications in high-impact venues such as PNAS , Nature Human Behavior , and Science and Medicine in Football . Scientific awards and funding include: Fellowship for interdisciplinary economics, Joachim Herz Foundation (2024) PhD funding from the Foundation of German Business (Stiftung der deutschen Wirtschaft) Research grant from the Danish Data Science Academy His recent article trends emphasize ensembling techniques that leverage complementary human and AI errors, algorithmic fairness, and practical heuristics like Hybrid Confirmation Trees. These works demonstrate significant improvements in diagnostic accuracy and decision cost-efficiency. Beyond academia, Berger works as a consultant and ML engineer with Simply Rational , focusing on interpretable models for financial and sports analytics. His work bridges theoretical research with real-world applications, prioritizing fairness, transparency, and human accountability in AI systems.
Sara Green is an Associate Professor at the Department of Science Education, University of Copenhagen, specializing in the Section for History and Philosophy of Science . Her work bridges philosophy, biology, and biomedical ethics, focusing on the epistemic and social implications of datafication in healthcare and the ethical challenges of precision medicine and consumer health technologies. Green holds a PhD in Science Studies from Aarhus University and was a postdoctoral fellow at the University of Pittsburgh’s Center for Philosophy of Science. She leads the PROMISE and COPE projects and contributes to EU-funded initiatives like DataSpace , TRANSCEND , and REDESIGN . Research Themes: Philosophy of precision medicine and data-driven healthcare Ethics of patient-derived organoids and organ-on-chip technologies Epistemic standards in consumer medicine Interdisciplinary integration in systems biology Article Trends: Recent publications explore organoid ethics , datafication in medicine , and philosophical frameworks for emerging health technologies . Key sub-fields include biobanking, cross-border data governance, and temporal dimensions of personalized medicine. Scientific Recognition: DFF Research Project 1 (2020) Semper Ardens Accellerate Grant (2023) Silver Medal, Royal Danish Society of Science and Letters (2024) Werner Callebaut Prize (2015) EU SwafS-Horizon stipend (2020) Teaching & Supervision: She teaches philosophy of science to students in biology, chemistry, and sports science, supervising projects on philosophy of biology and medicine and co-supervising science communication research. Collaborative Networks: Green collaborates across Denmark, the EU, and the U.S., particularly on cross-border health data infrastructure and reduction of animal models through organoid technologies.
Zoran Kalinic serves as an Assistant Professor at the Faculty of Economics, University of Kragujevac, where he teaches Electronic Business since October 2012. Previously, he worked at the Faculty of Mechanical Engineering in Kragujevac from 1996 to 2005, and joined the Faculty of Economics in February 2005 as an assistant in Information Systems, later teaching Information Technology and Electronic Business from 2009 onward. Doctorate (2012): Faculty of Engineering, University of Kragujevac, specializing in information systems development and mobile communications Postgraduate studies: Faculty of Mechanical Engineering in Kragujevac (completed with average grade of 10) Bachelor's degree: Faculty of Mechanical Engineering in Kragujevac (1996, average grade 9.43) Professor Kalinic's research focuses on digital transformation and its economic implications, with particular expertise in mobile commerce, electronic business systems, digital payment technologies, and consumer behavior in online environments. His work frequently employs advanced analytical methods including artificial neural networks, structural equation modeling, and hybrid analytical approaches to investigate technology adoption patterns and digital marketplace dynamics. He has conducted extensive research on Serbian digital markets, including studies on mobile payment systems, e-commerce development barriers, and real estate price prediction using AI techniques. His publication record demonstrates a clear progression from foundational technology acceptance research toward more complex analyses of digital ecosystems, with recent work examining influencer marketing effects on TikTok, biometric payment systems, and gig economy measurement in Serbia. The integration of artificial intelligence methodologies with traditional consumer behavior theories represents a distinctive feature of his scholarly approach. Professor Kalinic maintains active international academic engagement through short study visits to institutions including the University of Udine, Vienna University of Economics, University of Maribor, Krakow University of Economics, Coventry University, Polytechnic of Turin, and Comenius University in Bratislava. He spent six weeks at the University of Maribor in 2007 through a Tempus IMG grant and served as a visiting lecturer at the Krakow University of Economics in 2012. Author/co-author of over 60 papers in international and domestic journals and conferences Participant in multiple scientific research and professional projects Recipient of academic awards during studies from University, Faculty, Ministry of Science and Technology of Serbia, Embassy of Norway, WUS-Austria, Zastava-Yugo Automobiles, and Kragujevac City Assembly His professional development includes a month-long visit to the Faculty of Informatics at the University of the Basque Country in San Sebastian (2004) and ongoing collaboration with regional and European academic institutions. Professor Kalinic's research bridges theoretical frameworks with practical applications in the Serbian and Western Balkan digital economy context.
