Dr. Gianluca Demartini is a leading researcher in Human-in-the-loop AI Systems with significant contributions to Crowdsourcing , Information Retrieval , and Generative AI applications. His work bridges Machine Learning and Human-Computer Interaction , focusing on Bias Management , Fact-Checking , and Ethical AI . Major Affiliations : L3S Research Center, ScienceWISE platform, and collaborations with institutions like University of Queensland and University of Padua Over 15 years, his research has explored Crowdsourcing Quality Control (Mechanical Cheat 2012), Entity Ranking (2008-2013), and Semantic Search . Recent work (2024-2026) focuses on Generative AI Impacts in domains like Media Literacy , Data Curation , and Visual Analytics . Scientific Recognition : Best Paper Award (Top 1.4%) at ICTIR 2023 Best Short Paper Award (Top 0.6%) at ECIR 2020 Honorable Mention (Top 2%) at CSCW 2020 Best Demo Award at ISWC 2011 3rd Best Paper at LA-WEB 2008 His 15 most recent publications (2024-2026) demonstrate expertise in LLM-based Content Moderation , Immersive Data Visualization , and Trustworthy AI Systems . He has pioneered methods for Bias Detection in Wikipedia (2013), Entity Ranking (2008-2013), and Human-AI Collaboration frameworks. His work consistently addresses ethical challenges in AI for Social Good and Responsible Data Science .
Prof. Noam Noked is an Associate Professor at the Faculty of Law, The Chinese University of Hong Kong, specializing in tax law and policy. He serves as Director of the Faculty’s Ph.D. and M.Phil. programs and is an Honorary Secretary of Hong Kong’s Joint Liaison Committee on Taxation. Education: Doctor of Juridical Science (S.J.D.), Harvard Law School LL.M. (requirements fulfilled, degree waived), Harvard Law School LL.B., Tel Aviv University Faculty of Law B.A., Accounting Department, Tel Aviv University Research Interests: Tax policy and international taxation Tax administration and compliance Law and economics intersections His work focuses on combating offshore tax evasion, mandatory disclosure rules, and aligning domestic tax frameworks with global minimum standards. Scientific Awards: Research Excellence Award (2023-24) Young Researcher Award, CUHK (2020) John M. Olin Prize for Best Paper in Law & Economics (2010) Research Grants: HK$481,000 General Research Fund (2023-2025): "New Ways to Compete: How Hong Kong Can Adapt to the New International Tax Order" HK$475,000 General Research Fund (2021-2023): "Mandatory Disclosure Rules: Development, Policy Analysis, and Implications for Financial Centers" HK$470,000 Early Career Scheme (2019-2021): "Regularization of Tax Noncompliance: Comparative Legal Analysis and Proposal for China"
Giomara Lárraga Maldonado is a Postdoctoral Researcher at the Faculty of Information Technology within the University of Jyväskylä , Finland. She contributes to the Multiobjective Optimization Group and is affiliated with the Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO) thematic research area. Research Focus: Interactive Multiobjective Optimization, Evolutionary Computation, Explainable AI Key Areas: Preference integration, Decomposition-based methods, Human-Computer Interaction for decision support Her recent work explores explainability frameworks (e.g., LIME integration), phase-specific algorithm configuration, and semantic distance studies for visualization. She collaborates with researchers like Kaisa Miettinen and Giovanni Misitano. She has contributed to conferences such as GECCO, PPSN, and AAMAS, with publications emphasizing open-access availability. The R-XIMO framework (2022) highlights her work on explainable systems.
David Lo is the OUB Chair Professor of Computer Science at Singapore Management University's School of Computing and Information Systems, where he directs the Information Systems and Technology Cluster and the Center for Research on Intelligent Software Engineering. An ACM Fellow, IEEE Fellow, and ASE Fellow, his research focuses on AI for Software Engineering (AI4SE), leveraging machine learning, data mining, and NLP to enhance software analytics and automation. Research Highlights: AI4SE, code LLMs, human-AI synergy in software engineering, software reliability, and empirical studies of practitioner pain points Awards: IEEE TCSE Distinguished Service Award, university-wide Teaching Excellence Award, Outstanding Graduate Supervisor Award, 2 Test-of-Time Awards, and 11 ACM SIGSOFT/IEEE TCSE Distinguished Paper Awards Leadership: General Chair of ASE'16 and MSR'22, PC Co-Chair for ASE'20, FSE'24, and ICSE'25, ACM SIGSOFT Executive Committee member His work has received over 20 awards, 37,000 citations, and an H-index of 100. As an educator, he has mentored trainees who became faculty and R&D experts globally.
