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János GyőriView profile

Professor

• Intercultural Education
• Shadow Education Systems
• International Student Motivation
• +3 more

János Győri is a Professor at the Institute of Intercultural Psychology and Education at Eötvös Loránd University in Budapest. His roles include serving as a lecturer in the Relation between Shadow and Public Education Research Group and as an Alternate Member of the Credit Transfer Committee. He specializes in intercultural education systems, shadow education dynamics, and international comparative studies in teacher education and language learning motivation. His research spans multiple countries including Japan, Singapore, the Czech Republic, and Myanmar, with a focus on educational policies and student motivation across different cultural contexts. Dr. Győri’s work emphasizes cross-cultural pedagogical comparisons, particularly analyzing how informal educational structures (shadow education) influence formal schooling systems. He has conducted extensive studies on international students' language learning motivations, teacher identity formation, and gifted education programs across global contexts. His research bridges educational theory and practice, often employing both quantitative and qualitative methods to explore complex educational phenomena. Notable themes in his publications include examining motivational frameworks for language acquisition among international populations, analyzing systemic differences in teacher education between nations, and evaluating the societal impacts of supplementary educational systems. His recent work highlights emerging trends in global talent development strategies and the evolving role of non-formal educational interventions. While no specific awards are listed, his prolific publication record indicates sustained academic contribution to educational sciences. His advisory activities and committee roles reflect engagement with institutional educational reforms and cross-border educational collaborations.

• Electromagnetic Theory
• Applied Mathematics
• Numerical Methods
• +3 more

Dario Bojanjac is an Assistant Professor at the Department of Wireless Communications, Faculty of Electrical Engineering and Computing, University of Zagreb. His research focuses on mathematical modeling of electromagnetic processes, numerical methods for Maxwell's equations, and applied mathematics techniques like asymptotic analysis. He holds a PhD in mathematics (2015) and electrical engineering (2009), with extensive visiting scholar experience at institutions such as École Polytechnique Fédérale de Lausanne (EPFL) and the University of Michigan. Education: PhD in Mathematics (2015), Faculty of Science, University of Zagreb PhD in Electrical Engineering (2009), Faculty of Electrical Engineering and Computing His research interests include electromagnetic wave scattering, homogenization of Maxwell's equations, and computational electromagnetism. Recent work explores ground-based SAR systems, deep learning applications in radar data analysis, and flood classification using multivariate approaches. He has received awards including the Swiss Government Excellence Scholarship and Croatian Government Fellowship. His projects include satellite electromagnetic field measurements and metamaterial-based invisibility cloak realization. He participates in lab initiatives like AOLAB2 and coordinates projects such as BODYSEN and HybridAccess. Awards: Swiss Government Excellence Scholarships CIME Foundation Fellowship European Science Foundation Fellowship Bojanjac has advised on multiple research projects and contributed to educational initiatives like the MILE interactive learning system. His lab collaborations include work on sensor systems and optical communication technologies.

Clayton CafieroView profile

Senior Lecturer

• Theory of computation
• Artificial intelligence
• Software engineering
• +3 more

Clayton Cafiero is a Senior Lecturer in the Department of Computer Science at the University of Vermont's College of Engineering and Mathematical Sciences. He joined the CS department on a full-time basis in 2022 after beginning his teaching career in 2020. Dr. Cafiero's educational background includes an MS from the University of Vermont (2021), studies at the University of Chicago (1983-1986), and an AB from Dartmouth College (1983). His research and teaching interests focus on Theory of computation, Artificial intelligence, Software engineering, and Algorithms . He has developed extensive course materials covering foundational computer science concepts, mathematical fundamentals for CS, and practical programming tools. His teaching philosophy emphasizes clarity in explaining complex theoretical concepts while connecting them to real-world applications. For the 2025 fall semester, he is teaching CS 2210 (Computer Organization), CS 2250 (Computability and Complexity), CS 2510 (Introduction to Artificial Intelligence), and EDCI 5004 (Computer Organization for Educators). Dr. Cafiero is an active member of several professional organizations: Association for Computing Machinery (ACM) Institute of Electrical and Electronics Engineers (IEEE) and IEEE Computer Society American Association for the Advancement of Science (AAAS) Mathematical Association of America (MAA) Python Software Foundation He has developed educational resources including PyPI packages like the Two's Complement Practice Tool and maintains numerous UVM GitLab repositories containing lecture notes and course materials for CS 1210, CS 2240, CS 2210, CS 2250, and CS 2510 courses. He has also created materials for a non-credit self-assessment course covering mathematical fundamentals and CS tools.