Elena Karahanna is a Professor at the Terry College of Business , University of Georgia. Her research spans Artificial Intelligence , Health Information Technology , and the social and algorithmic implications of digital platforms . PhD in MIS, University of Minnesota (1993) MBA in Business Administration, Lehigh University (1988) BS in Computer Science, Lehigh University (1986) Her work examines how conversational agents and social bots reshape e-commerce and social media, the algorithmic coordination in organizations, and the integration of IT in healthcare systems . She has contributed to foundational theories like the Needs-Affordances-Features (NAF) framework for social media analysis. Recent publications highlight her focus on digital governance (e.g., firm-sponsored online communities), chatbot applications in public health (e.g., pandemic response), and privacy concerns in online social networks. Her research often bridges information systems and marketing (e.g., hyper-privacy and dark web insights). Scientific Awards Terry College of Business Service Award, 2024 INFORMS Information Systems Society President's Service Award, 2023 MIS Quarterly Best Paper Award, 2022 AIS Leo Award for Exceptional Lifetime Contributions, 2020 AIS Fellow, 2012 Karahanna has served as Senior Editor for MIS Quarterly , Information Systems Research , and Journal of AIS . She co-founded the Doctoral Student Corner (2014) and the Senior Scholar Consortium (2004), emphasizing her leadership in academic mentorship. She has taught courses on theory development and business intelligence , and her international teaching includes stints in Hong Kong, Cyprus, Singapore, and Australia .
Hannu Saarijärvi is a Professor in the Faculty of Management and Business at Tampere University, specializing in Marketing. His research bridges consumer behavior, retail innovation, and data-driven health studies. Based in Tampere University's City Centre Campus, he explores transformative retailing and societal impacts of consumer data. University: Tampere University School: Faculty of Management and Business Department: Business Studies Email: hannu.saarijarvi@tuni.fi His research focuses on consumer behavior in omnichannel and second-hand retailing, data analytics using loyalty card datasets, and health research linking maternal experiences to dietary patterns. Recent studies examine sustainable diets , alcohol consumption dynamics , and food waste reduction . Key article trends highlight loyalty card data applications in health informatics , retail transformation , and sustainability . Collaborative studies with Finnish institutions analyze population-level consumption behaviors, legislative impacts, and digital service innovations. Professor Saarijärvi's work emphasizes value co-creation , customer experience , and strategic digitalization in retail contexts, with practical implications for public health and business models.
Dongming Xu is an Associate Professor in Business Information Systems at the University of Queensland Business School. She holds a PhD from the City University of Hong Kong in Information Systems and has established herself as a prominent researcher in the field of information systems with over 100 publications in top-tier journals and conference proceedings. Her educational background includes a PhD from City University of Hong Kong in Information Systems, though specific details about earlier degrees are not provided in the available text. Dr. Xu's research focuses on the confluence of information technology use and innovation, with particular emphasis on IT entrepreneurship, social media applications in business contexts, and business intelligence systems. Her work explores how information systems influence society and business performance, with applications spanning disaster management, eFinance, eHealth, and knowledge management. She combines theoretical model building with laboratory and field experiments, often developing prototype systems to validate her research. Her publication record demonstrates consistent high-quality output across multiple domains of information systems research, with recent work emphasizing digital disruption, platform ecosystems, social media in disasters, healthcare technology, and micro-learning applications. Her research shows a clear trajectory from foundational work on intelligent agents and decision support systems toward contemporary topics in digital transformation and platform-based innovation. Associate Editor, Information & Management Associate Editor, Journal of Electronic Commerce Research Associate Editor, Australasian Journal of Information Systems Dr. Xu has supervised numerous PhD students to completion, with research topics spanning digital disruption, IT startup development, social media in disasters, conceptual modeling, and environmental management. She has received multiple research grants, including current funding for 'Empowering Australia's Visual Arts via Creative Blockchain Opportunities' (2023-2026) and past projects on 'Smart micro learning with open education resources' (2018-2022). Her research has been supported by various agencies including the Hong Kong Government Research Grant Council, The National Natural Science Foundation of China, The University of Queensland, and City University of Hong Kong. She leads research in several key areas including IT entrepreneurship, business intelligence systems, and social media applications across multiple domains. Her work often involves developing innovative systems such as web-service-agent-based family wealth management systems, decision support systems for securities exception management, and knowledge management systems for disaster management.
