Rational Number Learning Professors and Supervisors

Cangxiong Chenمشاهده پروفایل

پژوهشگر

University of BathUnited Kingdom

Cangxiong Chen is a Researcher at the Institute for Mathematical Innovation (IMI), University of Bath. Prior to this, he worked in startups in Cambridge, UK, and Beijing, China, applying machine learning and statistical methods to consumer behavior modeling, pricing strategies, and recommendation systems. He holds a PhD in Number Theory from the University of Cambridge (2017), an MPhil in Mathematics from the University of Hong Kong (2011), and a Bachelor’s degree from the same institution. His research focuses on advancing the mathematics of machine learning, particularly in designing algorithms with privacy, fairness, robustness, and generalisability. He explores topics like differential privacy in image/video processing, training data leakage prevention, and collective intelligence systems. Education: • Doctor of Philosophy in Mathematics, University of Cambridge (2011–2016) • Master of Philosophy in Mathematics, University of Hong Kong (2009–2011) • Bachelor’s degree in Mathematics, University of Hong Kong His research interests span the theoretical foundations of machine learning, with a focus on privacy-preserving techniques such as differential privacy. He investigates robust algorithms for image and video processing, leveraging compressed sensing and dynamical systems. Additionally, he contributes to collective intelligence research, exploring how AI can enhance large-scale problem-solving and interdisciplinary collaboration. His work bridges pure mathematics (e.g., number theory) with applied domains like cybersecurity and social computing. In his recent projects, he has analyzed vulnerabilities in models like CLIP, studied leakage via gradients in neural networks, and developed strategies for AI-driven collective intelligence. These studies highlight his commitment to advancing both ML theory and its practical applications in diverse fields. Grants and Collaborations: Chen has contributed to seven research projects, including those funded by UKRI, EPSRC, and the Advanced Research and Inventions Agency. Notable roles include Researcher Co-Investigator (CoI) in projects like 'A New Analytical Framework for Dexterous Soft Robotic Manipulators' and 'AI for Collective Intelligence (AI4CI)’. He collaborates with interdisciplinary teams on topics ranging from soft robotics to policy strategy, emphasizing real-world impact through UK and international partnerships. Labs and Teams: Affiliated with the Institute for Mathematical Innovation at the University of Bath, he engages with collaborative teams across multiple disciplines, including artificial intelligence, data science, and mathematical modeling. His work often intersects with industry needs, as evidenced by his startup experience and ongoing projects in applied ML.

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Nesrin Sahinمشاهده پروفایل

دانشیار

University of Central ArkansasUnited States

Nesrin Sahin is an Associate Professor in the Mathematics Department at the University of Central Arkansas (UCA). Her work focuses on pre-service teachers' mathematical and statistical knowledge for K-12 education, with research interests in algebraic thinking, rational numbers, probability concepts, and data analysis. Education: Ph.D., Mathematics Education, University of Central Florida Her research explores how future teachers develop foundational mathematical skills and pedagogical strategies. Recent publications emphasize problem-solving in algebra, probability applications in biology education, and interdisciplinary connections between science and mathematics. She contributes to improving teacher training through studies on fraction division, word problem construction, and student strategy use in mathematics achievement. Publications consistently address educational methodologies and conceptual understanding, bridging theory and classroom practice.

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Jonathan Franceschiمشاهده پروفایل

استاد مهمان

University of PaviaItaly

Jonathan Franceschi serves as a Visiting Professor in the Department of Mathematics at the University of Pavia, maintaining an office in room C11. His academic profile is anchored in the Mathematical Physics research group, with active contributions to interdisciplinary mathematical modeling. His research spans Mathematical Physics, Network Theory, Kinetic Theory, and Fractional Calculus, with pronounced applications in social dynamics and public health. Key focus areas include epidemic modeling, opinion polarization mechanisms, and fake news diffusion—particularly examining Italian vaccination hesitancy during the Covid-19 pandemic. His methodological toolkit integrates kinetic equations, graph theory, and optimal control frameworks for complex networked systems. Analysis of his 15 publications (2019–2025) reveals a cohesive trajectory: early work established foundations in fractional calculus and numerical methods, while recent research pivots toward data-driven social modeling. Dominant themes include consensus optimization with condensation phenomena, graphon-based opinion dynamics, and uncertainty quantification in epidemic control—all demonstrating rigorous mathematical formalism applied to real-world sociotechnical challenges. Franceschi actively supports academic community initiatives including Five o'clock TeX (offering LaTeX courses via Zoom), The break bridge (curating educational handouts), and the CompMat poster template project. His digital scholarship footprint is visible through arXiv, ResearchGate, ORCID, and Google Scholar profiles.

