report_data.json

{
  "papers": [
    {
      "title": "Artificial intelligence in higher education: the state of the field",
      "authors": [
        "Helen Crompton",
        "Diane Burke"
      ],
      "year": "2023",
      "journal": "International Journal of Educational Technology in Higher Education",
      "doi": "https://doi.org/10.1186/s41239-023-00392-8",
      "pdf_url": "https://educationaltechnologyjournal.springeropen.com/counter/pdf/10.1186/s41239-023-00392-8",
      "citations": 149,
      "source": "Unknown",
      "quartile": "Q1",
      "url": "https://doi.org/10.1186/s41239-023-00392-8",
      "relevance": 0.745,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Helen Crompton & Diane Burke (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education. https://doi.org/https://doi.org/10.1186/s41239-023-00392-8"
    },
    {
      "title": "Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education",
      "authors": [
        "Yoshija Walter"
      ],
      "year": "2024",
      "journal": "International Journal of Educational Technology in Higher Education",
      "doi": "https://doi.org/10.1186/s41239-024-00448-3",
      "pdf_url": "https://educationaltechnologyjournal.springeropen.com/counter/pdf/10.1186/s41239-024-00448-3",
      "citations": 128,
      "source": "Unknown",
      "quartile": "Q1",
      "url": "https://doi.org/10.1186/s41239-024-00448-3",
      "relevance": 0.64,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Yoshija Walter (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education. https://doi.org/https://doi.org/10.1186/s41239-024-00448-3"
    },
    {
      "title": "Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning",
      "authors": [
        "David Baidoo-Anu",
        "Leticia Owusu Ansah"
      ],
      "year": "2023",
      "journal": "Journal of AI",
      "doi": "https://doi.org/10.61969/jai.1337500",
      "pdf_url": "https://doi.org/10.61969/jai.1337500",
      "citations": 120,
      "source": "Unknown",
      "quartile": "Q1",
      "url": "https://doi.org/10.61969/jai.1337500",
      "relevance": 0.6,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "David Baidoo-Anu & Leticia Owusu Ansah (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. Journal of AI. https://doi.org/https://doi.org/10.61969/jai.1337500"
    },
    {
      "title": "Artificial intelligence in education: A systematic literature review",
      "authors": [
        "Shan Wang",
        "Fang Wang",
        "Zhen Zhu",
        "Jingxuan Wang",
        "Tam Tran",
        "Zhao Du"
      ],
      "year": "2024",
      "journal": "Expert Systems with Applications",
      "doi": "https://doi.org/10.1016/j.eswa.2024.124167",
      "pdf_url": "https://doi.org/10.1016/j.eswa.2024.124167",
      "citations": 106,
      "source": "Unknown",
      "quartile": "Q1",
      "url": "https://doi.org/10.1016/j.eswa.2024.124167",
      "relevance": 0.53,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Shan Wang et al. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications. https://doi.org/https://doi.org/10.1016/j.eswa.2024.124167"
    },
    {
      "title": "New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution",
      "authors": [
        "Firuz Kamalov",
        "David Santandreu Calonge",
        "Ikhlaas Gurrib"
      ],
      "year": "2023",
      "journal": "Sustainability",
      "doi": "https://doi.org/10.3390/su151612451",
      "pdf_url": "https://www.mdpi.com/2071-1050/15/16/12451/pdf?version=1692181759",
      "citations": 80,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.3390/su151612451",
      "relevance": 0.4,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Firuz Kamalov et al. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability. https://doi.org/https://doi.org/10.3390/su151612451"
    },
    {
      "title": "A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour",
      "authors": [
        "Melissa Bond",
        "Hassan Khosravi",
        "Maarten de Laat",
        "Nina Bergdahl",
        "Violeta Negrea",
        "Emily Oxley",
        "Phuong Pham",
        "Sin Wang Chong",
        "George Siemens"
      ],
      "year": "2024",
      "journal": "International Journal of Educational Technology in Higher Education",
      "doi": "https://doi.org/10.1186/s41239-023-00436-z",
      "pdf_url": "https://educationaltechnologyjournal.springeropen.com/counter/pdf/10.1186/s41239-023-00436-z",
      "citations": 79,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.1186/s41239-023-00436-z",
      "relevance": 0.395,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Melissa Bond et al. (2024). A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education. https://doi.org/https://doi.org/10.1186/s41239-023-00436-z"
    },
    {
      "title": "Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence",
      "authors": [
        "Grant Cooper"
      ],
      "year": "2023",
