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Seth Lloyd is a Professor of Mechanical Engineering at the Massachusetts Institute of Technology (MIT), where he directs the Center for Extreme Quantum Information Theory (xQIT). His work bridges theoretical physics, quantum information science, and complex systems theory. He has made significant contributions to the foundations of quantum computing and quantum information processing. Lloyd received his education from prestigious institutions: B.A. from Harvard College (1982) M.Phil from Cambridge University (1984) as a Marshall Scholar Ph.D. in Physics from Rockefeller University (1988) Lloyd's research focuses on quantum information science, particularly quantum computation and quantum communications. He has pioneered work in quantum analog computation, quantum error correction, and quantum metrology. His research explores how quantum mechanics can be harnessed for information processing tasks, with applications ranging from quantum computing to understanding biological processes like photosynthesis. Lloyd is also known for his work on complex systems and the relationship between information and physical systems, arguing that the universe itself can be viewed as a quantum computer. His publication record shows a clear progression from foundational quantum computing work to applications in quantum machine learning and quantum biology. The most recent articles reveal a strong focus on quantum algorithms for machine learning, quantum metrology, and the intersection of quantum mechanics with biological systems. His work on the HHL algorithm for solving linear systems has been particularly influential in quantum machine learning, though its practical advantages have been debated following Ewin Tang's classical algorithms. Lloyd has received numerous scientific honors: Lindbergh Fellow (1994) Finmeccanica Professorship (1996) Edgerton Prize (2001) Fellow of the American Physical Society (2007) Quantum Communication Award (2012) International Quantum Communication Award (2012) Throughout his career, Lloyd has mentored numerous students and researchers in quantum information science. He has secured significant research funding for his work in quantum computing and complex systems. His research has been supported by various foundations and government agencies interested in advancing quantum technologies. Lloyd has also been involved in interdisciplinary collaborations, particularly with biologists studying quantum effects in photosynthesis. Lloyd directs the Center for Extreme Quantum Information Theory (xQIT) at MIT, which brings together researchers from physics, computer science, and engineering to tackle fundamental challenges in quantum information processing. His lab has been at the forefront of developing theoretical frameworks for quantum computing and exploring practical implementations of quantum information protocols.

• Quantum Information Science
• Quantum Computation
• Quantum Communications
• +5 more

Amartya Sanyal is a Tenure Track Assistant Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Machine Learning. He also serves as an Adjunct Professor at the Indian Institute of Technology Kanpur (2023–2025). His research focuses on critical areas of AI safety, data privacy, and robust learning. University: University of Copenhagen Department: Department of Computer Science Academic Rank: Assistant Professor Adjunct Role: IIT Kanpur (2023–2025) His work addresses challenges like differential privacy , data poisoning attacks , machine unlearning , and robust mixture learning . Recent publications analyze privacy-preserving techniques for large language models, fairness in collective action algorithms, and certified data release mechanisms. Amartya has received the Villum Young Investigator Award (2025). His research outputs emphasize online learning , adversarial robustness , and privacy-utility tradeoffs through rigorous theoretical frameworks and practical implementations. Scientific Award: Villum Young Investigator Award His collaborations span institutions like IIT Kanpur and involve interdisciplinary projects with industry partners. Current activities include talks on privacy with correlated data and machine unlearning advancements.

• Machine Learning
• Data Privacy
• Robust Learning
• +3 more

Torben M. Andersen is a Professor at the Department of Economics and Business Economics, Aarhus University. He holds an M.Sc. from the London School of Economics (1981), a Lic. Oecon from Aarhus University (1994), and a PhD from CORE, Université Catholique de Louvain (1986). His research focuses on the Nordic welfare model, public economics, labour economics, and pension economics. He has published over 400 articles in top journals and contributed to policy advisement for Denmark, the EU, OECD, and the World Bank. He currently chairs the DREAM modelling group, the Economic Council for Greenland, and the Danish pension fund ATP. He also serves on boards of Aarhus University Research Foundation, Systemic Risk Council Faroe Islands, and others. Key research areas include welfare state sustainability, public expenditure prioritization, and pension reform impacts. His recent work explores mortality risk hedging and wealth inequality dynamics. He is a fellow at CEPR, IZA, and CESifo.

• Nordic welfare model
• Public Economics
• Labour Economics
• +3 more

Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.