• Stochastic Processes
• Financial Mathematics
• Statistics
• +3 more

Alexandra Chronopoulou is a Clinical Associate Professor in the Department of Statistics at the University of Illinois. She is affiliated with the Coordinated Science Lab and the Center for Social & Behavioral Science, contributing to interdisciplinary research in both mathematical theory and healthcare applications. Her roles emphasize bridging statistical methodologies with practical challenges in diverse fields. Her research interests span stochastic processes, including fractional Brownian motion and volatility modeling, alongside healthcare systems analysis and medical diagnostics. She applies statistical techniques to study burnout among healthcare professionals, particularly in pandemic testing environments, and explores biomechanical factors in gastrointestinal disorders. Her work also intersects with finance, focusing on risk management and option pricing through advanced stochastic frameworks. In recent years, her articles highlight trends in volatility estimation, fractional processes simulation, and healthcare ergonomics. Earlier contributions include methodological advances in sequential Monte Carlo, community detection algorithms, and multiscale diffusions. No scientific awards were explicitly mentioned in the provided texts. Though no advising or grant information was listed, her research collaborations extend to international partnerships. She contributes to labs and centers that foster interdisciplinary innovation, including work at the Coordinated Science Lab and the Center for Social & Behavioral Science.

Marko LüfteneggerView profile

Assistant Professor

• Educational Psychology
• Developmental Psychology
• Motivation and Self-Regulation
• +3 more

Marko Lüftenegger is an Assistant Professor in the Department of Developmental and Educational Psychology at the Faculty of Psychology. His research focuses on adolescent development, classroom environments, and educational psychology, with a particular emphasis on motivation, achievement goals, and teacher-student interactions. He leads projects addressing envy in educational settings, youth radicalization prevention, and teacher training programs. He has authored over 114 publications and secured grants for initiatives such as the REFLECT program promoting gender equality in schools. His work aligns with UN Sustainable Development Goals related to quality education and reducing inequalities. Key contributions include meta-analyses on cultural diversity climates and studies on pandemic impacts on learning. He received the 2011 Summer School Stipendium at the University of Arizona, Tucson. Education: Holds Mag. Dr. and Privatdoz. titles in psychology. Research Grants: Active projects include 'Envy and Schadenfreude in the Classroom' (2022–2025) and 'Youth Radicalization in Austria' (2022–2026). Teaching & Mentorship: Involvement in teacher induction programs and bridging courses for university students. Key Research Themes: Classroom goal structures, adolescent mental health, teacher emotions, and data-driven educational improvements. His work bridges theory and practice, influencing policy through collaborative initiatives.

• Science Education
• Informal Learning Environments
• Game-Based Learning
• +5 more

Dr. Ran Peleg is a Lecturer in Science Education at the Southampton Education School, University of Southampton, and a member of the MSHE research group. His work focuses on innovative teaching methods such as game-based learning, theatre, storytelling, and escape rooms to enhance science education. He holds a BA in Natural Sciences and MEng in Chemical Engineering from the University of Cambridge, and a PhD in science education from the Technion, focusing on museum theatre and informal learning environments. He has extensive experience in educational project management, including the EU-funded TEMI project and interdisciplinary STEAM initiatives. Education Background: BA in Natural Sciences, University of Cambridge MEng in Chemical Engineering, University of Cambridge PhD in Science Education, Technion Research Interests: Game-based and drama-based pedagogy Museum and informal learning environments STEAM education integration Accessibility in science education for visually impaired students Notable Achievements: Fellow of the Mandel Scholars in Education Programme Postdoctoral Fellowship, University of Haifa Senior Fellow of the Higher Education Academy (HEA) Supervision & Grants: Currently supervising 3 PhD students in Education Expertise in securing educational innovation grants through projects like TEMI and escape room initiatives Labs & Collaborations: Member of the MSHE research group Collaborations with museum practitioners and educational institutions globally