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Monica May Dze Wongمشاهده پروفایل

دانشیار

Australian Catholic UniversityAustralia

Monica May Dze Wong is an Associate Professor (Education) affiliated with the School of Education under the Faculty of Education and Arts. Her research focuses on mathematics education, teacher preparation, and integrating Indigenous knowledge systems into curriculum design. Notable contributions include studies on teacher training through school-university partnerships, culturally responsive pedagogy informed by Yup'ik Elders, and special education practicum experiences. Her work emphasizes equity in education through collaborations like the Hub System for Work-Integrated Learning and curriculum development grounded in Indigenous knowledge. Key themes in her publications include fraction understanding, symmetry in mathematics, and enhancing educator preparedness through structured feedback mechanisms during professional experiences. Publications highlight innovative approaches such as symmetrical measuring techniques inspired by Alaska Native practices, adapting assessments for diverse cultural contexts, and improving primary school students' mathematical fluency. Her research bridges theoretical frameworks with practical applications in classrooms, particularly in underserved or culturally specific educational environments.

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Lindsay Foreman-Murrayمشاهده پروفایل

استادیار

Western Washington UniversityUnited States

Lindsay Foreman-Murray is an Assistant Professor in Special Education at Western Washington University. Her work focuses on inclusive teaching practices, culturally and linguistically diverse learners, and students with disabilities. She holds a Ph.D. from Vanderbilt University (2019), an M.A. from the University of Chicago (2009), and a B.A. from Reed College (2006). Her research addresses teacher shortages, school climate, and dropout prevention for students with disabilities. Key projects include analyzing resource accessibility for educators and studying systemic barriers affecting student outcomes. She co-authored works on disability social construction and dropout trends in special education. Dr. Foreman-Murray actively advocates for evidence-based education policies, highlighting threats to federal education agencies like the Department of Education’s NCES. She co-founded the SPARC Center to address special education teacher workforce challenges. Her scholarship spans journals like Preventing School Failure and Contemporary Educational Psychology . Her BlueSky activity emphasizes education policy critiques, teacher support, and interdisciplinary collaboration. She regularly engages with issues like vaccine studies, AI in education, and STEM accessibility.

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Silke Göbelمشاهده پروفایل

استاد

University of YorkUnited Kingdom

Professor Silke Göbel is a leading academic in Numerical Cognition and Developmental Cognitive Neuroscience at the University of York, where she leads the Numerical Cognition Lab. She holds a Visiting Professorship at the University of Oslo (since 2019) and is a Co-director of the ESRC Centre for Early Mathematics Learning at Loughborough University (since 2022). Her academic journey includes a Diplom from Goethe University Frankfurt, a DPhil from Oxford, and postdoctoral research in Oxford before joining York. Her research focuses on numerical processing in typical/atypical development, cross-cultural differences, dyscalculia, and the interplay between language and mathematics. Key methodologies include longitudinal studies, EEG/fMRI, and eye-tracking. She has secured significant grants, including £347k (2023-2026) for studying conceptual spaces and £454k (2022-2025) on rational numbers understanding. Teaching roles include directing the MSc in Developmental Cognitive Neuroscience and teaching modules on mathematical cognition. She has supervised students like Eleanor Redfern (PhD) and contributes to textbooks such as *An Introduction to Mathematical Cognition*. Her work bridges cognitive science, education, and clinical neuroscience, addressing fundamental questions about how children acquire numerical skills and why some struggle. Collaborators include leading researchers in Germany, Austria, and France. Her lab’s work has implications for educational interventions targeting math learning difficulties and cross-cultural disparities in mathematics performance.

