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Blain MamiyaView profile

Associate Professor

• Chemical Education
• STEM Education
• Educational Psychology
• +3 more

Blain Mamiya serves as Associate Professor of Instruction in the Department of Chemistry within the College of Sciences at the University of Texas at San Antonio. His academic focus centers on improving student success in STEM through evidence-based educational research and curriculum development. Education Background: Ph.D. in Medicinal Chemistry, University of Texas at Austin M.S. in Organic Chemistry, University of Washington Mamiya's research investigates critical factors affecting STEM student performance, including mathematics automaticity, motivation, learning strategies, sense of belonging, and impostor syndrome. His work demonstrates how mathematical proficiency correlates with chemistry success and develops interventions like the Math-Up Skills Test (MUST). He particularly examines challenges faced by underrepresented minorities, first-generation students, and women in STEM environments, creating strategies to enhance inclusion and academic outcomes. Analysis of his publication record reveals a clear research evolution: recent work (2018-2024) focuses exclusively on chemical education and STEM pedagogy, while earlier publications (1995-2001) centered on medicinal chemistry and toxicology. Current studies emphasize diagnostic tools, curriculum alignment, and psychological factors in student success, published in leading science education journals. Mamiya teaches foundational chemistry courses including Basic Chemistry (CHE 1073), Organic Chemistry I Laboratory (CHE 2612), and Chemistry Communication (CHE 3973). He leads the Mamiya Laboratory, which develops and tests educational interventions to address STEM student challenges through rigorous assessment of learning strategies, motivation, and belonging. The lab's research directly informs classroom practices and institutional support systems for at-risk student populations.

Harshit Jitendra MotwaniView profile

Research Fellow

• Computational Algebraic Geometry
• Formal Verification
• Tensors
• +5 more

Harshit Jitendra Motwani is a Postdoctoral Researcher at the Max Planck Institute for Software Systems (MPI-SWS) , Germany. Previously, he was a Postdoctoral Fellow at the Hong Kong University of Science and Technology (HKUST) (2023-2024), following doctoral research at Ghent University (2021-2023) and earlier engagements at HKUST, Ghent University, and the University of Bristol . Education : PhD in Mathematics: Algebra and Geometry from Ghent University (2021-2023), Thesis on Algebro-Geometric Algorithms for Program Synthesis; Integrated BSc and MSc in Mathematics and Computing from IIT Kharagpur (2015-2020). Research Focus : Integrates mathematics into computational domains, particularly Computational Algebraic Geometry , Formal Verification , and Tensors . His work spans program synthesis , tensor networks , conditional independence models , and control theory applications . Publications : Recent contributions include algorithmic advancements in formal methods (FM, AAAI, LAGOS), algebraic statistics (IMRN), and quantum computing (SIGMA). His research combines symbolic computation with practical software engineering challenges. Awards & Honors : IEEE Computer Society Larson Best Paper Award (2023) ACM SIGPLAN Distinguished Paper Award (2023) Young Researcher of the Heidelberg Laureate Forum (2023) INSPIRE Scholarship (2015-2020) Teaching : Guest Lecturer at HKUST, Teaching Assistant at RPTU Kaiserslautern-Landau and IIT Kharagpur. Mentored multiple bachelor's projects at Ghent University and IIT Kharagpur.