Fabienne Berger-Remy is a Senior Lecturer at Dauphine University – PSL, accredited to supervise research (HDR). She transitioned to academia in 2014 after extensive professional experience in marketing, brand management, and consumer goods consulting, with prior affiliations at IAE Paris Sorbonne. Research Focus : Multidisciplinary studies on marketing profession transformations, work-brand-consumption dynamics, and intangible capital creation. Publications in M@n@gement , Journal of Business Research , and Journal of Marketing Management highlight her work on digital transformation, brand crisis management, and organizational psychology. Publications reveal trends in digital marketing impacts, crisis communication strategies, and intellectual capital dynamics. Her work bridges theoretical frameworks with practical marketing challenges, including brand dissonance and datafication.
Sylvie Delacroix is the Inaugural Jeff Price Chair in Digital Law and Director of the Centre for Data Futures at King's College London. She is also a Visiting Professor at Tohoku University, focusing on bridging theory and practice in ethics and public policy initiatives. Her research spans Data & machine ethics Ethical agency and habit Social sustainability of data ecosystems Participatory infrastructure for AI systems Uncertainty communication in LLMs Legal theory and digital law Recent publications address LLM interfaces as transitional spaces for democratic revival and sustainable data rivers in generative AI. Her work has attracted significant grant funding from the Patrick J. McGovern Foundation, Wellcome Trust, and Omidyar Network. Scientific awards include the Leverhulme Prize Peter Birks 2d Prize for Outstanding Legal Scholarship Montgomery Fellowship at Dartmouth College She supervises PhD research on large language models and uncertainty communication, as well as habit in ethical lives. Her policy contributions include advising the Law Society of England and Wales on algorithmic justice systems.
Novi Quadrianto is a Professor of Machine Learning at the School of Engineering and Informatics, University of Sussex, where he joined as a Lecturer in February 2014. He is currently a Principal Investigator on three active EU grants: BayesianGDPR (ERC), TANGO (EU Horizon RIA), and Act.AI (ERC Proof of Concept). He also holds an Adjunct Professor position in Data Science at Monash University, Indonesia, and serves as Strategic Lab co-Leader of the BCAM Severo Ochoa Strategic Lab on Trustworthy Machine Learning in Bilbao, Spain. His educational background includes a PhD in Machine Learning from the Australian National University (2012) and a BEng in Electrical and Electronics Engineering from Nanyang Technological University, Singapore. During his PhD, he conducted research at multiple international institutions including HIIT-Finland, Yahoo! Research-US, University of Alberta-Canada, Fraunhofer IAIS-Germany, and IST Austria. From 2012-2014, he was a Newton International Fellow of the Royal Society at the University of Cambridge. Professor Quadrianto directs the Predictive Analytics Lab (PAL) since 2017, which focuses on "Responsible AI" research developing AI models that embed fairness, accountability, transparency, and trustworthiness. His research spans algorithmic fairness, federated learning, and computer vision, with applications in sustainable development, healthcare, and finance. His work has been funded by prestigious organizations including the European Research Council, EPSRC, and HM Treasury. His publications reveal a strong focus on addressing challenges in AI fairness, robustness, and privacy, particularly in dynamic environments and heterogeneous data settings. Recent work explores performative prediction, diversity-driven learning, and efficient vision transformer inference, demonstrating his leadership in cutting-edge machine learning research. European Research Council ERC Proof of Concept Grant (2023) Guarantor Researcher for BCAM Severo Ochoa Excellence Accreditation (2023) European Lab for Learning and Intelligent Systems (ELLIS) Scholar/Fellow (2020) European Research Council ERC Starting Grant (2019) Newton International Fellowship (2012) Microsoft Research Asia Fellowship (2009) Professor Quadrianto currently supervises six PhD students and five postdoctoral researchers. He has served as Action Editor for Transactions on Machine Learning Research since 2022 and as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence since 2016. He has also been an Area Chair for major conferences including NeurIPS, ICML, and AAAI. His PAL laboratory hosts a team of 15 members focused on inter-disciplinary AI research with domain experts across various sectors. The PAL Lab operates three innovation strands: AI for Sustainable Development (supporting UN SDGs), AI for Healthcare (transforming health outcomes), and AI for Finance (personalized loan decision-making). The lab also leads initiatives in Diversity & Inclusion in AI and offers Pro-Bono Office Hours to organizations seeking guidance on machine learning aspects.