Dimitris PavlopoulosView profile

Associate Professor

• Non-Standard Employment
• Statistical Methodology
• Hidden Markov Models
• +3 more

Roles & Affiliations: Associate Professor in Sociology and Research Methods at VU Amsterdam, ERC Consolidator Grant recipient (2019), and affiliated researcher at Statistics Netherlands (CBS). Specializes in non-standard employment dynamics and statistical methodology. Education: PhD in Sociology (Tilburg University, 2007), MSc in Economics (Athens University of Economics and Business), BSc in Mathematics (National and Kapodistrian University of Athens). Research Interests: Focuses on the career effects of non-standard employment contracts, application of Hidden Markov Models, and improving official statistics through novel methodologies. Explores how organizational strategies and policies shape employment trajectories in Europe. Grants & Projects: Led the ERC-funded DYNANSE project (2020–2026), co-developed the SHARESTATS open statistics item bank, and manages the COMBINE grant (2024–2026) addressing measurement errors in social assistance data. Awards: ERC Consolidator Grant (2019), Best Poster Award (RC28 Conference 2017), and a PhD thesis bonus (2007). Labs & Teams: Leads research teams at the Social Inequality and the Life Course (SILC) group, collaborating internationally on labour market dynamics and statistical innovation.

Patrick PunView profile

Associate Professor

• Applied Mathematics
• Financial Mathematics
• Quantitative Finance
• +7 more

Patrick Pun is an Associate Professor in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore, serving as Assistant Chair (MSc Programs) and Director of the MSc in FinTech program within the School of Physical and Mathematical Sciences. His academic journey includes a Ph.D. and M.Phil. from the Chinese University of Hong Kong (CUHK) and a B.Sc. from Nankai University. Professor Pun’s research focuses on the intersection of applied mathematics and finance, with methodologies spanning stochastic controls, nonlinear partial differential equations (PDEs), robust optimization, and machine learning. His work addresses challenges in portfolio optimization, derivatives pricing, risk management, and financial data analysis. He has also contributed to interdisciplinary areas such as nanoparticle characterization and epidemiological modeling (e.g., during the COVID-19 pandemic). Award-winning scholar, Pun holds the 2016 Nicola Bruti Liberati Prize from the Bachelier Finance Society and the CUHK Young Scholars Thesis Award. He is an ad-hoc reviewer for leading journals including Automatica , SIAM Journal on Financial Mathematics , and Quantitative Finance . His professional roles include membership in the Academic Council of the Global Digital Economy Forum. Pun’s teaching and academic leadership include oversight of master’s programs and curriculum development. His research outputs emphasize innovative solutions to time-inconsistent problems, high-dimensional financial data challenges, and the integration of machine learning with traditional financial models. His recent work explores transformer-based generative models, quantum algorithms for financial PDEs, and reinforcement learning applications in portfolio management.

• Human-Computer Interaction
• Learning Analytics
• Learning Technologies
• +6 more

Michail Giannakos is a Professor of Interaction Design and Learning Technologies at the Department of Computer Science, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). He serves as Head of the Learner-Computer Interaction Lab and has held visiting positions including EAISI Visiting Professor at Eindhoven University of Technology (2023-2024) and Honorary Professor at UCL Knowledge Lab (2022-2023). Previously, he was Associate Professor (2017-2020) and Senior Lecturer (2014-2017) at NTNU, and Assistant Professor at Old Dominion University (2013-2014). Dr. Giannakos's research focuses on the design and study of emerging technologies in online and hybrid education settings, with particular emphasis on student and instructor experiences. His work spans Human-Computer Interaction , Learning Analytics , Learning Technologies , and User Experience Research . He has co-authored over 150 peer-reviewed publications in leading journals including Computers & Education, Computers in Human Behavior, IEEE TLT, and ACM TOCE. His recent publications reveal a strong trend toward multimodal learning analytics, embodied interaction in educational contexts, and the application of generative AI in education. The research increasingly integrates physiological and cognitive measurements with traditional learning data to create more comprehensive educational insights. There's also a noticeable focus on STEM education, particularly in mathematics learning through embodied and multimodal approaches. EAISI Visiting Professor, Eindhoven University of Technology (2023) Honorary Professor, UCL Knowledge Lab, University College London (2022) IDC Best Paper Award (2022) ITiCSE Top 5 papers in 25 Years Award (2020) RCN Young Research Talent grant (2016) ERCIM "Alain Bensoussan" Fellow (2013) Outstanding Academic Award, NTNU (2017-2020) Dr. Giannakos actively supervises multiple PhD students and postdocs, including Giulia Cosentino and Andrew Pulsipher as main supervisees. He has successfully mentored numerous PhD candidates to completion, many of whom have gone on to academic positions. His research is supported by substantial grants from diverse sources including the European Commission (Horizon Europe, Horizon 2020), Research Council of Norway, US-NSF, Microsoft Research, and DAAD. Current major projects include STEAM Learning Ecologies (Horizon Europe, 2022-2025) and SURROUNDEDbySCIENCE (Horizon 2020, 2021-2025). As Head of the Learner-Computer Interaction Lab, Dr. Giannakos leads a multidisciplinary team exploring how emerging technologies can enhance learning experiences. The lab focuses on multimodal data collection, embodied interaction design, and the development of intelligent learning environments that adapt to user needs. Current work emphasizes the integration of generative AI with multimodal analytics to create more responsive educational systems.

