جست‌وجوی استاد و پژوهشگر

Bob Jantzenمشاهده پروفایل

استاد

• General Relativity
• Cosmology
• Differential Geometry
• +۴ مورد دیگر

Robert T. Jantzen is a Professor in the Department of Mathematics and Statistics at Villanova University, affiliated with the College of Arts and Sciences. He holds an A.B. in Physics from Princeton University (1974) and a Ph.D. in Physics from UC Berkeley (1978), specializing in general relativity. His research focuses on mathematical general relativity, cosmology, differential geometry, and Lie groups, with collaborations at institutions like the University of Rome's ICRA. He teaches applied mathematics courses, coordinates the Differential Equations with Linear Algebra course, and advocates for active learning in STEM education. Notable awards include the 2018 Mendel Award. His work bridges mathematics and physics, exploring topics like gravitoelectromagnetism and spacetime splitting. He is an honorary member of the Italian research group G9 and contributes to interdisciplinary projects, including climate change advocacy. Education A.B. in Physics, Princeton University, 1974 Ph.D. in Physics, UC Berkeley, 1978 Research Interests Focuses on general relativity, cosmological models with symmetry, observer-based spacetime analysis, gravitoelectromagnetism, differential geometry, and applications of Lie groups. His work integrates abstract mathematics with physical interpretation, often using computational tools like Maple. Publications & Talks His articles appear in journals like Classical and Quantum Gravity and General Relativity and Gravitation . Recent talks include discussions on geodesics on pasta surfaces and relativity. He has organized international conferences, including Marcel Grossmann Meetings, and co-edited their proceedings. Teaching & Innovation Develops Maple-based educational resources for calculus and differential equations. Emphasizes active learning, problem-solving, and technical communication. Maintains extensive course materials, including quizzes, tests, and grade calculators. Collaborations & Outreach Collaborates with Italian researchers on relativistic astrophysics. Engages in public science communication and progressive activism, supporting independent media and climate change initiatives. Serves as faculty advisor for student groups like the Armenian Student Organization and Villanova Against Sweatshops. Labs & Teams Active in the International Center for Relativistic Astrophysics (ICRA) network and the Vatican Observatory collaboration. Leads interdisciplinary projects blending mathematics, physics, and technology.

Cesare Giulio Arditoمشاهده پروفایل

مدرس

• Modular Representation Theory
• Finite Group Theory
• Global-local Conjectures
• +۳ مورد دیگر

Cesare Giulio Ardito is a Lecturer in Pure Mathematics at the University of Manchester, where he also earned his PhD (2020). His research spans two core areas: mathematics focusing on modular representation theory and global-local conjectures in finite group theory, and education technology emphasizing the impact of generative AI on higher education frameworks. He holds a BSc and MSc from Sapienza University of Rome, followed by a PhD from the University of Manchester, and completed a PGCert in Higher Education. His educational qualifications include a PGDip in Higher Education (2022) and advanced training in mathematics pedagogy. Ardito is a Senior Fellow of the Higher Education Academy (SFHEA) and a Member of the Institute of Mathematics and its Applications (MIMA). His recent publications explore AI detection in assessments, blended learning optimization, and Cartan matrix properties in representation theory. Ardito has led the LMS-funded 'Research Reboot' project and presented widely on topics like AI ethics in education, student perceptions of generative AI, and STEM assessment strategies. He actively contributes to the Italian community in the UK through roles like Manchester Comites councillor and managing the I3Italy guidebook for expatriates.

Jakob Zechمشاهده پروفایل

استاد

• Uncertainty Quantification
• High-Dimensional Approximation
• Sparse-Grid Techniques
• +۴ مورد دیگر