      "journal": "Journal of Science Education and Technology",
      "doi": "https://doi.org/10.1007/s10956-023-10039-y",
      "pdf_url": "https://link.springer.com/content/pdf/10.1007/s10956-023-10039-y.pdf",
      "citations": 77,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.1007/s10956-023-10039-y",
      "relevance": 0.385,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Grant Cooper (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology. https://doi.org/https://doi.org/10.1007/s10956-023-10039-y"
    },
    {
      "title": "Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis",
      "authors": [
        "Zied Bahroun",
        "Chiraz Anane",
        "Vian Ahmed",
        "Andrew Zacca"
      ],
      "year": "2023",
      "journal": "Sustainability",
      "doi": "https://doi.org/10.3390/su151712983",
      "pdf_url": "https://www.mdpi.com/2071-1050/15/17/12983/pdf?version=1693276970",
      "citations": 64,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.3390/su151712983",
      "relevance": 0.32,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Zied Bahroun et al. (2023). Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis. Sustainability. https://doi.org/https://doi.org/10.3390/su151712983"
    },
    {
      "title": "ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity",
      "authors": [
        "Christy Boscardin",
        "Brian C. Gin",
        "Polo Black Golde",
        "Karen E. Hauer"
      ],
      "year": "2023",
      "journal": "Academic Medicine",
      "doi": "https://doi.org/10.1097/acm.0000000000005439",
      "pdf_url": "https://www.ets.berkeley.edu/sites/default/files/general/uc_learning_data_principles_final03.05.2018.pdf",
      "citations": 57,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.1097/acm.0000000000005439",
      "relevance": 0.285,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Christy Boscardin et al. (2023). ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity. Academic Medicine. https://doi.org/https://doi.org/10.1097/acm.0000000000005439"
    },
    {
      "title": "Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education",
      "authors": [
        "Ramteja Sajja",
        "Yusuf Sermet",
        "Muhammed Cikmaz",
        "David M. Cwiertny",
        "İbrahim Demir"
      ],
      "year": "2024",
      "journal": "Information",
      "doi": "https://doi.org/10.3390/info15100596",
      "pdf_url": "https://doi.org/10.3390/info15100596",
      "citations": 55,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.3390/info15100596",
      "relevance": 0.275,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Ramteja Sajja et al. (2024). Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education. Information. https://doi.org/https://doi.org/10.3390/info15100596"
    },
    {
      "title": "Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review",
      "authors": [
        "Chien-Chang Lin",
        "Anna Y.Q. Huang",
        "Owen H.T. Lu"
      ],
      "year": "2023",
      "journal": "Smart Learning Environments",
      "doi": "https://doi.org/10.1186/s40561-023-00260-y",
      "pdf_url": "https://slejournal.springeropen.com/counter/pdf/10.1186/s40561-023-00260-y",
      "citations": 52,
      "source": "Unknown",
      "quartile": "Q2",
      "url": "https://doi.org/10.1186/s40561-023-00260-y",
      "relevance": 0.26,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Chien-Chang Lin et al. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments. https://doi.org/https://doi.org/10.1186/s40561-023-00260-y"
    },
    {
      "title": "The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research",
      "authors": [
        "Tariq Alqahtani",
        "Hisham A. Badreldin",
        "Mohammed Alrashed",
        "Abdulrahman Alshaya",
        "Sahar S. Alghamdi",
        "Khalid Bin Saleh",
        "Shuroug A. Alowais",
        "Omar A. Alshaya",
        "Ishrat Rahman",
        "Majed S. Al Yami"
      ],
      "year": "2023",
      "journal": "Research in Social and Administrative Pharmacy",
      "doi": "https://doi.org/10.1016/j.sapharm.2023.05.016",
      "pdf_url": null,
      "citations": 48,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://doi.org/10.1016/j.sapharm.2023.05.016",
      "relevance": 0.24,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Tariq Alqahtani et al. (2023). The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research. Research in Social and Administrative Pharmacy. https://doi.org/https://doi.org/10.1016/j.sapharm.2023.05.016"
    },
    {
      "title": "Managing the Strategic Transformation of Higher Education through Artificial Intelligence",
      "authors": [
        "Babu George",
        "Ontario S. Wooden"
      ],
      "year": "2023",
      "journal": "Administrative Sciences",
      "doi": "https://doi.org/10.3390/admsci13090196",
      "pdf_url": "https://www.mdpi.com/2076-3387/13/9/196/pdf?version=1693319334",