• Neuropsychology
• Cognitive Aging
• Dementia
• +4 more

Prof Jelle Jolles serves as Professor of Neuropsychology and Director of the Centre for Brain, Learning & Education at Vrije Universiteit Amsterdam (VU Amsterdam), where he bridges neuroscience, education, and cognitive development research. His leadership focuses on translating brain science into practical educational applications through interdisciplinary collaboration. His primary research domains encompass brain-learning-education interfaces, cognitive aging trajectories, and dementia/Alzheimer's disease mechanisms. Recent investigations emphasize sex-specific cognitive development patterns in adolescence, executive function assessment beyond formal testing, and environmental influences like nutrition (e.g., krill oil supplementation) and physical activity on cognitive outcomes. His work consistently addresses real-world educational contexts through large-scale population studies. Analysis of his 2018-2020 publications reveals concentrated focus on adolescent cognitive neuroscience, particularly examining how biological factors (sex differences), dietary interventions, and exercise modulate learning processes. Methodologically, his team employs rigorous designs including randomized controlled trials, cross-sectional analyses, and systematic reviews to establish evidence-based educational strategies. The Centre for Brain, Learning & Education operates as his primary research ecosystem, facilitating partnerships between neuroscientists, educators, and policymakers. This hub drives initiatives converting laboratory findings into classroom practices, with emphasis on optimizing learning environments through neurocognitive insights and addressing developmental challenges across the lifespan.

Nathan WiebeView profile

Research Fellow

• Quantum Computing
• Quantum Algorithms
• Quantum Simulation
• +3 more

Nathan Wiebe is a Research Fellow in Quantum Information Science at the University of Toronto and Pacific Northwest National Laboratory, specializing in quantum algorithm development for simulating physical systems, machine learning, optimization, and quantum system characterization. His interdisciplinary work bridges theoretical computer science and quantum physics to advance computational methodologies. His academic credentials include: PhD in Physics from the University of Calgary MSc in Physics from Simon Fraser University BSc in Mathematical Physics from Simon Fraser University Dr. Wiebe's research focuses on designing quantum algorithms that enable efficient simulation of quantum dynamics, enhance machine learning models through quantum acceleration, and solve complex optimization problems. His theoretical contributions address fundamental challenges in quantum computational complexity and circuit design, with applications spanning physics, chemistry, and artificial intelligence. His publication history demonstrates a clear trajectory toward increasingly sophisticated quantum computational frameworks, particularly in quantum linear algebra (2019), foundational quantum machine learning (2017), and Hamiltonian simulation techniques (2012). These works collectively establish him as a key contributor to quantum algorithm theory with emphasis on practical implementability. His professional recognition includes: Yale Distinguished Lecture Award (2022) No information regarding student supervision or research funding sources was provided in the source material. He maintains affiliations with the Department of Computer Science at the University of Toronto and the Wellcome Centre for Human Neuroimaging, though specific research group structures or laboratory facilities were not detailed in the available documentation.

• Artificial Intelligence
• Multimodal Machine Learning
• Digital Health
• +3 more

Mrs Omnia Alwazzan is a PhD researcher in Computer Science at Queen Mary University of London, affiliated with the Digital Environment Research Institute (DERI). She is supervised by Prof Ioannis Patras and Prof Greg Slabaugh , and works on AstraZeneca-funded projects . Education: Masters in Computer Science (Georgia State University, 2017-2019), BSc in Computer Science (King Abdul Aziz University) Her research focuses on multi-modal AI fusion for healthcare, combining medical imaging , electronic healthcare records , and ‘omic’ data to improve diagnostics and treatment discovery. Key projects include: FOAA (2024, ISBI): Flattened Outer Arithmetic Attention for tumor classification MOAB (2023, ISBI): Multi-modal Outer Arithmetic Block for brain tumor grading PyTorch implementations for classification and Grad-CAM visualization She has presented at international conferences like IEEE ISBI 2023 (Colombia) and 2024 (Athens), and contributed to open-source repositories on GitHub. Her scientific work was recognized in the 3MT competition , where she highlighted AI applications in healthcare. Personal interests include running and walking, and she recommends tools like PyTorch , ChatGPT , and YouTube for academic learning.

