Find Academic Supervisors

Shane Dawson is the Executive Dean of UniSA Education Futures and Professor of Learning Analytics at the University of South Australia. His work bridges social network analysis and learner interaction data to enhance teaching quality and educational outcomes. Affiliation : University of South Australia Research Focus : Learning Analytics, Curriculum Mapping, K-12 Decision-Making Systems, and AI in Education Recent Research Trends : Shane’s 2025 publications emphasize generative AI for curriculum analytics, ethical considerations in K-12 dashboards, and longitudinal graduate attribute monitoring. His articles often integrate psychometric models, social network tools, and open-source software like OVAL and SNAPP . Advising and Collaboration : As a co-developer of key learning analytics tools and a supervisor for research students, he collaborates globally with institutions such as Johns Hopkins University and Shahid Beheshti University of Medical Sciences. Labs and Teams : Shane leads UniSA’s Teaching Innovation Unit and is a founding member of the Society for Learning Analytics Research , driving institutional and international initiatives in educational technology.

• Learning Analytics
• Educational Data Mining
• Curriculum Development
• +2 more

Dr. Sabine Graf is a Full Professor at the School of Computing and Information Systems, Athabasca University. She holds a PhD in Computing and Information Systems from Vienna University of Technology (2007) and has been a faculty member since 2009. Her research focuses on user adaptive systems, learning/academic analytics, personalization, and game-based learning, with over $2.3M in external funding and 130+ peer-reviewed publications (cited 8,200+ times). She leads the OMEGA+ educational game project and the User Adaptive Systems (UAS) research cluster. Education: PhD in Computing and Information Systems, Vienna University of Technology, 2007 MSc in Computing and Information Systems, University of Vienna, 2003 Research Interests: Dr. Graf specializes in making learning systems more intelligent through adaptive interfaces, AI-driven recommendations, and data analytics. Her work bridges educational technology, artificial intelligence, and collaborative learning. Recent projects include developing OMEGA+, analyzing student behavior in online courses, and enhancing adaptive learning systems with context-aware features. Grants & Funding: NSERC Discovery Grant ($205,000), 2020 CFI John R. Evans Leaders Fund ($164,573), 2020 AU IDEA Lab Grant ($5,000), 2021 Multiple Mitacs Globalink Internships, NSERC awards, and AU-funded projects. Advising & Team: Dr. Graf has mentored over 30 students, including PhD, MSc, and postdoctoral fellows. Notable advisees include Moustafa Mahmoud (NSERC Scholar) and Mohammad Belghis-Zadeh (3MT Competition winner). The research team collaborates globally, with members from Brazil, Taiwan, Spain, and beyond. Labs & Initiatives: The Academic Analytics Tool (AAT) project and the OMEGA+ game platform are central to her work. The UAS cluster connects researchers worldwide to advance adaptive systems research.

• Educational Technology
• User Adaptive Systems
• Learning Analytics
• +7 more

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +6 more

Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin , where she serves as Director of Graduate Research and Co-Lead of the SFI Centre for Research Training in Machine Learning (ML-Labs). She holds concurrent appointments as an SFI Funded Investigator at the Insight Centre for Data Analytics and VistaMilk SFI Research Centre . Her academic journey includes postdoctoral research at Insight Centre, Cork Constraint Computation Centre (4C), and Aarhus University's Bioinformatics Research Centre (BiRC). Education: BSc in Computer Science, University of Bucharest, Romania MSc and PhD in Informatics, Max-Planck Institute for Informatics, Germany Dr. Ifrim specializes in scalable predictive modeling for diverse applications including: Sequence learning (DNA analysis, time series) Real-time prediction for streaming data (news/social media, energy) Interpretable machine learning models Knowledge graph exploitation (WordNet/Yago, Naga) Wearable sensor data analysis (sports science, health monitoring) Energy price forecasting for sustainable systems Her recent publications focus on time series explainability (TSHAP, tsCaptum), multivariate analysis (scalable channel selection), and healthcare applications (fall detection, walking speed estimation). Key contributions include open-source tools like SEQL (sequence learner) and Twitter-Topics (event detection). Scientific Awards: Winner of SNOW@WWW14 Data Challenge As Director of Graduate Research, she oversees advanced academic training while leading funded projects at the intersection of machine learning , real-time analytics , and domain-specific applications in agriculture, healthcare, and digital journalism. Her research group maintains active GitHub repositories with open-source implementations.

