Kamrun Nahar Keya

Kamrun Nahar Keya is pursuing a Ph.D. in Applied Mathematics at Arizona State University (ASU), specializing in computational mathematics with a focus on optimization, data compression, and pattern recognition. Her academic journey began with a B.S. in Mathematics from the University of Dhaka, Bangladesh, where her passion for mathematical theory inspired her to pursue advanced studies. At ASU, she has become an integral part of the research community, contributing to projects such as online non-negative matrix factorization for streaming data and structure-aware CP tensor decomposition.

In addition to her research, Kamrun is deeply committed to education and has developed extensive experience as a Teaching Assistant (TA) at ASU. She has supported a wide range of courses, including Calculus I for Engineers, MATLAB laboratory sessions, precalculus recitations, Linear Algebra, and graduate qualifying courses such as Applied Analysis and Partial Differential Equations. In these roles, she has helped students engage with mathematics at multiple levels—guiding undergraduates through the fundamentals of calculus and computational problem-solving in MATLAB, while supporting graduate students as they navigate the rigorous theories of advanced analysis and differential equations. Her teaching philosophy emphasizes clarity, accessibility, and connection, ensuring that students not only learn the technical skills but also appreciate the broader relevance of mathematics.

Kamrun’s earlier research provided valuable insights into mathematical biology, particularly in ecological modeling and population dynamics. As her work evolved, she expanded her focus to data science, applying mathematical techniques to real-world, data-driven challenges. Currently, she is developing methods for online non-negative matrix factorization in streaming data, with applications in pattern recognition and data compression. This shift enables her to integrate computational mathematics with machine learning, addressing problems in large-scale data analysis and AI-driven applications.

Beyond her academic achievements, Kamrun is actively engaged in the mathematical community. She serves as President of the Association for Women in Mathematics (AWM) Student Chapter at ASU, where she advocates for representation, support, and visibility of women in mathematics. In this role, she organizes professional development talks, networking opportunities, and outreach activities that foster an inclusive and supportive environment for students. She also serves as Treasurer of the Society for Industrial and Applied Mathematics (SIAM) Student Chapter at ASU, contributing to the chapter’s programming and financial management, and creating opportunities for students to explore applied and interdisciplinary mathematics.

Outside of academia, Kamrun enjoys a range of creative and intellectual pursuits, including reading science fiction and thrillers, cooking, and crafting. These hobbies provide a well-rounded balance to her rigorous academic work.

Looking ahead, Kamrun is eager to further her research at the intersection of computational mathematics and data science. She is particularly interested in developing innovative mathematical frameworks and algorithms to address complex, data-driven challenges across diverse application areas. Through this work, she aspires to advance both the theoretical foundations and practical tools of applied mathematics, while making a meaningful and lasting impact in science and society.