Trung Tuyen TruongView profile

Professor

• Several Complex Variables
• Dynamical Systems
• Algebraic Geometry
• +7 more

Trung Tuyen Truong is a Professor of Mathematics at the University of Oslo, Faculty of Mathematics and Natural Sciences, Department of Mathematics, since September 2023. Previously, he served as an Associate Professor at the same institution from September 2017 to September 2023. His academic journey includes a PhD from Indiana University (2006-2012) under Professor Eric Bedford, followed by postdoctoral positions at Syracuse University (2012-2014), Korea Institute for Advanced Study (2014-2015), and The University of Adelaide (2015-2017). His research spans several complex variables, dynamical systems, and related topics in algebraic geometry. He is particularly interested in applying dynamical systems theory and computational techniques to solve both theoretical and practical problems. His work includes developing optimization algorithms, exploring connections between Weil's Riemann hypothesis and dynamical systems, and investigating the Jacobian conjecture. Truong has made significant contributions to optimization methods, particularly developing Backtracking Gradient Descent and Backtracking New Q-Newton's method, which have applications in deep learning and solving complex mathematical problems. His research has been supported by various grants including a Seed grant from UiO Growth House for developing AI tools for mathematical education, membership in MSCA-Cofund-DP for ERC funding PhD positions, and as Principal Investigator for the Young Research Talents grant from the Research Council of Norway. Truong is actively involved in developing software tools to help students learn mathematics and optimization, as well as creating efficient computational tools. His NUV Optimization solvers have demonstrated superior performance compared to established tools like Matlab and IPOPT in certain optimization problems. He is collaborating with AI companies and medical doctors to use AI for diagnosing from lung data measurements. His publications demonstrate expertise across pure mathematics, computational methods, and interdisciplinary applications, with recent work focusing on dynamical systems approaches to number theory problems and practical optimization algorithms.

Klaus-Peter EichlerView profile

Professor

• Mathematics Education
• Geometry Teaching
• Early Childhood Mathematics
• +4 more

Klaus-Peter Eichler is a Professor at the Institute of Mathematics and Computer Science within the College of Mathematics & Computer Science at the Pedagogical University of Schwäbisch Gmünd. His work focuses on mathematics education in elementary and primary schools, emphasizing the integration of arithmetic and geometry, spatial reasoning development, and art-mathematics interdisciplinary approaches. He has contributed extensively to curriculum design, teacher training, and educational technology. Research Interests: Mathematics education, geometry teaching, spatial reasoning, early childhood math, primary education, art integration, differentiated instruction. Email: klaus-peter.eichler@ph-gmuend.de His publications span over two decades, with recent work (2010-2013) addressing competency-based teaching, spatial visualization, and digital learning tools. Eichler has presented at international conferences in Chile and Germany, focusing on practical geometry education and spatial imagination development. He co-developed educational resources like the Mathematikus textbook series and the www.mathematikus.de portal, which provides learning materials for children and teachers. Key trends in his research include bridging abstract mathematical concepts with concrete experiences, fostering spatial reasoning through play and technology, and promoting inclusive, student-centered teaching methods. He advocates for connecting mathematics to real-world applications and artistic expression to enhance engagement and understanding in young learners.

Taha Ertuğrul KuzuView profile

Assistant Professor

• Learning Process Research
• Multilingualism Research
• Professionalization Research
• +4 more

Dr. Taha Ertuğrul Kuzu is a Tenure-Track Professor at Pädagogische Hochschule Schwäbisch Gmünd since October 2023, holding the Professorship for Heterogeneity in Primary School . He previously served as a postdoctoral researcher at the University of Münster (2020-2023) and completed his doctorate at TU Dortmund (2018) with a thesis on Multilingual Concept Development Processes . His research focuses on multilingualism activation , qualitative interaction analysis , and AI integration in education . Bachelor: TU Dortmund (Mathematik/Deutsch, Grundschullehramt) Master: TU Dortmund (Mathematik/Deutsch, Grundschullehramt) His research interests span: Multilingual learners' mathematical meaning-making Translanguaging in classrooms Digital pedagogy with AI tools Heterogeneity-sensitive teacher training Qualitative interaction analysis His peer-reviewed publications examine AI-integrated task design, multilingual video explanations, and cognitive transitions in mathematics. Current projects include CaLSAM (Erasmus+ AI/multilingualism), KIKo-Prim (AI competencies), and ProHeDi (teacher professionalization). Scientific awards include: BMBF Avicenna Studienwerk Promotionsstipend (2014-2018) As editorial leader , he co-edits the BildungsWelten Grundschule book series and serves as Schriftleiter for Grundschulmagazin. He actively participates in professional networks including GDM, ERME, and Avicenna Alumni.