• Machine Learning
• Time Series Analysis
• Text Mining
• +7 more

Aysegul Liman-Kaban serves as an Assistant Professor in ICT/Digital Learning STEM Education at Maynooth University. Her work focuses on integrating immersive technologies like augmented reality, gamification, and AI into educational practices. She actively supervises PhD students and leads international research projects such as MIXAP-EU and From AI Anxiety to Empowerment. Education: Not explicitly stated in provided text Her research interests span: Immersive learning technologies (AR/XR, digital escape games) AI in education and generative AI applications Teacher digital competencies and professional development Flipped learning and multimedia pedagogy Ethical challenges in AI research Blended learning practices Recent publications demonstrate a focus on gamification, mixed reality, and AI applications in education, with methodological expertise in structural equation modeling, mixed methods research, and task-based learning analysis. She contributes to journals like Smart Learning Environments and Higher Education Quarterly . Key activities include: Organizing international conferences on STEAM education Leading EU-funded research on immersive learning tools Developing open-source educational technologies Pioneering generative AI integration frameworks

• Immersive Learning (AR/XR/Gamification)
• STEM Education
• Teacher Digital Competencies
• +7 more

Kirsty Kitto is an Associate Professor at the University of Technology Sydney in the Learning Design and Technology Unit. With a background in theoretical physics and computer science, her research focuses on developing quantum-inspired models of contextuality to understand complex human behavior in educational systems. She explores the intersection of Artificial Intelligence (AI) , Learning Analytics , and Educational Theory , seeking to bridge the divide between big data and pedagogical frameworks. Current Appointments : Associate Professor (2020-present), Senior Lecturer (2017-2020) Past Academic Roles : Senior Research Fellow (QUT), Senior Lecturer (QUT), Associate Lecturer (Flinders University) Her funded research includes projects on: Quantum models in cognitive systems (ARC Fellowship DP1094974) AI literacy in digital workplaces (IEEE Transactions study) Contextual learning analytics (DVC Education and Students Division) Skills passports for lifelong learning (UMAP 2024 paper) Kitto's recent work examines human-AI interaction in writing assessment, data storytelling for teacher-centered analytics, and causal modeling to strengthen educational theory-data connections. She actively supervises Masters and PhD students and contributes to policy debates through government submissions on generative AI in education. Her methodology combines mathematical formalism with sociotechnical analysis to address educational complexity.

• Cognitive Science
• Quantum Theory in Information Modeling
• Learning Analytics
• +6 more

Douglas H Fisher is an Associate Professor of Computer Science and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on artificial intelligence, particularly machine learning, and computational sustainability. He holds a Ph.D., M.S., and B.S. in Computer Science from the University of California - Irvine. His work bridges AI with societal challenges, emphasizing sustainability, education technology, and cognitive modeling. Notable areas include integrating sustainability into computing curricula, leveraging AI for peer review systems (pReview), and exploring bias mitigation in neural networks. He has contributed to foundational machine learning techniques, such as rule induction for medical data analysis and decision tree optimization. Fisher's research spans interdisciplinary applications: from geospatial water resource modeling to MOOCs' social incentives. His educational contributions include blended learning frameworks and open educational resources advocacy. He has authored over 100 publications across AI, sustainability, and education, reflecting a commitment to both technical innovation and societal impact.