Jakob Zech is a Professor at the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University since April 2020. Before this, he held postdoctoral positions at MIT (2019-2020) and ETH Zürich (2018-2019). He earned his PhD in Mathematics from ETH Zürich in 2018, focusing on Sparse-Grid Approximation of High-Dimensional Parametric PDEs, followed by a Master’s (2014) and Bachelor’s (2012) in Applied Mathematics from ETH Zürich and TU Wien, respectively. Research Interests : Zech’s work bridges Uncertainty Quantification (UQ), high-dimensional approximation, and computational mathematics. Key areas include sparse-grid techniques, neural networks, transport methods, Bayesian inverse problems, and the theoretical foundations of deep learning. His research emphasizes developing algorithms for stochastic modeling and analyzing their mathematical properties. Teaching : He has taught advanced courses such as High Dimensional Approximation, Theory of Deep Learning, and Numerical Methods for Bayesian Inverse Problems at Heidelberg University. He also served as a teaching assistant for numerous courses at ETH Zürich, covering numerical analysis, partial differential equations, and linear algebra. Publications : His recent work explores quantum computing applications in polynomial chaos expansions, statistical learning theory for neural operators, and multilevel optimization strategies. His articles reflect a strong focus on combining classical numerical methods with modern machine learning techniques. Labs/Teams : While no specific lab is mentioned, his research group is active in computational UQ and deep learning, collaborating internationally with institutions like MIT and ETH Zürich.

Fabian C. Mossمشاهده پروفایل

استادیار

• Computational Musicology
• Music Theory
• Digital Humanities
• +۴ مورد دیگر

Fabian C. Moss is an Assistant Professor for Digital Music Philology and Music Theory at Julius-Maximilians-Universität Würzburg (JMU), Germany. His research bridges humanities and computational methods, focusing on interdisciplinary approaches to music structure, including musicology, mathematics, data science, and digital humanities. He leads projects such as DigiMusTh (building a digital collection of historical music theory texts) and Digital Choro (exploring Brazil’s musical heritage). He is also part of the Zentrum für Philologie und Digitalität (ZPD) and the Graduate School Humanities (GSH) at JMU. Before joining JMU, Moss held positions as a Research Fellow in Cultural Analytics at the University of Amsterdam and as a postdoctoral and doctoral researcher at École Polytechnique Fédérale de Lausanne (EPFL). He has conducted research visits at MIT and Escola Superior de Música de Catalunya (ESMUC). His work emphasizes computational modeling, corpus studies, and historical music analysis, with a focus on tonal evolution, harmonic progressions, and digital tools for musicology. Moss teaches courses in computational musicology, music theory, and digital tools. He serves on advisory boards for journals like Computational Humanities Research and Analitica , and actively contributes to conferences and workshops. His research outputs include datasets, software tools (e.g., MonodiKit, midiVERTO), and interdisciplinary analyses of musical corpora.

John R. Haddockمشاهده پروفایل

استاد

• Ordinary Differential Equations
• Functional Differential Equations
• STEM Education
• +۳ مورد دیگر

John R. Haddock is a Professor of Mathematical Sciences at the University of Memphis, holding the Dunavant Professorship since 2009. With continuous service since 1980, he serves as an NSF Program Officer under the Intergovernmental Personnel Act and co-founded the Center for Research & Innovation in STEM Teaching And Learning (CRISTAL). His leadership includes interim roles as Department Chair and College of Arts & Sciences Dean. Haddock's research bridges theoretical mathematics and educational innovation. In differential equations, he investigates stability theory, invariance principles, and qualitative behavior of solutions for functional and integral equations. His STEM education work focuses on undergraduate retention, developing programs like MemphiSTEP and Math Bridge Bootcamps to address challenges in mathematics instruction through blended learning and targeted interventions. His publication trends reveal dual trajectories: ongoing contributions to mathematical theory (evidenced by 2023 work on Lyapunov methods) and impactful educational scholarship, particularly in blended instruction effectiveness and STEM talent expansion. This synergy positions him at the intersection of advanced mathematics and pedagogical innovation. Honors include: Thomas W. Briggs Foundation Teaching Award (2011) Dunavant Professorship of Mathematics (2009) PAEMST National Selection Committee membership Mathematical Association of America Professional Development Committee (2009-2012) Meritorious Faculty Award (1992) Haddock has advised five PhD students to completion and secured over $4 million in external funding. Key grants include the $2M NSF MemphiSTEP program (2007-2014), ONR's $1.5M Shareable Knowledge Objects project (2013-2014), and Tennessee's Math-Science Partnership ($600k, 2007-2010). His work emphasizes translating research into practical educational strategies. As CRISTAL co-founder and co-director (2010-2012), he fostered interdisciplinary collaboration in STEM education. His documentary film production and museum curation on Memphis baseball history demonstrate commitment to community engagement beyond traditional academic boundaries.