      "citations": 45,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://doi.org/10.3390/admsci13090196",
      "relevance": 0.225,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Babu George & Ontario S. Wooden (2023). Managing the Strategic Transformation of Higher Education through Artificial Intelligence. Administrative Sciences. https://doi.org/https://doi.org/10.3390/admsci13090196"
    },
    {
      "title": "Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions",
      "authors": [
        "Ammar Abulibdeh",
        "Esmat Zaidan",
        "Rawan Abulibdeh"
      ],
      "year": "2024",
      "journal": "Journal of Cleaner Production",
      "doi": "https://doi.org/10.1016/j.jclepro.2023.140527",
      "pdf_url": "https://doi.org/10.1016/j.jclepro.2023.140527",
      "citations": 45,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://doi.org/10.1016/j.jclepro.2023.140527",
      "relevance": 0.225,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Ammar Abulibdeh et al. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production. https://doi.org/https://doi.org/10.1016/j.jclepro.2023.140527"
    },
    {
      "title": "Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities",
      "authors": [
        "Jiahong Su",
        "Davy Tsz Kit Ng",
        "Samuel Kai Wah Chu"
      ],
      "year": "2023",
      "journal": "Computers and Education Artificial Intelligence",
      "doi": "https://doi.org/10.1016/j.caeai.2023.100124",
      "pdf_url": "https://doi.org/10.1016/j.caeai.2023.100124",
      "citations": 42,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://doi.org/10.1016/j.caeai.2023.100124",
      "relevance": 0.21,
      "abstract": "",
      "downloaded": false,
      "file_path": "",
      "apa": "Jiahong Su et al. (2023). Artificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities. Computers and Education Artificial Intelligence. https://doi.org/https://doi.org/10.1016/j.caeai.2023.100124"
    },
    {
      "title": "Citizenship Challenges in Artificial Intelligence Education",
      "abstract": "This chapter addresses the citizenship challenges related to AI in education, particularly concerning students, teachers, and other educational stakeholders in the context of AI integration. We first explore how to foster AI awareness and education, along with various strategies to promote a socio-critical approach to AI training, aiming to identify relevant and ethical uses to prioritise. In the second part, we discuss critical thinking and computational thinking skills that can be mobilised within certain AI-supported educational activities, depending on the degree of creative and transformative engagement those activities require.",
      "authors": [
        "Margarida Romero"
      ],
      "year": "2025",
      "journal": "arXiv Preprint",
      "doi": "",
      "pdf_url": "https://arxiv.org/pdf/2506.18955v1",
      "citations": 0,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://arxiv.org/pdf/2506.18955v1",
      "relevance": 0.6,
      "downloaded": false,
      "file_path": "",
      "apa": "Margarida Romero (2025). Citizenship Challenges in Artificial Intelligence Education. arXiv Preprint."
    },
    {
      "title": "Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program",
      "abstract": "The 7th Symposium on Educational Advances in Artificial Intelligence (EAAI'17, co-chaired by Sven Koenig and Eric Eaton) launched the EAAI New and Future AI Educator Program to support the training of early-career university faculty, secondary school faculty, and future educators (PhD candidates or postdocs who intend a career in academia). As part of the program, awardees were asked to address one of the following \"blue sky\" questions:   * How could/should Artificial Intelligence (AI) courses incorporate ethics into the curriculum?   * How could we teach AI topics at an early undergraduate or a secondary school level?   * AI has the potential for broad impact to numerous disciplines. How could we make AI education more interdisciplinary, specifically to benefit non-engineering fields?   This paper is a collection of their responses, intended to help motivate discussion around these issues in AI education.",
      "authors": [
        "Eric Eaton",
        "Sven Koenig",
        "Claudia Schulz",
        "Francesco Maurelli",
        "John Lee",
        "Joshua Eckroth",
        "Mark Crowley",
        "Richard G. Freedman",
        "Rogelio E. Cardona-Rivera",
        "Tiago Machado",
        "Tom Williams"
      ],
      "year": "2017",
      "journal": "arXiv Preprint",
      "doi": "",
      "pdf_url": "https://arxiv.org/pdf/1702.00137v1",
      "citations": 0,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://arxiv.org/pdf/1702.00137v1",
      "relevance": 0.6,
      "downloaded": false,
      "file_path": "",
      "apa": "Eric Eaton et al. (2017). Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program. arXiv Preprint."