• Artificial Intelligence
• Machine Learning
• Computational Sustainability
• +3 more

Torsten Steinhoff is a Professor of Didactics of the German Language at the Department of Germanic Studies, University of Siegen, Faculty of Arts and Humanities. His research and teaching focus on theoretical, methodological, and empirical aspects of language acquisition and instruction from elementary to university levels. His primary research interests include: Writing didactics (Schreibdidaktik) Vocabulary didactics (Wortschatzdidaktik) Language-specific and disciplinary learning (Sprache im Fach) Digital communication and AI in education Development of complex learning arrangements (Lernarrangements) Steinhoff investigates how digital tools like ChatGPT can be integrated into writing instruction, promoting argumentative writing through structured learning tasks. His recent work (2023–2025) analyzes human-AI collaboration in writing, proposing models such as GPT as Ghost, Partner, or Tutor. He emphasizes a post-digital didactic approach, balancing traditional literacy with digital competencies. His publications reflect a strong trend in digital transformation of writing, multilingual education, and empirical interventions in secondary classrooms. He leads research projects funded by BMBF and MKW NRW, including the "AI Writing Arrangements" project tested in 8th-grade classes. Scientific contributions and collaborations: Co-editor of research handbooks on empirical writing didactics Collaborator with scholars like Nicole Marx, Katrin Lehnen, and Joachim Grabowski Active contributor to journals such as Didaktik Deutsch , BiSS-Journal , and Waxmann publications Hosts a research team at lernarrangements.de He advises on academic language development, text procedures, and vocabulary transfer across modalities and subjects. His lab develops open educational resources (OER) for digital writing and communication, contributing to platforms like Twillo.

• Writing Didactics
• Vocabulary Didactics
• Digital Communication in Education
• +7 more

Christopher Brooks is an Assistant Professor at the University of Michigan's School of Information, specializing in educational technologies and data science education. He directs the Educational Technology Collective (etc), a multidisciplinary research group focused on learning analytics, educational data mining, and collaborative learning systems. His work bridges computer science and education, with a focus on improving teaching methods through AI-driven tools and platforms. Research Interests: Development and impact assessment of educational technologies Predictive modeling for student success Data science pedagogy Privacy in smart home technologies Publications reflect a focus on learning analytics, MOOC design, and educational AI, with notable contributions to conferences like CHI, LAK, and AIED. Awards include multiple best paper recognitions. Teaching includes applied data science courses at UMich and Coursera. He leads the Master of Applied Data Science (MADS) program and collaborates with institutions like Microsoft to build AI-driven educational tools.

• Educational Technology
• Data Science Education
• Learning Analytics
• +3 more

Joni S. Williams, MD, MPH, is an Associate Professor of Medicine and holds dual roles as the Section Chief for Inclusion and Community Outreach and Section Chief for Research in the Department of Medicine at the Medical College of Wisconsin (MCW). She also serves as the Milwaukee Community Chair in Health Equity Research and Director of the Center for Advancing Population Science (CAPS). Her research focuses on reducing health inequities through social-medical integration, particularly addressing race, socioeconomic status, and geographic barriers affecting chronic disease outcomes in marginalized communities. She leads the ARCHE team within CAPS, advancing health equity research, clinical trials, and community engagement. Dr. Williams earned her MD from the Medical University of South Carolina (2012) and her MPH in Community Health from Drexel University (1998). She completed a postdoctoral fellowship in health disparities research at the Medical University of South Carolina (2008–2014). Her research interests include health equity, community-based interventions, and addressing social determinants of health. She has secured multiple grants, including NIH R01, R21, and U54 awards, and has authored over 260 publications. She is an active member of the Society of General Internal Medicine’s Health Equity Commission and serves as an associate editor for the Journal of General Internal Medicine and the American Journal of Medicine Open . Dr. Williams is committed to education, mentoring over 50 learners, and has received recognition such as the MCW President’s Inclusive Excellence Award (2023). She collaborates with community partners like the Milwaukee Area Health Education Center and the Greater Galilee Baptist Church to advance health equity initiatives.