Yoon Kimمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Yoon Kim is an Assistant Professor at MIT, affiliated with the departments of Computer Science (CS), Electrical Engineering (EE), and the AI+D initiative within the School of Engineering. His research focuses on artificial intelligence, machine learning, natural language processing, and speech processing, with notable work on vision-language models and large language models (LLMs). He was named an AI2050 Early Career Fellow in 2024. His recent studies address critical issues like LLMs' failure to handle negation in high-stakes contexts and the ethical implications of retrieval-augmented systems in medical communication. Kim’s work bridges theoretical advancements and practical applications, including optimizing transformer architectures, improving model robustness, and exploring semantic representations across languages and modalities. His publications often emphasize hardware-efficient training and inference techniques, reflecting his interest in scalable AI systems. Collaborative projects with interdisciplinary teams highlight his commitment to advancing both technical and societal aspects of AI.

• Mathematics Education (K-University)
• Indigenous Mathematics Education
• Cognitive Load Theory in Mathematics
• +۳ مورد دیگر

Dr. Bronwyn Reid O'Connor is a Senior Lecturer in Secondary Mathematics Education at the University of Sydney, based in the Sydney School of Education and Social Work. Her research focuses on mathematics curriculum design, Indigenous education, cognitive load theory, and error analysis. She teaches undergraduate and graduate courses in mathematics education. Current research students include Jenny BUI (dosage effects in learning), Michelle CHEUNG (teacher implementation of challenging tasks), and Kelly PADAYACHEE (assessment reform in NSW). Research interests span K-University mathematics education, learning and cognition, and Indigenous mathematics education. Notable grants include the 2022 'Promoting Adolescents Mathematics Engagement' project (NSW Education Fund) and the Equity Prize: Brown award. Publications emphasize Indigenous student proficiency, teacher curriculum competence, and student misconceptions in ratio problems. Collaborations include projects on online learning platforms and mathematics proficiency in the Australian Curriculum.

Brian Plancherمشاهده پروفایل

استادیار

• Robotics
• Embedded Systems
• Machine Learning
• +۳ مورد دیگر

Brian Plancher is an Assistant Professor of Computer Science at Barnard College, Columbia University, and will transition to Dartmouth College in Fall 2025. He leads the Accessible and Accelerated Robotics Lab (A²R Lab), focusing on optimizing robotic systems through algorithm-hardware-software co-design. His research spans Robotics, Embedded Systems, and Machine Learning, with an emphasis on accessibility in STEM education and global TinyML initiatives. He co-chairs the TinyMLedu Open Education Initiative and serves on the IEEE RAS Technical Committee. Education: PhD (2022), MEng (2018), and BA (2013) in Computer Science from Harvard University. Research Interests: Developing open-source algorithms for dynamic motion planning, GPU-accelerated optimization, and education initiatives to lower barriers in robotics and embedded ML. Recent efforts include TinyMPC (microcontroller optimization) and MPCGPU (real-time NMPC on GPUs). Grants & Awards: NSF CSSI Grant (2024), Toyota Research Institute Grant (2025), and best paper/poster awards at IEEE ICRA and robotics conferences. His work emphasizes sustainability, ethics, and global accessibility in AI and robotics. Lab & Teaching: Teaches Parallel Optimization for Robotics at Barnard and organizes the Optimization for Robotics Summer School. Collaborates internationally on TinyML4D to scale education in developing countries.