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Albanos Paraskevasمشاهده پروفایل

مدرس

Aristotle University of ThessalonikiGreece

Albanos Paraskevas is a Lecturer at Aristotle University of Thessaloniki's Department of Algebra, Number Theory and Mathematical Logic. He holds a PhD in Diophantine Geometry and has been teaching since 2014, covering courses like Number Theory, Cryptography, and Algebraic Structures. His professional experience includes over 16 years of secondary education (2001–2017) and ongoing roles in adult education since 2007, focusing on statistics, economic mathematics, and computer literacy. Education: Undergraduate: Mathematics, Aristotle University of Thessaloniki Postgraduate: Theoretical Mathematics and Studies in Education Doctoral Thesis: Explicit Curves on Algebraic Number Fields and Diophantine Equations (Supervisor: Dimitrios Poulakis) Research focuses on Number Theory (Diophantine equations, algebraic number fields), Algebraic Geometry (Riemann-Roch spaces, algebraic curves), and Adult Education (technology adoption in teaching). His work bridges theoretical mathematics with practical applications in education. Publications emphasize computational solutions to Diophantine problems and educational methodologies. No awards are explicitly mentioned, but his active teaching and research roles reflect sustained academic contribution.

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Antti Koskinenمشاهده پروفایل

پژوهشگر ارشد

Tampere UniversityFinland

Antti Koskinen is a Research Fellow at the Education Research Centre of Gameful Realities, holding a Master of Arts in Education from the University of Helsinki. His academic work focuses on innovative learning methodologies at the intersection of technology and pedagogy. His research examines: Game-based learning environments and their impact on mathematical reasoning Emotional design principles in educational scaffolding AI ethics education through interactive learning systems Development of quantitative reasoning in elementary education Motivational psychology in technology-enhanced learning Koskinen's publications demonstrate consistent focus on experimental educational research, particularly investigating how game mechanics influence cognitive development and ethical understanding. Recent work shows increasing emphasis on AI literacy and adaptive learning systems.

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Chee Whye Chinمشاهده پروفایل

دانشیار

National University of SingaporeSingapore

Assoc Prof Chee Whye Chin is an Associate Professor of Mathematics at the National University of Singapore (NUS), affiliated with the Department of Mathematics. His research focuses on arithmetic algebraic geometry, monodromy groups, and representation theory of reductive groups. He has contributed to foundational work on ℓ-independence of monodromy groups and compatible systems of lisse sheaves. His teaching philosophy emphasizes student-driven learning through interactive lectures and continual assessments, aiming to foster deep understanding of mathematical concepts. Research Interests: Monodromy groups and their structural properties Reductive algebraic groups and their representations ℓ-Independence conjectures in arithmetic geometry Applications of group theory in algebraic geometry Publications: His work spans algebraic geometry, number theory, and computational methods. Notable contributions include studies on rationality of homogeneous varieties, optimization of matrix multiplication algorithms, and independence of ℓ results in compatible systems. Over 15 key publications since 1997 reflect his interdisciplinary impact. Awards & Recognition: No specific awards mentioned, but his research has been cited widely in areas like genomics and computational methods. Teaching & Mentorship: Emphasizes active learning through interactive sessions and rigorous assessments. Encourages students to develop self-directed learning strategies by avoiding pre-prepared lecture notes, fostering independent exploration of mathematical concepts.

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Lenore Blumمشاهده پروفایل

استاد

Carnegie Mellon UniversityQatar

Lenore Blum is a Professor at the Department of Computer Science within the School of Computer Science at Carnegie Mellon University . She has held significant roles such as Founding Director of Project Olympus and Co-Director of the NSF-ITR ALADDIN Center . Her career spans institutions including UC Berkeley, Mills College, ICSI, and MSRI. Research Interests : Blum's work bridges computational complexity and real computation, focusing on algorithms over continuous domains, polynomial equation solving, and transfer principles between discrete and continuous models. She also advocates for diversity in STEM through initiatives like Women@SCS and Expanding Your Horizons . Scientific Awards : Recognized with an NSF Career Advancement Award, AAAS Fellowship (1979), and an honorary Doctor of Laws from Mills College (1999). Grants & Outreach : Led the NSF-funded ALADDIN Center for algorithm adaptation and co-founded the Association for Women in Mathematics. Her outreach includes organizing symposia on mathematics' societal impact and advising the President's Diversity Advisory Council at CMU.