Kenneth C. Wilbur is a Professor of Marketing and Analytics at the University of California, San Diego's Rady School of Management. He holds the Sheryl and Harvey White Chair in Management Leadership and serves as Associate Editor for Marketing Science and the Journal of Marketing Research. Research focuses on quantitative marketing, customer analytics, and digital platform phenomena 18 award-winning papers across marketing, economics, and interdisciplinary journals Organizer of the Workshop on Platform Analytics with YouTube archives His work bridges empirical analysis with practical applications in advertising, blockchain technology, and regulatory compliance. Recent publications examine digital advertising inefficiencies, platform pricing algorithms, and policy impacts on consumer behavior. Scientific Awards John D. C. Little Award Finalist Don Morrison Long-Term Impact Award Finalist Frank M. Bass Award Winner Multiple Best Paper Finalists Teaching materials include UCSD courses: Customer Analytics and Introduction to Marketing Analytics. Publicly shares Quarto source files for educational reuse.
Armin Kirchknopf serves as a Junior Researcher at the Media Computing Research Group within the Institute of Creative Media/Technologies, Department of Media and Digital Technologies at the University of Applied Sciences St. Pölten. His interdisciplinary work bridges artificial intelligence, computer vision, and social media analysis, with significant contributions to misinformation detection and disaster response systems. Based at Campus-Platz 1 in St. Pölten, Austria, he actively collaborates on EU-funded projects and publishes in top-tier AI venues. His educational journey spans humanities and technology: a Bachelor of Arts in Egyptology and Master of Arts in Classical Archaeology from the University of Vienna (including fieldwork at excavation sites across Austria, Germany, and Egypt), followed by a Bachelor of Science in Media Technology from FH St. Pölten. This unique background informs his human-centered AI research approach. Kirchknopf's research centers on explainable multimodal AI systems for real-world challenges. His recent work demonstrates expertise in transformer-based architectures for cross-lingual fake news detection, sexism identification, and flood monitoring through social media imagery. He pioneers techniques like Grad-CAM for object detection explainability and develops visualization tools for complex data interpretation, emphasizing transparency and social impact in AI deployment. Analysis of his 13 publications (2017-2022) reveals a strategic shift toward applied AI in societal contexts , particularly using social media data for disaster management and combating online toxicity. His projects consistently integrate computer vision with natural language processing, showing increasing sophistication in multilingual capabilities and model interpretability frameworks. His scientific recognition includes: Creative Business Award for co-developing the Tenjin learning quiz application No documented student advisement or grant leadership appears in current records, though he actively mentors through project-based collaborations. His work with the Media Computing Research Group drives innovation in educational technology and public safety applications. Kirchknopf contributes to the Media Computing Research Group's portfolio including Fake News Detection, SAiEX (Safe AI with explainable integrity), InfraBase (building footprint segmentation), and Ressel Center music therapy projects. His cross-disciplinary collaborations span computer scientists, archaeologists, and social scientists, reflecting the group's commitment to human-centric technological solutions .
Anson Kahng is an Assistant Professor in the Department of Computer Science and the Goergen Institute of Data Science at the University of Rochester. He previously held postdoctoral positions at the University of Toronto and completed his PhD at Carnegie Mellon University under the supervision of Ariel Procaccia, focusing on computational social choice. PhD, Computer Science, Carnegie Mellon University Undergraduate degree, Computer Science, Harvard College His research explores the intersection of computer science and democracy, developing frameworks like virtual democracy and liquid democracy while analyzing fairness in participatory budgeting and voting systems. He combines theoretical analysis with empirical methods, emphasizing interdisciplinary collaboration. Recent work includes advancements in ranked choice voting optimization, fairness metrics for elections, and structural analysis in cryo-electron tomography. He has published in top venues such as IJCAI, AAAI, NeurIPS, and ACM Transactions on Economics and Computation. NeurIPS 2019 Spotlight Presentation (top 2.5% of submissions) Kahng advises PhD students Alina Chadwick and Joe Saber, and has mentored multiple undergraduate researchers. He teaches courses on algorithmic game theory and computational statistics at the University of Rochester.