• Efficient Machine Learning
• Deep Learning
• Embedded Systems
• +12 more

Charlotte Jacobsen is a Professor and Head of the Research Group for Bioactives – Analysis and Application at the National Food Institute, Technical University of Denmark (DTU). Her research focuses on lipid oxidation, antioxidants, and sustainable utilization of marine resources. She leads multiple interdisciplinary projects and supervises PhD students in food science and technology. Research Interests: Antioxidant chemistry in food systems Oxidative stability of omega-3 fatty acids Valorization of fish and seafood by-products Microalgae as sustainable sources of bioactives Functional foods and nutraceuticals Green extraction technologies Recent Research Trends: Her recent publications (2021–2025) reflect a strong focus on sustainable food systems, including the recovery of bioactive compounds from fish side-streams, stabilization of omega-3 lipids, development of anti-obesity peptides from seaweed, and cultivation of microalgae using industrial waste streams. The work spans food chemistry, marine biotechnology, and green processing, with applications in functional foods and nutrition. Scientific Awards: Danisco Award, 2003 Edwin Frankel Best Paper Award, 2010 and 2011 La Médaille Chevreul, 2010 Marcuse Lecturer grant, 1999 Advising and Grants: Professor Jacobsen actively supervises PhD students and leads multiple funded research projects, including 'Utilization of fish side-streams for production of novel food ingredients' and 'Sustainable Production of Microalgae Proteins'. She is involved in national and international collaborations, securing research funding for projects on omega-3 extraction, microalgae cultivation, and seafood quality. Labs and Teams: She leads the Research Group for Bioactives – Analysis and Application at DTU, which is part of the DTU Microbes Initiative. The group specializes in analytical methods for bioactive compounds, lipid oxidation analysis, and development of sustainable food ingredients.

• Antioxidant Chemistry
• Lipid Oxidation
• Omega-3 Fatty Acids
• +7 more

Manex Aguirrezabal Zabaleta is an Associate Professor in the Department of Nordic Studies and Linguistics at the University of Copenhagen. He previously held positions as a Postdoc (2017-2019) and Assistant Professor at the same institution. His educational background includes: PhD in Natural Language Processing from the University of the Basque Country (UPV/EHU), conducted at the IXA NLP group. Master's degree in Natural Language Processing from UPV/EHU. Bachelor's degree in Computer Science (5 years) from UPV/EHU. Dr. Aguirrezabal's research focuses on the computational analysis of poetry , particularly stress patterns in English. He explores whether computers can effectively analyze poetic structures, a field with roots in the 1980s but revitalized by modern techniques. Additionally, he investigates language generation , computational morphology and phonology , and finite-state methods . His work bridges traditional linguistic inquiry with cutting-edge natural language processing. Recent publications (2023-2024) demonstrate a diverse engagement with computational linguistics, including poetry generation, multimodal corpus development, clickbait analysis, and fact-checking. His research often employs zero-shot learning and language models, reflecting current trends in AI-driven linguistic analysis. He has contributed to international collaborations such as ParlaMint (multilingual parliamentary corpora) and the GEHM Zoom corpus. While specific grant details are not provided, his active publication record indicates ongoing research support. Dr. Aguirrezabal maintains a strong connection to his Basque heritage, having pursued his early education in the Basque language.

• Natural Language Processing
• Computational Linguistics
• Poetry Analysis
• +4 more

Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)