Dor AbrahamsonView profile

Professor

• Mathematical cognition
• Design-based research
• Embodied interaction
• +7 more

Dor Abrahamson is a Professor of Learning Sciences and Human Development in the Graduate School of Education at the University of California Berkeley. He directs the Embodied Design Research Laboratory (EDRL) and has established himself as a leading design-based researcher in the field of mathematics education. His work bridges cognitive science, socio-cultural theory, and embodiment paradigms to create innovative learning environments that transform how students understand mathematical concepts. Abrahamson's research focuses on the relationship between physical action and conceptual learning, with particular emphasis on how embodied interaction facilitates mathematical understanding. His work spans intensive quantities like ratio, likelihood, and slope, as well as early algebra concepts. He develops experimental technological materials and activities that have potential for scale-up, while simultaneously refining theoretical constructs in the learning sciences and developing frameworks for educational design. His current projects include developing embodied-interaction technological systems for the guided reinvention of mathematical concepts, with recent work involving computer-embedded animated avatars that incorporate naturalistic gesture in face-to-face mathematics tutoring. Analysis of Abrahamson's recent publications reveals a strong focus on multimodal learning approaches, with significant attention to how gesture, eye-tracking, and physical manipulation contribute to mathematical understanding. His work increasingly integrates learning analytics, complex systems theory, and inclusive design principles, particularly in developing educational technologies for diverse learners. The research demonstrates a consistent trajectory toward understanding the micro-dynamics of learning through embodied interaction while creating practical educational interventions. National Academy of Education/Spencer Postdoctoral Fellowship for Seeing Chance Co-recipient of NSF grants for developing naturalistically gesturing interactive pedagogical avatars Co-recipient of NSF grants for fostering children's productive dispositions toward failure when programming Best Submission—Dr. Arthur I. Karshmer Award for Assistive Technology Research Finalist, Best Paper, IJCCI 2021 Abrahamson has secured significant research funding including NSF grants for developing gesturing avatars and for understanding how children approach programming failures. His work emphasizes collaborative, interdisciplinary research that brings together experts from education, cognitive science, movement science, and computer science. He has mentored numerous doctoral students and collaborators who have gone on to contribute significantly to the field of educational design. The Embodied Design Research Laboratory operates as a hub for innovative research that combines theoretical rigor with practical educational applications. The Embodied Design Research Laboratory (EDRL) represents a multi-disciplinary approach to educational design, inspired by the belief that all students can deeply understand mathematics. EDRL projects involve creating mixed-media materials that are iteratively refined based on empirical studies of student multimodal behaviors including speech, gesture, and eye-gaze. The lab has produced numerous technological innovations including motion sensor applications, touch screen interfaces, and agent-based simulations that support embodied mathematical learning.

• Abstract Interpretation
• Program Analysis
• Program Verification
• +5 more

Roberto Bagnara is a Full Professor of Computer Science at the Department of Mathematics and Computer Science of the University of Parma, Italy. He has been a faculty member since 1997, progressing from Assistant Professor to Associate Professor and finally to Full Professor in November 2010. In addition to his academic position, he serves as Chief Scientist, CTO, and President of BUGSENG srl, a university spin-off focused on software verification and validation technologies. Professor Bagnara received his laurea degree (magna cum laude) in Computer Science from the University of Pisa in July 1992, followed by a Ph.D. in Computer Science from the same university in September 1997. Prior to his doctoral studies, he worked at CERN in Geneva with Tim Berners-Lee, the inventor of the World Wide Web, and at the University of Bologna's Physics Department developing software for data acquisition and analysis. His research spans abstract interpretation, program analysis and verification, and semantics-based program manipulation techniques . Professor Bagnara has made significant contributions to the fields of static program analysis, with particular focus on convex polyhedra manipulation, constraint logic programming, and formal verification of safety-critical software. His work bridges theoretical foundations with practical applications, resulting in several influential software projects including the Parma Polyhedra Library (PPL), CHINA, PURRS, and ECLAIR. The PPL is particularly notable as it's used in the GNU Compiler Collection (GCC), the most widely used compiler suite worldwide. Professor Bagnara's recent publications reveal a strong focus on safe and secure programming, particularly in C language ecosystems. His work on C-rusted, MISRA compliance, and floating-point verification demonstrates his commitment to practical solutions for real-world software verification challenges. His research increasingly integrates formal methods with industry needs, especially for safety-critical embedded systems. Professor Bagnara has supervised numerous thesis students and has been involved in multiple national and international research projects, including ESPRIT, COFIN, and PRIN projects. He has served on program committees for major conferences such as SAS, VMCAI, and ICLP, and has organized workshops and summer schools in his field. He leads the Applied Formal Methods Laboratory at the University of Parma, which focuses on developing theoretical foundations and practical tools for software analysis and verification. The laboratory's work has significant industrial impact, particularly through the ECLAIR project, which aims to create an industrial-strength platform for analysis, verification and transformation of imperative languages.