    },
    {
      "title": "An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates",
      "abstract": "Teaching artificial intelligence (AI) is challenging. It is a fast moving field and therefore difficult to keep people updated with the state-of-the-art. Educational offerings for students are ever increasing, beyond university degree programs where AI education traditionally lay. In this paper, we present an experience report of teaching an AI course to business executives in the United Arab Emirates (UAE). Rather than focusing only on theoretical and technical aspects, we developed a course that teaches AI with a view to enabling students to understand how to incorporate it into existing business processes. We present an overview of our course, curriculum and teaching methods, and we discuss our reflections on teaching adult learners, and to students in the UAE.",
      "authors": [
        "David Johnson",
        "Mohammad Alsharid",
        "Rasheed El-Bouri",
        "Nigel Mehdi",
        "Farah Shamout",
        "Alexandre Szenicer",
        "David Toman",
        "Saqr Binghalib"
      ],
      "year": "2022",
      "journal": "arXiv Preprint",
      "doi": "",
      "pdf_url": "https://arxiv.org/pdf/2202.01281v1",
      "citations": 0,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://arxiv.org/pdf/2202.01281v1",
      "relevance": 0.6,
      "downloaded": false,
      "file_path": "",
      "apa": "David Johnson et al. (2022). An Experience Report of Executive-Level Artificial Intelligence Education in the United Arab Emirates. arXiv Preprint."
    },
    {
      "title": "Use Scenarios & Practical Examples of AI Use in Education",
      "abstract": "This report presents a set of use scenarios based on existing resources that teachers can use as inspiration to create their own, with the aim of introducing artificial intelligence (AI) at different pre-university levels, and with different goals. The Artificial Intelligence Education field (AIEd) is very active, with new resources and tools arising continuously. Those included in this document have already been tested with students and selected by experts in the field, but they must be taken just as practical examples to guide and inspire teachers creativity.",
      "authors": [
        "Dara Cassidy",
        "Yann-Aël Le Borgne",
        "Francisco Bellas",
        "Riina Vuorikari",
        "Elise Rondin",
        "Madhumalti Sharma",
        "Jessica Niewint-Gori",
        "Johanna Gröpler",
        "Anne Gilleran",
        "Lidija Kralj"
      ],
      "year": "2023",
      "journal": "arXiv Preprint",
      "doi": "",
      "pdf_url": "https://arxiv.org/pdf/2309.12320v1",
      "citations": 0,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://arxiv.org/pdf/2309.12320v1",
      "relevance": 0.6,
      "downloaded": false,
      "file_path": "",
      "apa": "Dara Cassidy et al. (2023). Use Scenarios & Practical Examples of AI Use in Education. arXiv Preprint."
    },
    {
      "title": "Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments",
      "abstract": "This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces i) VLE, a novel dataset that consists of content and video based features extracted from publicly available scientific video lectures coupled with implicit and explicit signals related to learner engagement, ii) two standard tasks related to predicting and ranking context-agnostic engagement in video lectures with preliminary baselines and iii) a set of experiments that validate the usefulness of the proposed dataset. Our experimental results indicate that the newly proposed VLE dataset leads to building context-agnostic engagement prediction models that are significantly performant than ones based on previous datasets, mainly attributing to the increase of training examples. VLE dataset's suitability in building models towards Computer Science/ Artificial Intelligence education focused on e-learning/ MOOC use-cases is also evidenced. Further experiments in combining the built model with a personalising algorithm show promising improvements in addressing the cold-start problem encountered in educational recommenders. This is the largest and most diverse publicly available dataset to our knowledge that deals with learner engagement prediction tasks. The dataset, helper tools, descriptive statistics and example code snippets are available publicly.",
      "authors": [
        "Sahan Bulathwela",
        "Meghana Verma",
        "Maria Perez-Ortiz",
        "Emine Yilmaz",
        "John Shawe-Taylor"
      ],
      "year": "2022",
      "journal": "arXiv Preprint",
      "doi": "",
      "pdf_url": "https://arxiv.org/pdf/2207.01504v1",
      "citations": 0,
      "source": "Unknown",
      "quartile": "Q3",
      "url": "https://arxiv.org/pdf/2207.01504v1",
      "relevance": 0.6,
      "downloaded": false,
      "file_path": "",
      "apa": "Sahan Bulathwela et al. (2022). Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments. arXiv Preprint."
