جست‌وجوی استاد و پژوهشگر

Alex Blumenthalمشاهده پروفایل

استادیار

• Dynamical Systems
• Smooth Ergodic Theory
• Chaos Theory
• +۳ مورد دیگر

Alex Blumenthal is an Assistant Professor in the School of Mathematics at the Georgia Institute of Technology since Fall 2020. His academic background includes a Ph.D. from New York University (2016) with a dissertation titled 'Nonuniformly hyperbolic theory for Banach space mappings.' Prior to joining Georgia Tech, he held positions as an instructor at the University of Maryland, teaching courses in probability theory, linear algebra, and precalculus, and served as a recitation leader at New York University for courses in chaos theory, differential equations, and analysis. Blumenthal's research focuses on dynamical systems and ergodic theory, with specialization in: Chaotic behavior in deterministic and stochastic systems Smooth ergodic theory and SRB measures Lyapunov exponents in random dynamical systems Stochastic fluid mechanics and turbulence modeling Infinite-dimensional dynamical systems on Banach spaces Statistical properties of complex systems His work bridges abstract mathematical theory with physical applications like fluid dynamics and statistical mechanics. Analysis of his recent publications shows strong emphasis on stochastic dynamics, Lyapunov exponents, and fluid mechanical systems, with mathematical techniques drawn from ergodic theory, functional analysis, and probability theory. His publications frequently appear in top mathematical physics and dynamics journals. No scientific awards or honors are mentioned in the source materials. Similarly, no information is available regarding research grants, student advising, or laboratory affiliations.

Irene Duranczykمشاهده پروفایل

دانشیار

• Mathematics Education
• Community College Mathematics Education
• Developmental Mathematics Education
• +۳ مورد دیگر

Irene Duranczyk is an Associate Professor of Mathematics Education in the Department of Curriculum and Instruction at the University of Minnesota's College of Education. Her work focuses on advancing mathematical literacy at the undergraduate level, with particular attention to creating equitable educational opportunities through community engagement and multicultural perspectives. As a first-generation college student from a working-class family, she brings personal experience to her commitment to addressing educational inequalities. Her educational background includes an EdD from Grambling State University's College of Education, with a focus on Developmental Education: Higher Education Administration and Management, and a cognate in Mathematics Education. Duranczyk's research centers on understanding institutional barriers and cognitive/affective blocks students face in college mathematics, with particular emphasis on community college mathematics education. She employs a multicultural equity pedagogy framework and integrates universal instructional design principles into her work. Her research aims to develop pedagogical processes and assessment practices that prepare students for success in college-level mathematics, thereby expanding opportunities for students to complete college education and pursue degrees requiring advanced mathematical skills. Her recent scholarly output reveals a strong focus on measuring and improving the quality of algebra instruction at community colleges. Through NSF-funded research, she has developed instruments to assess mathematical knowledge for teaching college algebra and investigated conditions under which algebra courses improve student learning. Her work spans multiple methodologies including video analysis of classroom instruction, cognitive interviews with faculty, and psychometric analysis of assessment tools. National Science Foundation Principal Investigator (2020-2023, $501,852) National Science Foundation Supplemental Funds (2024-2025, $100,370) 2007 National Association for Developmental Education (NADE) Outstanding Research Conducted by a Developmental Education Practitioner Award Duranczyk has secured significant grant funding, most notably a three-year, $2.3 million NSF grant (as co-PI with Nidhi Kohli, Vilma Mesa, April Strom, and Laura Watkins) to study algebra instruction at community colleges. This project investigates conditions under which algebra courses improve student learning across six community colleges in three states, focusing on linear equations, rational equations, and exponential equations. She has also been involved in international collaborations with educators in Russia and China, and participates in faculty learning communities focused on international and multilingual student success. Her work extends to the development of Integrated Multicultural Instructional Design (IMID) frameworks for postsecondary settings and Multicultural Equity Pedagogy for online education, reflecting her commitment to creating inclusive learning environments that address diverse student needs.