• Health Equity
• Social Determinants of Health
• Diabetes
• +5 more

Andrew Ng is an Adjunct Professor at Stanford University's Computer Science Department and a globally recognized leader in AI. He is the Founder of DeepLearning.AI, Executive Chairman of LandingAI, General Partner at AI Fund, and Co-Founder of Coursera. His work has revolutionized machine learning and online education, with over 200 research papers in AI, robotics, and related fields. He was named to the 2023 Time100 AI list of most influential figures in AI. Ng's research focuses on machine learning, deep learning, reinforcement learning, and their applications in robotics and education. He pioneered the development of massive open online courses (MOOCs), notably through Stanford's early experiments in 2011 that attracted hundreds of thousands of learners. His contributions include foundational work in algorithms like Latent Dirichlet Allocation (LDA) for text analysis and advancements in spectral clustering and inverse reinforcement learning. His publications span topics from robotic hand design to scalable deep learning systems, emphasizing practical and scalable solutions. Ng's educational initiatives, such as the Machine Learning and Deep Learning Specializations, have educated millions worldwide. He advocates for accessible AI education and ethical AI development, emphasizing collaboration between academia and industry.

• Artificial Intelligence
• Machine Learning
• Robotics
• +4 more

Cengiz Hakan Aydin , PhD, is a full professor at Anadolu University in Turkey, where he has been a faculty member since the early 1990s. He currently serves as the Head of the Distance Education Department in the Faculty of Open Education and is the Director of the OpenAnadolu Project , which includes the AKADEMA MOOCs platform. Additionally, he holds the role of Director of the Office of Learning and Teaching Enhancement at Özyeğin University . Dr. Aydin’s research is centered on the design and development of open and distance learning (ODL) environments. His work explores the integration of emerging technologies such as AI, VR, AR, and MR into educational systems. He is deeply engaged in the study and promotion of Open Educational Resources (OER) , Open Educational Practices (OEP) , and Massive Open Online Courses (MOOCs) . His scholarly contributions also address current trends and challenges in higher education. Dr. Aydin has held leadership roles in several international organizations. He served as President and Board Member of the International Division at the Association for Educational Communications and Technology (AECT) , and as a Board Member of the International Council for Educational Media (ICEM) . He is currently a Steering Committee Member of the OpenupEd initiative under the European Association of Distance Teaching Universities (EADTU) , and a member of the AECT Board and the Centre for Distance Education Research (COER) . He is actively involved in editorial work, serving on the boards of International Review of Research in Open and Distance Learning (IRRODL) , Educational Media International (EMI) , and Journal of Open, Distance, and Digital Education (JODDE) . Research Projects and Grants: Volkswagen Foundation – AI in Education (AIEd) : Local researcher. Erasmus+ CRED4TEACH (MOOC-based micro-credentials for teacher professional development): Leading researcher at Anadolu University. Erasmus+ ADMIT (Generative AI and Large Language Models in Higher Education): Researcher. Anadolu University Internal Funds – Multiple projects including AI-based tools for writing skills, intelligent personal education coach, and automated grading systems for open-ended questions. Dr. Aydin serves as both Project Coordinator and Researcher . Labs and Teams: Dr. Aydin leads the OpenAnadolu Project , which encompasses platforms like AKADEMA and serves as a hub for innovation in distance education and MOOC development at Anadolu University.

• Open and Distance Learning (ODL)
• Educational Technology
• Artificial Intelligence in Education
• +5 more

Damien Raftery is a Lecturer in the Department of Business at South East Technological University (SETU Carlow), where he has served since 1995. He holds roles as eLearning Development Officer in the Teaching and Learning Centre (since 2008) and External Examiner. His academic leadership includes Programme Directorships, Academic Council membership (2013-2015), and chairing the Teaching, Learning & Support Services Committee. Education: BSc (Hons) and MSc in Mathematical Science from University College Dublin (1994-1995), followed by an MA in Management in Education (Waterford Institute of Technology, 2003) and an MA in Educational Studies (University of Sheffield, 2017). Research focuses on higher education pedagogy, with emphasis on generative AI's impact on teaching/assessment, blended/flipped learning methodologies, and quantitative literacy. He actively contributes to educational technology through roles in the Irish Learning Technology Association (founding treasurer, conference organizer) and co-developed the StatsSkills web app for statistics education. His recent work addresses AI-driven challenges in assessment, VLE optimization, and digital pedagogy innovations. Collaborative efforts include organizing the 2024 Digital Education Conference and publishing on AI ethics in academic settings.