George E. Kusterمشاهده پروفایل

دانشیار

• Mathematics Education
• Differential Equations
• Inquiry-Oriented Instruction
• +۲ مورد دیگر

George E. Kuster is an Associate Professor in the Department of Mathematics at Christopher Newport University (CNU), with affiliations to the Center for Sustainability in Education and the Honors Program. He earned his Ph.D. and M.S. in Mathematics from Virginia Polytechnic Institute and State University, and a B.S. in Mathematics with a Psychology minor from St. Joseph's College. Research Interests : Learning and teaching of mathematics Student thinking in differential equations Inquiry-oriented instructional design Connections between pedagogy and student learning outcomes Grants : Co-PI, "Recruiting, Preparing, and Producing STEM Teacher-Scholars: The CNU Noyce Scholarship Program" (NSF-sponsored) Co-PI, "Preparing Highly-Qualified STEM Teachers: Supporting Student-Centered Instruction" (NSF-sponsored) Contributions : Developed the Inquiry-Oriented Instructional Measure (IOIM) to assess inquiry-based teaching effectiveness Explored variational reasoning and function understanding in differential equations

Riley Casperمشاهده پروفایل

استادیار

• Orthogonal Polynomials
• Integrable Systems
• Spectral Theory
• +۴ مورد دیگر

W. Riley Casper is an Assistant Professor of Mathematics at California State University, Fullerton (CSUF). His research focuses on the interplay between noncommutative algebra, algebraic geometry, and integrable systems, with applications to special functions and computational fluid dynamics. He holds a PhD from the University of Washington and dual MS/BS degrees from North Dakota State University. Dr. Casper teaches a wide range of courses at CSUF, including Calculus, Differential Equations, Real/Complex Analysis, Abstract Algebra, and Topology. His work spans both pure and applied mathematics, with recent contributions to matrix-valued differential operators, bispectrality, and prolate spheroidal wave functions. He has collaborated with institutions like Louisiana State University and the University of California, Berkeley on projects blending algebraic methods with computational techniques. Selected publications include studies on fractional differential operators, prolate spheroidal systems, and ocean data assimilation. His research has appeared in journals like Communications in Mathematical Physics and the American Journal of Mathematics. Teaching innovations include advanced problem-solving methodologies and applications of algebraic geometry in undergraduate instruction. Professional service includes organizing conferences (GAP XVI, ICM Satellite) and delivering invited talks at institutions worldwide. His work bridges theoretical mathematics with computational challenges in fluid dynamics and quantum computing.

Margaret Smithمشاهده پروفایل

دانشیار

• Mathematics Education
• Mathematical Problem Solving
• Cross-National Education Studies
• +۳ مورد دیگر

Dr. Margaret Smith is an Associate Professor of Mathematics Education at Iona University. She holds a Ph.D. in Curriculum and Instruction from the University of Delaware, an MA in Mathematics from Villanova University, and a BS in Physical Science with a Mathematics Concentration from York College of Pennsylvania. Her research focuses on how teachers design and implement mathematically rich and engaging lessons, with a particular emphasis on mathematical problem solving and cross-national comparisons of mathematics teaching methodologies. She has contributed to high-profile projects such as the TIMSS Video Study, Project 2061, and Algebra Learning for All, aiming to enhance teacher effectiveness in fostering critical thinking and problem-solving skills in students. In 2023, Iona University, under her involvement, secured a $1.5 million National Science Foundation (NSF) grant to support STEM educator development. Her work bridges research and practice, emphasizing evidence-based strategies to improve mathematics education globally.

Rena Stroudمشاهده پروفایل

دانشیار

• STEM Education
• Early Algebra
• Mathematics Pedagogy
• +۳ مورد دیگر

Rena Stroud is an Associate Professor of Education at Merrimack College's School of Education and Social Policy. She specializes in STEM education, early algebra development, and the integration of technology in teaching. Her research focuses on quantitative methodologies, including hierarchical linear modeling and structural equation modeling, and she explores how children develop mathematical knowledge through innovative instructional strategies. Dr. Stroud holds a Ph.D. and M.S. in Developmental Psychology from the University of Massachusetts Amherst and a B.A. in Psychology from Saint Anselm College. Her expertise includes educational technology, math pedagogy, and teacher preparation. Her research interests emphasize early algebra interventions, particularly in K-5 settings, and the role of tools like balance scales and gestures in fostering algebraic reasoning. She has published extensively in top-tier journals such as the Journal for Research in Mathematics Education and presented at conferences like AERA and NARST. Key contributions include studies on the persistence of early algebra knowledge post-intervention and strategies to enhance students' understanding of mathematical equivalence and parity concepts. Her work bridges cognitive development theory with practical classroom applications.