Vilma MesaView profile

Professor

• Mathematics Education
• Undergraduate Mathematics Instruction
• Community College Education
• +3 more

Vilma Mesa is a Professor of Education and Mathematics at the University of Michigan, affiliated with the Center for the Study of Higher and Post-secondary Education. She holds a B.S. in Computer Science and Mathematics from the University of Los Andes (Colombia), and an M.A. and Ph.D. in Mathematics Education from the University of Georgia. Research Interests: Her work focuses on undergraduate mathematics education, particularly in community colleges and inquiry-based learning environments. She investigates instructional resources, textbook use, and equity in STEM education. Key themes include teaching expertise development, student learning trajectories, and the impact of innovative teaching practices. Grants & Awards: Mesa has secured over $6M in federal funding and received notable awards, including the 2022 AWM Louise May Award and the 2022 University of Michigan Outstanding Mentor Award. Her research spans projects like the NSF-funded 'AI@CC 2.0' and 'PROTEUS,' aimed at improving algebra instruction and interactive textbook design. Professional Roles: She serves as co-Editor-in-Chief of Educational Studies in Mathematics and has contributed to editorial roles in Journal for Research in Mathematics Education . Her work integrates cross-disciplinary collaborations, including projects with Tribal colleges and national studies on calculus education.

• Educational Measurement
• Plagiarism Detection
• Psychometrics
• +2 more

Sébastien Béland is Associate Professor in the Faculty of Education at Université de Montréal, specializing in educational measurement and assessment. His research examines psychometric methods, plagiarism detection, and arts education evaluation frameworks. He leads major research initiatives including studies on notation systems' relationship to professional competency assessment and intercultural sensitivity measurement in college settings. His methodological expertise encompasses Rasch modeling, latent variable analysis, and machine learning applications in educational assessment. Current projects investigate academic bullying, generative AI impacts on STEM evaluation, and international collaborations on academic language socialization.

Andrew C. LeeView profile

Academic

• Theory of Computing
• Graphs and Combinatorics
• Computer Science Education
• +3 more

Andrew C. Lee is an Assistant Teaching Professor in the Department of Computer Science at Syracuse University. He holds a Ph.D. from the University of Maryland, College Park (1998) and multiple advanced degrees from the University of Michigan and the University of Hong Kong. His expertise spans the Theory of Computing, Graphs and Combinatorics, Computer Science Education, and the History of Computing. His research focuses on mathematical analysis of computational resources and strategies, integrating methods from logic, discrete mathematics, and automata theory. He has contributed to formal learning theory, graph algorithms, and educational curriculum development. Education: Ph.D. in Computer Science, University of Maryland, College Park (1998) M.A. in Computer Science, University of Maryland, College Park (1996) M.A. in Mathematics, University of Michigan, Ann Arbor (1988) B.A. in Mathematics, University of Hong Kong (1987) Research Interests: Dr. Lee investigates computational problem-solving strategies, particularly in machine learning and algorithm design. He applies graph theory and combinatorial methods to formal learning models and explores the interplay between computing history and education to enhance teaching practices for future professionals. Recent work includes applications in game theory, questionnaire design, and data analytics. Publications: His work spans topics like recursive chromatic numbers, query-based learning models, and graph homeomorphisms. Key themes include algorithmic efficiency, computational logic, and discrete mathematics applications. Teaching & Advising: Courses taught include Artificial Intelligence, Algorithms, and Automata Theory. No explicit grants or student advisees are listed, but his research engages undergraduates in concrete problem-solving scenarios. Labs/Teams: Not explicitly mentioned, but his educational focus suggests involvement in curriculum design and undergraduate research initiatives.

