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Debbie Yuster

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Debbie YusterAssociate Professor of Data Science and Mathematics

Year Joined RCNJ: 2020

Contact Information

Education:

  • Ph.D., Mathematics, Columbia University
  • B.A., Mathematics (concentration in Computer Science), Cornell University

Courses Offered:

Undergraduate:

  • CMPS 130 Scientific Problem Solving with Python
  • DATA 101 Introduction to Data Science
  • DATA 450 Data Science Capstone Project
  • MATH 108 Elementary Probability and Statistics
  • MATH 122 Calculus II
  • MATH 262 Linear Algebra

Graduate:

  • CMPS 530 Python for Data Science
  • DATA 601 Introduction to Data Science
  • DATA 620 Ethics in Data and Computing
  • MATH 562 Applied Linear Algebra

Research Interests:

  • Combinatorics
  • Polyhedral Geometry
  • Machine Learning

Recent Publications

  • E. Kupin and D. Yuster. Generalizations of the Goulden-Jackson cluster method. Journal of Difference Equations and Applications,Ìý16:12:1463-1480, 2010.
  • M.C. Rogers and D. Yuster. Insights from math-science collaboration at the high school level. In BioMath in the Schools, edited by M. Cozzens and F. Roberts, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, Vol.76, 2011.
  • I. Hallgrímsdóttir and D. Yuster. A complete classification of epistatic two-locus models. BMC Genetics,Ìý9:17,Ìý2008.
  • P. Huggins, B. Sturmfels, J. Yu, and D. Yuster. The hyperdeterminant and triangulations of the 4-cube. Mathematics of Computation,Ìý77(263):1653-1679, 2008.
  • J. Yu and D. Yuster. Representing tropical linear spaces by circuits. In Proceedings of FPSAC ‘07, 2007.
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