• Power Electronics
• Wind Turbines
• Photovoltaic (PV) Systems
• +6 more

Professor John W. Edmunds is a leading academic in Infectious Disease Modelling at the London School of Hygiene and Tropical Medicine (LSHTM). Holding a Professor position since 2013 and serving as Dean of the Faculty of Epidemiology and Population Health (2013-2019), he combines mathematical, statistical, and economic models to inform public health policy. His part-time role at the Health Protection Agency (HPA) since 2008 underscores his policy advisory contributions. PhD in Infectious Disease Modelling (Imperial College, 1994) MSc in Health Economics (University of York, 1995) BSc in Biology (Imperial College, 1989) His research focuses on understanding disease transmission and optimizing control strategies. He has pioneered methods integrating social contact surveys , participatory surveillance (e.g., Influenzanet), and economic analysis to evaluate vaccines and interventions. Recent work includes SARS-CoV-2 dynamics , Ebola spatial forecasting , and typhoid vaccine prioritization . His 15 most recent publications highlight social contact patterns (Reconnect, CoMix studies), vaccine impact (HPV, typhoid), and real-time outbreak analytics (Ebola, cholera). Key trends include digital epidemiology , behavioral surveillance , and cross-country modeling for global health. Knighthood (2024) for services to epidemiology Weldon Memorial Prize (2022) for biostatistics contributions FMedSci (2018) for medical science excellence OBE (2016) for public service As an educator, he teaches "Modelling and the Dynamics of Infectious Diseases" and co-organizes "Pandemics: Emergence, Spread and Response" . Current grants include National Institute for Health and Care Research projects on post-pandemic surveillance and Bill & Melinda Gates Foundation funding for polio eradication. He leads collaborations with the Centre for Mathematical Modelling of Infectious Diseases , Vaccine Centre , and Health in Humanitarian Crises Centre , while advising UK and WHO committees on zoonotic influenza , variants , and testing programs .

• Infectious Disease Modelling
• Epidemiology
• Public Health Policy
• +6 more

Diego Garlaschelli is Professor of Theoretical Physics at the IMT School for Advanced Studies in Lucca, Italy, and at the Lorentz Institute for Theoretical Physics, University of Leiden, the Netherlands. He leads the NETWORKS research unit at IMT and the Econophysics and Network Theory group at Leiden. He is also an external faculty member at the Complexity Science Hub in Vienna and an associate member of the Enrico Fermi Research Center in Rome. His affiliations reflect a strong international and interdisciplinary research profile in network science and statistical physics. He holds a master's degree in theoretical physics from the University of Rome III (2001) and a PhD in Physics from the University of Siena (2005). His postdoctoral experience includes positions at the Australian National University, the University of Siena, the University of Oxford, and the Sant’Anna School of Advanced Studies in Pisa. Garlaschelli’s research spans network theory, statistical physics, econophysics, financial complexity, ecological networks, and social dynamics. He applies maximum entropy models, information theory, and random graph frameworks to understand complex real-world systems. His teaching includes courses in Network Theory, Econophysics, and Complex Systems at both PhD and MSc levels. The 15 most recent publications highlight a consistent focus on network reconstruction, ensemble inequivalence, renormalization, and applications to financial and socio-economic systems. Key themes include statistical inference in networks, resilience, and multi-scale modeling, with publications in top journals such as Nature Reviews Physics , Physics Reports , Science , and Physical Review Letters . His scientific awards include the Best Paper Award at the 6th International Workshop on Self-Organizing Systems (2012) and the Jan Kijne Prize (2013) as supervisor. He has secured multiple grants from NWO, the European Union, and the Royal Society, and has supervised over 40 students at PhD, master’s, and bachelor’s levels. He also mentors postdocs and visiting scientists. Garlaschelli leads and organizes major international workshops and schools in network science and complex systems. He serves on scientific committees and is an active referee for journals like Nature and Physical Review Letters , as well as funding agencies including the ERC and NWO.