• High-Performance Computing
• Parallel Computing
• Machine Learning
• +7 more

José Leandro Penadés Martínez is a Professor in the Department of Computer Science and Artificial Intelligence at the Higher Polytechnic School II of the University of Alicante. He has been a faculty member since 1988 and held administrative roles including Vice-Rector for Academic Affairs and Teaching Staff (2016–2020), Director of the Faculty Secretariat (2008–2016), and Department Director (2005–2008). He is affiliated with the University Research Institute in Computer Science and the High-Performance Computing and Parallelism Research Group (gCAPyP) . PhD in Computer Science , University of Alicante Graduate in Mathematical Sciences , University of Valencia His research focuses on parallel algorithms for linear/nonlinear systems in heterogeneous architectures and designing high-level interfaces for parallel programming . Key applications include Markov chains , Google PageRank , combustion problems , and climate variability analysis . Recent work explores educational software for arithmetic, machine learning in construction materials, and parallel methods for environmental modeling. His scientific achievements include 15 years of continuous recognition by CNEAI (10 research periods, 6 teaching merit periods). Notable publications span interactive learning software , parallel computing , and machine learning applications in civil engineering and education. Doctoral advisees : Vicente Galiano Ibarra (2007), Héctor Francisco Migallón Gomis (2004), Jose Arnal García (2000) He has participated in public research projects funded by the Generalitat Valenciana and Spanish Ministry of Education , focusing on scientific computing libraries and hybrid systems. His 2025 teaching includes Discrete Mathematics and Software Development in Parallel Architectures at the University of Alicante.

Ulrike SchildView profile

Researcher

• Developmental Psychology
• Speech Perception
• Phoneme Processing
• +5 more

Dr. Ulrike Schild is a researcher at the University of Tuebingen 's Department of Psychology , specializing in developmental psychology. She has been a post-doctoral researcher there since 2013, following her PhD in biological psychology and neuropsychology from the University of Hamburg (2012). Her work spans speech perception, phoneme processing, and literacy acquisition effects. Current affiliation: Department of Psychology, University of Tuebingen Doctoral training: Biological Psychology & Neuropsychology, University of Hamburg Post-graduate education: Master of Higher Education, University of Hamburg Research Focus includes: Ontogenetic language development Speech perception mechanisms Phoneme and prosody processing Neurophysiological adaptations in blindness Literacy's impact on speech processing Developmental neuroscience methodologies Key Methods : EEG, NIRS, eye-tracking, behavioral data (reaction times, finger-tracking). Her publications from 2011-2023 focus on early language acquisition, stress processing, and cross-modal cognitive studies. Scientific Awards : No explicit awards mentioned in the provided data. Teaching Activities include courses in educational psychology, developmental psychology, and diagnostics. She has participated in multiple international workshops on infant language development, eye-tracking methodology, and mixed-effects modeling.