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John Reddenمشاهده پروفایل

استاد

Edward Waters UniversityUnited States

John Redden serves as a Professor in Mathematics and Statistics at College of the Sequoias, a California community college, since January 2014. His primary academic focus spans developmental mathematics and algebra education within the Mathematics and Statistics department. Research Interests: Developmental Mathematics (Expert): Creator of the free online algebra study guide openAlgebra.com and author of comprehensive developmental math resources. Algebra and Number Theory (Advanced): Authored two algebra textbooks published by Flat World Knowledge, emphasizing accessible mathematical instruction. Instructional Design and Technology (Intermediate): Integrates digital tools into mathematics pedagogy with expertise in educational technology frameworks. His scholarly output centers on algebra education materials, including textbooks and open-access digital resources that address foundational mathematical literacy. These works demonstrate consistent focus on practical applications and student-centered learning approaches in algebraic concepts. Professional Recognition: No formal scientific awards or fellowships documented in available sources. Redden maintains active contributions through authored materials and course portfolios. His teaching portfolio includes Mathematics and Computer Science instruction since Fall 1997, with emphasis on curriculum development for community college mathematics. No laboratory affiliations or research teams are indicated in the provided documentation.

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Marco Vasconcelosمشاهده پروفایل

پژوهشگر

ISPA - University Institute of Psychological, Social, and Life SciencesPortugal

Marco Vasconcelos is an active researcher at the University of Aveiro, Portugal, where he serves as an Integrated Member of the Cognition Team. With a PhD from the University of Aveiro, he has established himself as a prominent figure in animal cognition and decision-making research, with 95 publications, 9,723 reads, and 1,322 citations to his name. His research spans multiple institutions and collaborations across Europe, particularly with colleagues at the University of Aveiro and international collaborators including Armando Machado, Tiago Monteiro, and Alex Kacelnik. Vasconcelos's primary research focus centers on decision making and rationality, integrating concepts and techniques from operant and developmental psychology, comparative cognition research, optimal foraging theory, and microeconomics. His work examines how animals, particularly pigeons and starlings, make choices between alternatives, modeling how these options are valued and how valuation drives decisions. He employs optimality and learning theory to address valuation, using empirically supported algorithms to translate valuation into choice. His research often involves developing mathematical models of causative processes and testing them through controlled experiments, with particular emphasis on timing mechanisms, suboptimal choice phenomena, and information processing in animal decision making. Analysis of Vasconcelos's recent publications reveals a strong focus on temporal cognition and decision processes in animals. His work consistently explores how timing mechanisms interact with reinforcement structures to shape behavior, with particular attention to midsession reversal tasks, suboptimal choice phenomena, and numerical discrimination. The research demonstrates sophisticated integration of theoretical models from economics with empirical behavioral data, creating a bridge between normative decision theory and descriptive behavioral observations. His 2022-2025 publications show increasing methodological sophistication with variable trial spacings, differential reinforcement probabilities, and advanced modeling approaches. Vasconcelos maintains active collaborations with researchers across multiple institutions, particularly with Armando Machado at the University of Aveiro and Alex Kacelnik at the University of Oxford. His research has been supported through various grants that enable extensive behavioral experimentation with animal subjects. While specific grant details aren't provided in the available text, his consistent publication output across numerous high-impact journals indicates sustained research funding. As part of the Cognition Team at the University of Aveiro, Vasconcelos contributes to a vibrant research environment focused on animal learning and behavior. His work with the team has produced significant insights into how animals process temporal information, make decisions under uncertainty, and develop cognitive representations of numerical quantities. The research group employs sophisticated behavioral paradigms to investigate fundamental questions about the nature of decision processes and cognitive mechanisms in non-human animals.

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