Tharindu P. De Alwisمشاهده پروفایل

استادیار

• High-dimensional Multivariate Statistics
• Sufficient Dimension Reduction
• Dimension Reduction
• +۹ مورد دیگر

Dr. Tharindu P. De Alwis is an Assistant Professor in the Department of Mathematics and Statistics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He is actively engaged in teaching and research, with a focus on high-dimensional data analysis and machine learning applications. Ph.D. in Mathematics (Statistics), Southern Illinois University Carbondale M.S. in Mathematics, Southern Illinois University Carbondale B.Sc. in Statistics and Operations Research, University of Peradeniya, Sri Lanka His research centers on dimension reduction techniques, particularly Sufficient Dimension Reduction (SDR), envelope methods, and their applications in multivariate time series and spatial-temporal data. He integrates deep learning and neural networks into statistical modeling, with recent work on stacking-based deep neural networks and Fourier-based SDR methods. His work bridges statistical theory with practical machine learning applications in complex datasets. His recent publications (2021–2024) demonstrate a strong focus on developing innovative statistical and machine learning methods for time series and high-dimensional regression. Key themes include nonlinear modeling, dimension reduction, R package development, and AI-augmented reliability analysis. These works reflect interdisciplinary applications in engineering, data science, and systems safety. Dr. De Alwis has presented his research at national academic conferences in the USA and has publications in peer-reviewed journals such as Statistical Methods & Applications and Reliability Engineering & System Safety , as well as preprints on arXiv and software on CRAN. He teaches a variety of courses including Precalculus with Trigonometry, Linear Algebra, Applied Statistics, and Data Science. While no formal advisees or grants are mentioned, his active publication record suggests ongoing research mentorship and scholarly engagement. He previously served as a post-doctoral scholar at Worcester Polytechnic Institute before joining UWF.

Meiqin Liمشاهده پروفایل

دانشیار

• STEM Education
• Mathematics Education
• Engineering Education
• +۵ مورد دیگر

Dr. Meiqin Li is an Associate Professor of Applied Mathematics at the University of Virginia (UVA) and a Faculty Fellow at the UVA Center for Teaching Excellence. She joined UVA in 2017 after earning her Ph.D. in Applied Mathematics from Texas A&M University. Her research focuses on STEM education innovation, particularly integrating technology into classrooms, fostering inclusive learning environments, and optimizing curricula for engineering students. She also explores numerical computation, optimization, and nonlinear analysis in applied mathematics. Dr. Li’s educational background includes a Ph.D. from Texas A&M University, College Station, TX (2017). Her teaching portfolio spans courses like APMA 3080 (Linear Algebra) and APMA 2501 (Programming in R & MATLAB), reflecting her commitment to computational and pedagogical excellence. Her research interests emphasize active learning strategies, curriculum redesign for equity, and leveraging MATLAB/Autograder tools in education. Recent publications highlight outcomes from integrating precalculus into calculus courses and enhancing linear algebra instruction through technology. Awards: 2025 ASEE Mathematics Division Best Paper Award 2024 SoTL Dissemination Award (UVA Center for Teaching Excellence) 2020 Thomas E. Hutchinson Award Finalist Dr. Li’s work bridges pedagogical innovation and applied mathematics, with grants and recognitions underscoring her impact in teaching and research. She actively contributes to UVA’s engineering education community and promotes student success through inclusive practices.