• Higher Education Pedagogy
• Generative AI in Education
• Academic Integrity
• +5 more

Samantha Curle is a Reader in the Department of Education at the University of Bath, serving as Director of all MRes Programmes in the Humanities and Social Sciences Faculty. She also holds roles as Institutional Academic Lead for the South West Doctoral Training Partnership and Director of Studies for the MRes in Advanced Quantitative Methods. Her research focuses on English Medium Instruction (EMI) in global higher education, particularly its academic and linguistic outcomes, technology integration, and psychological dimensions. Career highlights include a PhD from the University of Oxford (2018) on stakeholders’ attitudes toward EMI in Japanese higher education. She has extensive editorial roles, including guest editorships at Frontiers in Educational Psychology and Data in Brief . Her expertise spans quantitative methods, applied linguistics, and bilingual education, contributing to UN Sustainable Development Goal 4 (Quality Education). Education: PhD (University of Oxford, 2018) MSc Research Methods (University of Oxford, 2014) Bachelor of Education (Open University of Hong Kong, 2010) Grants and Projects: Leading projects on EMI in Saudi Arabia, Brazil, and Hong Kong-UK collaboration Focus on educational inequalities in Spain using CART models Awards: Adjunct Professor (2024) Her research has yielded 88+ publications, emphasizing EMI’s role in STEM, teacher professional development, and sustainable education. She advises doctoral students on quantitative EMI studies and advocates for evidence-based policy in multilingual education.

• English Medium Instruction (EMI)
• Integrating Content and Language in Higher Education (ICLHE)
• Advanced Quantitative Research Methods (AQM)
• +4 more

Juho Leinonen is an Academy Research Fellow at Aalto University's Department of Computer Science, Finland, specializing in AI-enhanced computing education. His work focuses on leveraging large language models (LLMs) to transform programming instruction through personalized learning analytics and educational technology. Education Background: PhD in Computer Science, University of Helsinki (2019) Docent (Adjunct Professor) in Computer Science, University of Helsinki Postdoctoral research at The University of Auckland, Aalto University, and University of Helsinki Research Focus: Leinonen's work centers on three interconnected pillars: (1) developing fine-grained learning analytics to decode student programming behavior; (2) applying LLMs to create adaptive educational tools for diverse learners; and (3) implementing learnersourcing strategies for scalable resource generation. His research particularly addresses challenges in multilingual programming education and responsible AI integration, with emphasis on non-native English speakers and novice programmers. Publication Trends: Recent publications (2024-2025) reveal a concentrated exploration of generative AI in computing education, with 85% focused on LLM applications. Key themes include synthetic data generation for educational research, multilingual prompting systems, and ethical frameworks for AI feedback. His work demonstrates both practical implementations (e.g., autocompletion quizzes) and critical analyses of AI limitations in educational contexts. Awards & Recognition: ACE2024 Best Paper Award for LLM-generated worked examples study UKICER 2023 Best Paper Award for achievement goals research ACE 2023 Best Practitioner Paper ICER 2022 Best Paper Award for programming exercise generation SIGCSE TS 2022 Best Paper in Computing Education Research ACE 2021 Best Paper Award for contextualized problem descriptions Research Leadership: As principal investigator of the Academy of Finland-funded project 'Advanced Student Modeling and Tailored LLMs for Personalized Learning', Leinonen supervises PhD students and postdocs while leading international collaborations with institutions including The University of Auckland and University of Helsinki. His grant portfolio focuses on ethical AI deployment in education and cross-cultural computing pedagogy. Collaborative Networks: He maintains active partnerships with leading computing education researchers like Paul Denny (Auckland), Arto Hellas (Aalto), and Andrew Luxton-Reilly (Auckland), evidenced by 90% co-authored publications. His work appears consistently in top venues including ACM SIGCSE, ICER, and ACE conferences.

• Computing Education
• Artificial Intelligence
• Educational Technology
• +3 more