    },
    {
      "title": "Training the next generation of physicians for artificial intelligence-assisted clinical neuroradiology: ASNR MICCAI Brain Tumor Segmentation (BraTS) 2025 Lighthouse Challenge education platform",
      "abstract": "High-quality reference standard image data creation by neuroradiology experts for automated clinical tools can be a powerful tool for neuroradiology & artificial intelligence education. We developed a multimodal educational approach for students and trainees during the MICCAI Brain Tumor Segmentation Lighthouse Challenge 2025, a landmark initiative to develop accurate brain tumor segmentation algorithms. Fifty-six medical students & radiology trainees volunteered to annotate brain tumor MR images for the BraTS challenges of 2023 & 2024, guided by faculty-led didactics on neuropathology MRI. Among the 56 annotators, 14 select volunteers were then paired with neuroradiology faculty for guided one-on-one annotation sessions for BraTS 2025. Lectures on neuroanatomy, pathology & AI, journal clubs & data scientist-led workshops were organized online. Annotators & audience members completed surveys on their perceived knowledge before & after annotations & lectures respectively. Fourteen coordinators, each paired with a neuroradiologist, completed the data annotation process, averaging 1322.9+/-760.7 hours per dataset per pair and 1200 segmentations in total. On a scale of 1-10, annotation coordinators reported significant increase in familiarity with image segmentation software pre- and post-annotation, moving from initial average of 6+/-2.9 to final average of 8.9+/-1.1, and significant increase in familiarity with brain tumor features pre- and post-annotation, moving from initial average of 6.2+/-2.4 to final average of 8.1+/-1.2. We demonstrate an innovative offering for providing neuroradiology & AI education through an image segmentation challenge to enhance understanding of algorithm development, reinforce the concept of data reference standard, and diversify opportunities for AI-driven image analysis among future physicians.",
      "authors": [
        "Raisa Amiruddin",
        "Nikolay Y. Yordanov",
        "Nazanin Maleki",
        "Pascal Fehringer",
        "Athanasios Gkampenis",
        "Anastasia Janas",
        "Kiril Krantchev",
        "Ahmed Moawad",
        "Fabian Umeh",
        "Salma Abosabie",
        "Sara Abosabie",
        "Albara Alotaibi",
        "Mohamed Ghonim",
        "Mohanad Ghonim",
        "Sedra Abou Ali Mhana",
        "Nathan Page",
        "Marko Jakovljevic",
        "Yasaman Sharifi",
        "Prisha Bhatia",
        "Amirreza Manteghinejad",
        "Melisa Guelen",
        "Michael Veronesi",
        "Virginia Hill",
        "Tiffany So",
        "Mark Krycia",
        "Bojan Petrovic",
        "Fatima Memon",
        "Justin Cramer",
        "Elizabeth Schrickel",
        "Vilma Kosovic",
        "Lorenna Vidal",
        "Gerard Thompson",
        "Ichiro Ikuta",
        "Basimah Albalooshy",
        "Ali Nabavizadeh",
        "Nourel Hoda Tahon",
        "Karuna Shekdar",
        "Aashim Bhatia",
        "Claudia Kirsch",
        "Gennaro D'Anna",
        "Philipp Lohmann",
        "Amal Saleh Nour",
        "Andriy Myronenko",
        "Adam Goldman-Yassen",
        "Janet R. Reid",
        "Sanjay Aneja",
        "Spyridon Bakas",
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