Irina Lyublinskayaمشاهده پروفایل

استاد

• STEM Education
• Mathematics Education
• Science Education
• +۵ مورد دیگر

Irina Lyublinskaya is a Professor of Mathematics and Education at Teachers College, Columbia University. She is affiliated with the Mathematics, Science & Technology department and specializes in STEM education, mathematics education, and educational technology. Her research interests include teacher education, international education, and curriculum development. Lyublinskaya holds a Ph.D. and M.S. in Theoretical and Mathematical Physics from Leningrad State University (now St. Petersburg State University). Her scholarly work spans over three decades, with a focus on integrating technology into mathematics and science education. Notable contributions include co-authoring textbooks such as Geometry investigations with GeoGebra and Exploring precalculus with The Geometer’s Sketchpad . Her recent research emphasizes culturally responsive teaching, TPACK framework applications, and robotics integration in elementary education. Lyublinskaya’s publications explore topics like teacher professional development, special education technology competency, and cross-cultural STEM pedagogy. She has mentored students such as Xiang Du and Alyssa Kaplon-Schilis, who co-authored impactful studies on TPACK trajectories and culturally relevant mathematics tasks. Her work bridges theoretical research and practical classroom applications, advocating for innovative educational technologies.

Justin Grayمشاهده پروفایل

مدرس ارشد

• Mathematics Education
• Educational Technology
• Online Learning
• +۳ مورد دیگر

Justin Gray is a Senior Lecturer and Associate Chair (Undergraduate Learning) in the Department of Mathematics at Simon Fraser University (SFU). He holds a central role in shaping undergraduate education within the Faculty of Science. His research and professional focus revolves around enhancing mathematics education through innovative online assessment tools. He is recognized as a leading Canadian expert in leveraging digital platforms to evaluate and improve students' mathematical proficiency. His work emphasizes practical applications of technology to bridge gaps in educational outcomes. No scientific awards or grants are explicitly listed in the provided materials. His teaching responsibilities include courses such as MATH 100 D100 Precalculus for Fall 2025. While no student advisees or lab affiliations are mentioned, his role as Associate Chair underscores his institutional contributions to academic governance and curriculum development.

• Mathematics Education
• Undergraduate Mathematics
• STEM Education Initiatives
• +۲ مورد دیگر

Joungdong Kim is an Instructional Associate Professor at Texas A&M University, affiliated with the College of Arts & Sciences. He holds an office in Blocker 300B and oversees various academic initiatives. His work focuses on enhancing undergraduate mathematics education through programs like the Research Experience for Undergraduates (REU), Math Circle, SMaRT Camp, and Personalized Precalculus. He is actively involved in outreach activities, including the High School Math Contest and Math Awareness Month. Kim contributes to academic administration and computing resources management within the department.

• Analysis
• Partial Differential Equations
• Harmonic Analysis
• +۵ مورد دیگر

Cheikhna Mahawa Diagana serves as a Lecturer in the Department of Mathematics at the City College of New York (CCNY), part of the City University of New York (CUNY) system, with documented teaching activity spanning from 2008 to Summer 2025. He maintains an active instructional role across the undergraduate mathematics curriculum at CCNY. His research focuses on core areas of mathematical analysis, including Partial Differential Equations, Harmonic Analysis, Functional Analysis, and Complex Analysis with particular attention to manifolds. Recent explorations examine intersections between Partial Differential Equations and elliptic curves/elliptic functions, reflecting evolving theoretical interests within analytical frameworks. Dr. Diagana's extensive teaching portfolio demonstrates consistent contribution to foundational mathematics education, having instructed courses such as Calculus I-III, Precalculus, Linear Algebra, Elements of Calculus, and Methods of Differential Equations. He is scheduled to teach two sections of Calculus I during Summer 2025, continuing his long-standing commitment to undergraduate instruction at CCNY.

• Mathematics
• Mathematics Education
• Algebra
• +۳ مورد دیگر

Sevan Bharathan is a Lecturer in the Department of Mathematics at The City College of New York. They are based in the office MR 326 and can be reached via phone at (212) 650-5105. Their teaching responsibilities focus on foundational mathematics courses at both undergraduate and graduate levels, though specific research interests are not explicitly stated in the provided materials. Sevan has taught courses such as Precalculus AB (Math 19500) in Fall 2024, College Algebra and Trigonometry A3 (Math 19000) in Spring 2024, Precalculus BC (Math 19500) in Fall 2023, and Mathematics for the Contemporary World M (Math 15000) in Spring 2023. They are not scheduled to teach during the Summer 2025 semester. They are affiliated with the Artino Mathematics Tutoring Center and participate in institutional events like the Pi Day celebration organized by the Artino Lab . No scientific awards or grants are documented in the provided content.