Leah Macfadyen is an Associate Professor of Teaching in the Department of Language & Literacy Education at the University of British Columbia (UBC), Faculty of Education. She serves as Coordinator for Curriculum & Instruction in the Master of Educational Technology (MET) program. With interdisciplinary training in experimental sciences and humanities, she bridges analytical rigor with cultural theory in her research on digital education and learning analytics. Her research spans learning analytics , digital literacies , and critical intercultural communication . Key projects include developing UBC’s Introduction to Global Citizenship online course (2005) and co-authoring MET program courses like ETEC 542. She explores ethical dimensions of ‘big data’ in education and data literacy challenges. Recent publications (2020–2023) focus on institutional learning analytics frameworks, curriculum NLP analysis, and ethical codes for practitioners. Collaborative work with Shane Dawson and others has been published in journals like Journal of Learning Analytics , Computers & Education , and Journal of Genetic Counselling . Key Themes : Intercultural communication in digital spaces, systems thinking for educational analytics, ethical implications of data-driven learning Courses Developed : ETEC 500, 520, 542, 543, 581, and 590
Luisa Wellert is a Research Associate at the Innovative Educational Technologies Department within the Tübingen Center for Digital Education (TüCeDE) at the University of Tübingen since September 2023. She is also a PhD student at TüCeDE since October 2022. Education: Master of Arts in Intermedia and General Educational Science (2020-2022) from University of Cologne Bachelor of Arts in Media Studies and Educational Science (2016-2019) from University of Tübingen Research Focus: Her work centers on media pedagogy , media didactics , and adaptive learning systems , with particular emphasis on AI integration in educational contexts. Recent projects examine automated qualitative coding of AI tutoring dialogues using large language models and effectiveness of self-developed adaptive systems in schools. Publications: Recent work analyzes assessment methodologies in adaptive learning systems, compares performance-based and cognitive load-based evaluation approaches, and explores implementation challenges of DIY adaptive technologies. She actively contributes to open-source AI tutoring initiatives through the OSATI project. Presentations: Luisa presents her research at major conferences including EARLI, LEAD Research Meeting, and GEBF Conference, focusing on practical implementations of AI-based educational tools and their cognitive impacts. Professional Activity: Prior to her current role, she served as Project Manager for Educational Research at TüCeDE (2022-2023) and worked as a Research Assistant at mmb Institut GmbH (2021-2022) and mecodia GmbH (2018-2020). She also has experience in media education and empirical media research.
Cornelius Puschmann is a Professor of Communication and Media Studies at the University of Bremen's ZeMKI, leading the Digital Communication and Information Diversity (DCID) Lab. He has held affiliations with institutions including Zeppelin University, the Alexander von Humboldt Institute for Internet and Society, and the Leibniz Institute for Media Research / Hans Bredow Institute. His research focuses on computational communication, digital media usage, hate speech, and algorithmic impacts on digital communication. Current projects: Informed by Influencers? (INDI), Political Polarization and Individualized Online Information Environments (POLTRACK) Member of Deutsche Gesellschaft für Publizistik- und Kommunikationswissenschaft (DGPuK), European Communication Research and Education Association (ECREA), and International Communication Association (ICA) His recent publications explore topics such as alternative news consumption, political polarization, and communicative AI. He has also contributed to open-source methodologies like the RPC-Lex dictionary for analyzing right-wing populist discourse. Notable affiliations include visiting scholar roles at the Oxford Internet Institute, Berkman Klein Center for Internet and Society, and University of Amsterdam's Department of Media Studies.
Katy Ilonka Gero is a Lecturer at the University of Sydney's School of Computer Science, with a PhD in Computer Science from Columbia University (2022). She holds a BSc in Mechanical Engineering from MIT, where she received the Carl G. Sontheimer Prize for Excellence in Innovation and Creativity. Education : BSc (MIT), PhD (Columbia) Her research focuses on Human-Computer Interaction , Creative Writing , and AI Ethics , particularly examining how language models impact writing processes, ownership, and agency. She advocates for community-driven language models trained on consensual data and explores technical innovations for personalized AI tools. Recent publications span language model ethics (Nature Machine Intelligence 2023), generative AI (CHI 2025 Best Paper), and creative collaboration (CHI 2023). Key trends include user-centered AI design , creative ownership , and data ethics . Scientific Awards : NSF Graduate Research Fellowship, Brown Institute for Media Innovation, Amazon Research Award, CHI Best Paper (2025), CHI Honorable Mention (2024) As co-founder of Ensemble Park and former taper editor, she bridges computational poetry and traditional literary practices. Her work at startups Rest Devices and Soofa demonstrates technical innovation in consumer and urban tech.
Benjamin Goldstein is an Assistant Professor at the University of Michigan School for Environment and Sustainability, where he leads the Sustainable Urban-Rural Futures (SURF) lab. His work bridges quantitative methods (life cycle assessment, input-output analysis, geospatial data science) with social science theory to explore urban sustainability, distributive justice, and global supply chains. His research spans urban food systems, agri-commodities, residual resource engineering, and energy systems. Recent trends in his publications focus on urban agriculture's environmental trade-offs, supply chain transparency, and carbon-negative construction materials. He applies data science to map sustainability challenges across urban and rural landscapes while critically analyzing power asymmetries in global industries like beef production and cannabis cultivation. His work emphasizes actionable tools for policymakers and corporations to address environmental justice and resource efficiency.