• Mathematics Education
• Teacher Professional Learning
• Student Engagement in Mathematics
• +4 more

Professor Janette Bobis is a mathematics educator and researcher at the University of Sydney, affiliated with the Sydney School of Education and Social Work. She holds a BEd from the University of Sydney, an MEdAdmin (Hons) from UNSW, and a PhD from UNSW. Her research focuses on teacher professional learning, student engagement in mathematics, and mental computation strategies. She has held senior roles such as Research Director and Associate Dean, and currently supervises research students like Michelle CHEUNG and Yasser MENESES ZEPEDA. Her awards include the 2023 MERGA Research Award, 2017 Senior Fellowship from the Higher Education Academy (UK), and multiple teaching excellence awards. Current research projects include 'The Benefits of Visual-Spatial Representations of Numbers' (ARC DP230101481) and 'Understanding Non-Specialist Mathematics Teachers' (NSW Strategic Research Fund). Bobis has authored books like Maths Sequences for the Early Years (2023) and contributed to journals such as Mathematics Education Research Journal and Research in Mathematics Education . She serves on editorial boards for key mathematics education journals and has over 100 publications in peer-reviewed outlets. Her work emphasizes challenging mathematical tasks, teacher identity development, and equity in mathematics education. Projects like EMCC3 (ARC LP180100611) explore cumulative and challenging task sequences in collaboration with schools and universities.

Laura BlackView profile

Professor

• Inequalities in Education
• Social Justice in Mathematics Education
• Gender Studies in STEM
• +3 more

Laura Black is a Professor of Education at the Manchester Institute of Education, University of Manchester. Her research focuses on inequalities and social justice in education, particularly within mathematics education. She employs frameworks like Cultural Historical Activity Theory (CHAT) and Bourdieu’s concepts of capital to examine how pedagogical practices reproduce or challenge educational disparities. Her current projects include the Very Local Maths project , which explores community-based mathematics through art collaborations, and the Nonbinary Mathematics Project , addressing gender nonconformity in STEM education. She has supervised over a dozen PhD students, many focusing on issues of equity, pedagogy, and marginalized communities. Key research themes include: Mathematical identities in schools and universities Gender and non-binary experiences in mathematics education Funds of Knowledge approaches to curriculum design Home-school relationships and class dynamics Her work contributes to UN Sustainable Development Goals related to quality education (SDG 4) and reduced inequalities (SDG 10). Recent publications analyze caregiver perspectives on school mathematics and queer students’ experiences in mathematical spaces.

Lorin LachsView profile

Professor

• Multimodal speech perception
• Perception of Spoken Language
• Psycholinguistics
• +3 more

Lorin Lachs is a Professor in the Department of Psychology at Fresno State, affiliated with the College of Science and Mathematics. He holds a BA in Neuroscience and Psychology from Brandeis University and a PhD in Cognitive Science and Psychology from Indiana University Bloomington. His research focuses on perception across sensory modalities, including speech perception, psycholinguistics, virtual reality, and video gaming behavior. Education: Bachelor of Arts (Brandeis University): Double Major in Neuroscience and Psychology Doctor of Philosophy (Indiana University): Joint Degree in Cognitive Science and Psychology Research Interests: Explores multimodal speech perception and the perception of spoken language in diverse environments Investigates how virtual reality and video gaming behavior influence perceptual processes Applies psycholinguistic frameworks to study human perception across sensory systems Teaching: Undergraduate courses: Sensation and Perception, Research Design, History of Psychology, Psychology of Language Graduate courses: Research Methods, Lab Teaching, Proposal Development, Perception and Action Awards/Grants: No specific awards or grants listed in the provided text. Dr. Lachs’ curriculum vitae is maintained up to date and accessible online, reflecting his academic trajectory and contributions to the field of cognitive psychology.