• Mathematics
• Applied Mathematics
• Calculus
• +۳ مورد دیگر

Susan Rutter is a Lecturer in the Department of Mathematics at the CUNY Graduate Center, where she teaches foundational undergraduate courses including Precalculus (Math 19500) and Calculus II (Math 21200). She is based in Office MR 326, reachable at (212) 650-5105, and serves as a Graduate Teaching Fellow. Her role emphasizes mathematics education and student engagement in STEM disciplines. Research Interests highlight Mathematics and Applied Mathematics, with a focus on Calculus instruction and pedagogical strategies for undergraduate education. Her teaching aligns with broader goals in mathematical education and curriculum development. Contact & Teaching History : Email: srutter@gc.cuny.edu Recent Courses: Math 19500 (Precalculus, Fall 2024), Math 21200 (Calculus II, Fall 2024, Spring 2024, Fall 2023)

Charles Dalyمشاهده پروفایل

استادیار مهمان

• Geometric Structures on Manifolds
• Rigidity Theory
• Affine Geometry
• +۴ مورد دیگر

Charles Daly is a Visiting Assistant Professor in the Department of Mathematics at Brown University. He received his PhD in August 2021 from the University of Maryland under the supervision of Professor William Goldman. His academic career includes teaching various mathematics courses at both Brown University and the University of Maryland. Daly's research focuses on geometric structures on manifolds, with particular emphasis on rigidity results. His work combines abstract mathematical theory with computational approaches to verify theoretical results. He has made significant contributions to the understanding of affine and convex projective manifolds, local rigidity phenomena, and representation varieties of hyperbolic 3-manifolds. His recent publications demonstrate a strong focus on projective rigidity of once-punctured torus bundles and computational approaches to geometric structures. Daly's work bridges theoretical mathematics with practical computational verification, using techniques like interval arithmetic to validate complex geometric properties. Daly has taught a wide range of mathematics courses at Brown University, including Topology, Multivariable Calculus, and Introduction to Lie Algebras. At the University of Maryland, he taught various undergraduate mathematics courses including Calculus, Linear Algebra, and Precalculus.

• Mathematics Education
• Teacher Preparation
• Curriculum Development
• +۱ مورد دیگر

Dr. Janessa Michele Beach is Assistant Professor of Instruction in the Mathematics Department at The University of Texas at Arlington. Her work focuses on mathematics teacher preparation and curriculum development. Education includes a Ph.D. in Mathematics from UTA (2020), M.S. from Texas A&M University-Commerce, and B.S. from Abilene Christian University. She teaches courses across mathematics and mathematics education. Research examines: Development of mathematical knowledge in teachers Innovative approaches to secondary mathematics instruction Task design for teacher education Technology integration in mathematics Visual representations in mathematics learning Current grants support projects on inquiry-based precalculus instruction and active learning approaches in calculus. Awards recognize teaching excellence and innovative instruction.