Prof. Annette Jackle is a Professor of Survey Methodology and Deputy Director of Understanding Society - the UK Household Longitudinal Study at the University of Essex. Her research focuses on innovative data collection methods, including mobile device integration, sensor data, and data linkage consent processes. She leads methodological experiments in longitudinal studies to improve participation rates and data quality. Key projects include the Understanding Society Innovation Panel, which explores event-triggered data collection, mobile app-based expenditure measurement, and consent mechanisms for administrative data linkage. Her work addresses barriers to participation, mode effects, and bias reduction in surveys. Recent studies analyze digital trace data during the pandemic, mobile app efficacy in probability/nonprobability panels, and the impact of question placement on consent decisions. Her research informs best practices for survey design in rapidly evolving technological landscapes. Jackle collaborates with institutions like ISER and the ESRC Research Centre on Micro-Social Change. She advises on survey methodology for large-scale studies and contributes to policy-relevant research through Understanding Society's extensive dataset.
Dr Harrison Smith is a Lecturer in Digital Media & Society at the University of Sheffield's School of Sociological Studies, Politics and International Relations. He holds a PhD from the University of Toronto’s Faculty of Information, alongside MA and BA degrees in Sociology from Queen’s University, Canada. His research focuses on the political economy of data analytics, particularly in smart cities and consumer surveillance contexts. Education: PhD in Information Studies, University of Toronto (Canada) MA in Sociology, Queen’s University (Canada) BA (Hons) in Sociology, Queen’s University (Canada) Smith’s research examines how data infrastructures shape socio-economic inequality through processes like surveillance, classification, and market segmentation. Key areas include location-based marketing, 5G data infrastructures, and industry consolidation in data analytics. His work critiques how digital technologies reconfigure urban spaces and labor markets, particularly in 'smart city' contexts. Recent publications explore the metaverse's industrial implications, blockchain’s role in dispute resolution, and surveillance practices at music festivals. His teaching includes leading the module SCS2016: The Sociology of the Media. Smith’s expertise bridges media theory, urban informatics, and critical data studies, emphasizing ethical and political dimensions of digital technologies in everyday life.
Associate Professor Bruno Schivinski is affiliated with RMIT University's School of Media & Communication. He specializes in online consumer behavior, quantitative research methods, and multivariate data analysis. His work bridges digital media impact, consumer psychology, and health behavior, with a focus on gaming disorder, social media engagement, and brand equity. Education and professional background include roles at Gdansk University of Technology and consulting for institutions like the Polish Ministry of Science. He serves as Associate Editor for the Journal of Management and Business Administration–Central Europe . Research interests span digital phenotyping, behavioral addictions, and sustainable consumption. Notable contributions include studies on gaming disorder measurement, food waste reduction, and influencer marketing effectiveness. His work is published in top-tier journals like Journal of Business Research and Journal of Clinical Medicine . Recognition includes the Vice-Chancellor’s Award for Research Impact (2020), Emerald Literati Outstanding Reviewer (2022), and multiple best paper awards. He supervises research projects on digital behavior, food waste, and social media's role in health. Professional memberships include the Royal Statistical Society, Higher Education Academy, and American Marketing Association. His interdisciplinary approach addresses real-world challenges in digital health, consumer behavior, and sustainability.
Dr. Reuben Binns is an Associate Professor of Human Centred Computing at the University of Oxford , where he investigates intersections between computer science, law, and philosophy. His research focuses on data protection , machine learning ethics , and regulation of technology .