• Mathematics Education
• Statistical Methods
• Data Science Pedagogy
• +۳ مورد دیگر

Jon-Paul N Paolino is an Associate Professor and Program Director of Mathematics at the School of Liberal Arts, Mercy College. His work focuses on advancing statistical pedagogy and educational assessment techniques through innovative approaches to teaching mathematics and data science. His research interests include applying statistical methods like principal component analysis, Rasch models, and machine learning algorithms to improve educational outcomes. He emphasizes practical teaching methods such as contour plots for linear correlation and loss functions for univariate analysis. His publications from 2013–2024 reflect a consistent focus on integrating advanced statistical techniques into educational contexts, particularly in item response theory and data science curriculum design. No academic awards are explicitly mentioned in the provided materials. No advising relationships or grant funding details were explicitly disclosed in the source text. His affiliation with Mercy College’s School of Liberal Arts underscores his role in bridging mathematical theory with liberal arts education.

Steven Lippoldمشاهده پروفایل

استادیار

• Multilinear Algebra
• Generalizations of Linear Algebra Concepts
• Combinatorics

Steven Lippold is an Assistant Professor of Mathematics at Geneva College. He holds a B.S. in Mathematics and Physics from Clarion University of Pennsylvania (2017), an M.A. in Mathematics from Bowling Green State University (2018), and a Ph.D. in Mathematics from Bowling Green State University (2023). His research focuses on Multilinear Algebra, Generalizations of Linear Algebra Concepts, and Combinatorics. His work includes studies on matrix structures, determinant-like functions, and hypergraph partitions. Dr. Lippold has been recognized with the Graduate Excellence in Teaching Award (2023), the Judyta & Bronislaw Blass Memorial Fellowship (2022), and the James Robert and Gretchen Overman Scholarship (2018-2019). He is a member of the Mathematical Association of America, Association of Christians in the Mathematical Sciences, and the American Mathematical Society. His professional certifications include Python for Data Science and Machine Learning (Udemy, 2023), Teaching and Learning Certificate (Bowling Green State University, 2020), and Google IT Automation with Python (2021). His academic journey includes consistent academic excellence, reflected in his Dean’s List status at Clarion University (2014-2017) and membership in honor societies like Phi Kappa Phi and Pi Mu Epsilon. His research contributions span algebraic structures, linear algebra extensions, and combinatorial applications, with recent publications in Linear Algebra and Its Applications and Monatshefte fu¨r Mathematik .

Darryl Chamberlain Jr.مشاهده پروفایل

استادیار

• Educational Data Science
• Mathematics Education
• Online Learning Technologies
• +۵ مورد دیگر

Dr. Darryl Chamberlain Jr. is an Assistant Professor and Associate Department Chair of Mathematics, Science, and Technology at Embry-Riddle Aeronautical University’s College of Arts and Sciences. He holds a Ph.D. in Mathematics and Statistics (2017) from Georgia State University and a B.S. in Mathematics (2010) from the University of Florida. His research focuses on educational data science, leveraging machine learning and theoretical frameworks to analyze student learning in mathematics and technology-enhanced education. He has developed innovative teaching strategies for online and large-scale courses, emphasizing mastery-based learning and asynchronous collaboration. Education: Ph.D. in Mathematics and Statistics, Georgia State University (2012–2017) B.S. in Mathematics, University of Florida (2007–2010) Research Interests: Dr. Chamberlain’s work centers on cognitive development in precalculus, technology integration in education, curriculum design, and assessment validation. He explores how asynchronous learning environments and generative AI can enhance student engagement and knowledge construction. His projects often involve analyzing discussion board interactions and developing frameworks for collective knowledge progression. Grants & Projects: PI: Autonomous Procedural and Conceptual Interactive Lessons (NSF-funded) Co-PI: Community of Inquiry and Cognitive Load (NSF-funded) Co-PI: Generative AI Feedback Across the Disciplines (Internal Funding) Service & Leadership: Chair of MAA Subcommittee on Technologies in Mathematics Education Member of NSF Grant Review Panels Acting Chair of ERAU-WW Department of Mathematics, Science, and Technology Labs/Teams: He is a key member of the Academic Technology Committee and contributes to the development of the Applied Data Science Minor at ERAU.