• Mathematics
• Applied Mathematics
• Quantitative Reasoning
• +۳ مورد دیگر

Patrick Okpo is a Lecturer at the City College of New York, where he has taught a variety of undergraduate mathematics courses since 2012. His current role involves teaching Precalculus and Quantitative Reasoning, with office hours held both online and in person. Over the years, he has instructed courses such as College Algebra and Trigonometry, Basic Ideas in Mathematics, and Mathematics for the Contemporary World, reflecting his focus on foundational and applied mathematics. Email: pokpo@ccny.cuny.edu Recent Teaching (2025): Math 19500-1XD: Precalculus (Summer, MoTuWeTh 3:20PM-5:00PM in NAC 5/102) Past Teaching History: Math 18000: Quantitative Reasoning (Spring 2025, Spring 2024, 2023, etc.) Math 19500: Precalculus (Summer, Spring, and Fall semesters across multiple years) Math 19000: College Algebra and Trigonometry (Fall 2023, Spring 2018, etc.) Math 18500: Basic Ideas in Mathematics (Fall 2022, Summer 2021, etc.) Office Hours: Wednesdays online (Zoom ID 243 016 0740, 1:00 pm - 2:00 pm) Thursdays in person (6:00 pm - 8:00 pm in Room NAC 6/413)

• Applied Mathematics
• Mathematical Physiology
• Oxygen Transport Modeling
• +۳ مورد دیگر

Brooke McGuire is an Assistant Professor in the Department of Mathematics at the College of Science and Mathematics, University of Arizona. Her academic appointment reflects a strong interdisciplinary focus, bridging applied mathematics and biomedical sciences. Educational Background: Ph.D. in Bioengineering and Biomedical Engineering, University of Arizona, 2003 MS in Applied Mathematics, University of Arizona, 1997 BS in Applied Mathematics, University of Rochester, 1994 Her research focuses on theoretical modeling of physiological systems, particularly oxygen transport dynamics in skeletal muscle and macromolecular behavior in vascular tissues. Using mathematical frameworks, she investigates transport limitations, capillary density estimation, and metabolic responses under stress conditions such as hypoxia. Her work contributes to foundational understanding in exercise physiology and biomedical engineering. The analysis of her publications reveals a consistent theme in mathematical physiology, with emphasis on modeling oxygen consumption, diffusion processes, and vascular transport phenomena. These studies employ theoretical frameworks to explore biological constraints and predict system behavior under extreme physiological demands. Scientific Awards: Outstanding Teacher Award 2016-2017, Department of Mathematics Brooke McGuire has contributed to academic service through roles such as Committee Member on the Faculty Grievance Committee (2017–2020). She has also engaged in public service with the Gertrude Herbert Institute of Art. While no formal advising or grant activity is listed, her teaching portfolio includes core mathematics courses such as College Algebra and Precalculus Mathematics. There is no indication of lab affiliations or research teams in the available data.

Kelly Clineمشاهده پروفایل

مدرس

• Mathematics Education
• Statistics Education
• Classroom Pedagogy
• +۴ مورد دیگر

Dr. Kelly Cline is a Lecturer at Carroll College , specializing in mathematics education and pedagogy. With a Ph.D. in Astrophysics from the University of Colorado at Boulder , he combines his scholarly background with innovative teaching methods such as classroom voting and active learning to engage students across disciplines including statistics, calculus, and astronomy. Ph.D. in Astrophysics, University of Colorado at Boulder His research focuses on improving mathematical instruction through project-based learning, educational technology, and discussion-provoking questions. He has developed classroom voting systems, programming integration frameworks, and manipulatives for geometry, while also exploring applied mathematical modeling in geophysics. His work bridges the gap between theoretical understanding and practical application in education. Recent publications highlight his expertise in using clickers and classroom voting to address misconceptions in statistics, calculus, and precalculus. These works emphasize curriculum innovation, formative assessment, and resource development for educators. His interdisciplinary approach includes geophysical modeling of avalanches using mathematical techniques. National Science Foundation Grant ($180,000, 2010-2013): Project MathVote National Science Foundation Grant ($100,000, 2006-2009): MathQUEST W. M. Keck Foundation Grant ($250,000, 2014-2018): Project InterStats Dr. Cline mentors students through the Mathematical Contest in Modeling (MCM) and founded the University Physics Competition , which now attracts global participation. His teaching portfolio includes statistics, calculus, differential equations, and data science, reflecting his broad expertise.