• Network Theory
• Statistical Physics
• Econophysics
• +7 more

Timo Minssen is Professor of Law at the University of Copenhagen (UCPH) and the Founding Director of UCPH's Center for Advanced Studies in Bioscience Innovation Law (CeBIL). He also holds affiliations as an LML Research Affiliate at the University of Cambridge and an Inter-CeBIL Research Affiliate at Harvard Law School's Petrie-Flom Centre. With extensive expertise in Intellectual Property, Competition, and Regulatory Law, Minssen focuses on the legal aspects of emerging health and life science technologies, including genome editing, big data, artificial intelligence, and quantum technology. His educational background includes a German law degree (Staatsexamen) from Georg-August-University in Göttingen, and Swedish biotech & IPR related LL.M., LL.Lic., and LL.D. degrees from Lund University and Uppsala University. His PhD thesis on the patentability of biopharmaceutical technology in the US & Europe received the prestigious Swedish King Oscar award. 2024: TUM Global Visiting Professor, Technical University of Munich (Germany) 2016: Visiting Research Fellow, University of Cambridge (UK) 2014: Visiting Research Fellow, University of Oxford (UK) 2013-14: Visiting Scholar, Harvard Law School (US) 2012: LL.D. - Doctor of Laws (Swedish "juris doktor"), EU/US patent law, Lund University, Sweden Minssen's research spans AI & Big Data in Health & Life Sciences, Sustainable and responsible innovation & tech transfer, Pharmaceutical-, Life Science- & Biotech Law, Comparative European & US Patent Law, Intellectual Property Law & Open Innovation, and EU Competition- & US Antitrust Law. His work addresses legal issues throughout the lifecycle of health and life science products and processes, from R&D regulation to technology transfer and commercialization. His extensive publication record includes 7 books and over 200 articles and book chapters published in leading journals such as Science, Nature Biotechnology, JAMA, and Harvard Business Review. His research has been featured in The Economist, Financial Times, and other major media outlets. Minssen's recent work shows a strong focus on AI regulation, quantum technology law, and data governance in health contexts, reflecting the evolving landscape of technology and law. Scientific Awards and Recognition King Oscar award for best Jur. Dr. thesis (2014) Jorcks Fonds Forsknings Pris (Jorck's Foundation Research Prize) (2017) Awapatent Research Prize (2009) Max Planck Research Scholarship (2005) Visiting Scholar appointments at Harvard Law School, University of Oxford, and University of Cambridge Recipient of a Novo Nordisk Foundation Grant for a "Collaborative Research Program in Biomedical Innovation Law" (2018) As an advisor, Minssen serves international organizations including the WHO, WIPO, and EU Commission. He has supervised numerous PhD students in areas including pharmaceutical law, biotechnology patents, and antimicrobial resistance. His current research projects include the Novo Nordisk Foundation's International Collaborative Bioscience Innovation & Law (Inter-CeBIL) Programme (50 million DKK), CLASSICA: EU Horizon Project on AI-assisted surgery, and AI@Care: Law and Ethics and Algorithmic Bias in Healthcare. Minssen leads the Center for Advanced Studies in Bioscience Innovation Law (CeBIL), which serves as a hub for interdisciplinary research on the intersection of law, technology, and innovation in the health and life sciences. The center collaborates with institutions worldwide to address pressing legal challenges in emerging technologies.

• Intellectual Property Law
• Competition Law
• Regulatory Law
• +4 more

Jacob Østergaard is a Professor and Head of the Division for Power and Energy Systems at DTU Wind and Energy Systems, Technical University of Denmark. His research focuses on renewable energy systems, offshore wind power hubs, and quantum computing applications in energy systems. He leads initiatives like EnergyLab Nordhavn and PowerLabDK, emphasizing collaboration between academia and industry. Education: MSc in Electrical Engineering from DTU (1989–1995). External positions include roles at Research Institute of the Danish Electric Utilities and Ørsted (now SK Energy). Research Interests: Power system stability, flexibility markets, offshore wind energy, quantum computing in energy systems, Power-to-X, and energy storage. He advocates for integrated, market-based energy systems to achieve the green transition. Publications highlight quantum computing for grid optimization, offshore energy hubs, and Denmark’s energy island strategy. Recent work emphasizes scientific advice for energy policy and green hydrogen production. Awards: A. Angelo’s Prize (1996), AEG Electron Prize (2007), Danish Design Award (2019), and EU RESponsible Island Prize (2020). Advising and Grants: Supervises PhD students in grid integration and control. Active in projects like OEH (Offshore Energy Hubs) and BOSS (Battery Energy Storage System). His work drives Denmark’s energy policy through roles on Energinet’s board and the Danish Energy Commission. Labs/Teams: Leads PowerLabDK and EnergyLab Nordhavn, experimental facilities for smart grid and energy system research.

• Renewable Energy Systems
• Power System Stability
• Flexibility Markets
• +8 more

Pedro Monteiro is an Assistant Professor (tenure track) in the Department of Organization at Copenhagen Business School. His research focuses on organizational expertise development, bureaucratic systems, and qualitative methods, with fieldwork in engineering firms and the public sector. Academy of Management Annals Best Article Award Louis Pondy Award recipient Max Boisot Award winner Poets and Quants Top 50 Undergraduate Business Professors 2024 Monteiro's work spans organizational theory, cybersecurity coordination, and migrant expertise challenges. He serves as Communications Editor for Administrative Science Quarterly and contributes to qualitative research communities through co-founding the Talking About Organizations Podcast and Ethnography Atelier. His research projects include a Gothenburg University collaboration funded by Otto Mønsteds Fond (2023). Current teaching includes Organizational Behavior at BSc level and Strategy, Organization & Leadership at MSc level.