Ekta KhemaniView profile

Assistant Professor

• Anesthesia
• Patient Safety
• Quality Improvement in Healthcare
• +3 more

Ekta Khemani is an Assistant Professor in the Department of Anesthesia within the Faculty of Health Sciences at McMaster University. Her academic career spans nearly two decades with consistent scholarly output from 2006 to the present, including publications extending into 2025. Dr. Khemani's research interests focus on practical applications in clinical settings, with particular emphasis on patient safety, quality improvement in healthcare delivery, anesthesia practice optimization, and healthcare economics. Her work demonstrates a strong commitment to addressing real-world challenges in medical practice, especially in anesthesia services and patient care processes. Analysis of her publication history reveals evolving research priorities. Early work focused on pediatric conditions and medical education, while more recent publications heavily address pandemic-related challenges in anesthesia, cost reduction strategies, and patient safety improvements. Her research consistently bridges clinical practice with academic inquiry, often employing quality improvement methodologies and evidence-based approaches. Her scholarly impact is evident through significant readership on academic platforms like Mendeley, with multiple publications garnering over 40 readers, and broader influence shown by references in policy sources, Wikipedia pages, and news outlets. Dr. Khemani's work demonstrates leadership in regional healthcare improvement initiatives, particularly in anesthesia services and patient safety protocols within Canadian hospital systems. Her contributions span clinical practice improvement, medical education, and healthcare administration with a consistent focus on practical, implementable solutions.

Etienne VougaView profile

Associate Professor

• Physical simulation
• Geometry processing
• Discrete differential geometry
• +4 more

Etienne Vouga is an Associate Professor in the Department of Computer Science and the Institute for Computational Engineering and Sciences (ICES) at the University of Texas at Austin. His interdisciplinary research spans physical simulation, geometry processing, and computer graphics, with applications ranging from special effects in films like The Hobbit and Tangled to Artec's Shapify 3D portrait service. Education: PhD from Columbia Computer Graphics Group Postdoctoral research at Harvard SEAS Professor Vouga's research focuses on physical simulation of thin, elastic materials like cloth, hair, and paper, as they deform and collide. He has made significant contributions to discrete differential geometry, developing algorithms that better understand how geometric properties affect physical behavior of deformable objects. His work bridges computer graphics, computational mechanics, and scientific computing, with applications in special effects, 3D printing, architectural design, and biological modeling. He has pioneered approaches in inverse problems where desired outcomes drive the design process rather than simply simulating physical phenomena. Award Highlights: Best Paper Award at GECCO (2017) for Evolutionary Decomposition for 3D Printing Professor Vouga teaches Computer Graphics: Honors (CS 378H/CS 384G) and Physical Simulation (CS 395T) graduate courses every spring semester. He also serves as head coach of UT's competitive programming teams. His research group has developed several important software tools including Discrete Shell Code for shell simulation and Asynchronous Contact Mechanics Code for robust collision handling. While he is not actively expanding his research group significantly, he remains open to working with exceptional graduate students whose research interests align closely with his work in physical simulation and geometry processing.

• Italian Linguistics
• Language Education
• Mathematics Education
• +3 more

Dr. Silvia Demartini is a Professor at the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) , affiliated with the Department of Education and Learning and the Competence Centre for Mathematics Education (DDM). She teaches communication and writing courses within the Computer Science degree program at the University of Eastern Piedmont. Her academic journey began with a PhD in Italian Linguistics (2012), focusing on the history of Italian grammar and its teaching tools. Expertise in Italian grammar, language education, and interdisciplinary mathematics-Italian curriculum development Collaborative research with Silvia Sbaragli and Michele Canducci on educational materials Recipient of the Faculty's Best Graduate Student Award at both bachelor's and master's levels Her research spans textbook analysis, linguistic challenges in mathematics education, and innovative pedagogical frameworks. Recent publications include interdisciplinary approaches to geometry and language teaching, such as the 2023 article Mathematics in Rhyme and the 2022 book Parole, Numeri, Figure . Awards include the 2009 Subject Expert title for Italian Grammar. She collaborates on projects like Italmatica , addressing language-specialist communication in mathematics education.