• Organization Theory
• Bureaucracy and Organizational Forms
• Collaboration, Coordination, and Cooperation in Organizations
• +7 more

Ole Wæver is a Professor of International Relations at the Department of Political Science, University of Copenhagen. He founded the Centre for Advanced Security Theory (CAST) and directs the Centre for Resolution of International Conflicts (CRIC) . His work spans security theory, conceptual history, and sociology of science, with global recognition for developing the Copenhagen School of securitization theory. Primary Research Areas: International Relations, Security Studies, Climate Change, Religion/Secularism, Conflict Analysis Notable Contributions: Pioneering securitization theory, interdisciplinary analysis of security concepts, and theoretical developments in regional security complexes. His recent work explores the intersection of technology, philosophy of language, and security. Scientific Awards: Royal Danish Academy of Sciences and Letters (2007) Carlsberg Foundation Research Prize (2012) Knight of the Order of Dannebrog (2014) Hesbjerg Foundation Peace Prize (2015) Honorary Doctorate, University of Turku (2015) Publications: Authored and co-authored influential books such as Security: A New Framework for Analysis and Regions and Powers , and contributed to leading journals including International Organization , Security Dialogue , and Millennium .

• International Relations
• Security Theory
• Conceptual History
• +7 more

Jesper Rangvid is a Professor of Finance and Director of the Pension Research Centre (PeRCent) at Copenhagen Business School (CBS), where he also serves as Associate Dean of the Executive MBA program . His research focuses on financial markets, macroeconomics, financial crises, household finance, and mutual funds. He has authored influential works such as How Low Interest Rates Change the World (Oxford University Press, 2025) and From Main Street to Wall Street (Oxford University Press, 2021), exploring topics like interest rate trends, economic growth, and policy impacts. He chairs the Council for Return Expectations and holds board positions at Formuepleje, Advantage Investment Partners, and Finansiel Stabilitet, among others. His advisory roles include Levring & Levring and projects for Danish institutions like Forenet Kredit and BankInvest. Recent research highlights include analyzing Denmark’s pension system reforms, fiscal-monetary policy interactions, and the implications of low interest rates on global economies. Rangvid’s publications combine rigorous academic analysis with policy relevance, addressing topics like dividend predictability, economic growth’s impact on asset returns, and the behavior of professional investors. His work often bridges theoretical frameworks with empirical data, offering insights into macro-financial linkages and policy design.

• Financial markets and the macroeconomy
• International finance
• Financial crises
• +2 more

Tina Eliassi-Rad is Professor and the Inaugural Joseph E. Aoun Chair at Khoury College of Computer Sciences, Northeastern University in Boston. She serves as Core Faculty at the Network Science Institute and holds External Faculty positions at both the Santa Fe Institute and Vermont Complex Systems Institute. Additionally, she maintains Affiliated Faculty status across six Northeastern University institutes including the NULab for Digital Humanities and Computational Social Science, Global Resilience Institute, Cybersecurity and Privacy Institute, Institute for Experiential AI, and Internet Democracy Initiative. Her research spans: Data Mining & Machine Learning Network Science & Complex Systems Artificial Intelligence & Society She leads two major research initiatives: Trustworthy Network Science , which addresses explainability, transparency, stability, and robustness in network science ML algorithms; and Just Machine Learning , which examines broader complex systems where ML operates to understand and mitigate risks. Her work bridges theoretical foundations with societal applications. Dr. Eliassi-Rad's publication record demonstrates consistent focus on applying network science to critical societal challenges. Her recent research examines pandemic mobility patterns and cybersecurity threats using network-based approaches that combine epidemiological modeling with network analysis techniques. She actively mentors doctoral students through her RADLAB research group, currently advising PhD candidates Wan He (Network Science) and David Liu (Computer Science), along with PhD students Zohair Shafi and Samantha Dies (Computer Science). Her research has secured funding from prestigious organizations including the National Science Foundation, Department of Defense, Defense Advanced Research Projects Agency, Army Research Lab, and others. As leader of RADLAB, she directs research at the intersection of data science, network analysis, and societal impact, with particular emphasis on ensuring that technical advances in AI and network science serve societal needs responsibly and equitably.

• Data Mining & Machine Learning
• Network Science & Complex Systems
• Artificial Intelligence & Society
• +2 more