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Maggie Myers

Lecturer, Department of Statistics and Data Sciences at The University of Texas at Austin

Areas of expertise

  • Probability and Bayesian Statistical Methods
  • Mathematics Education
  • Mathematics Curriculum Development
  • Informal Learning
  • Formal Derivation of Algorithms

Major works

Linear Algebra: Foundations to Frontiers - Notes to LAFF With
by Maggie Myers, Pierce van de Geijn, and Robert van de Geijn

The Science of Deriving Dense Linear Algebra Algorithms
by Paolo Bientinesi, John A. Gunnels, Margaret E. Myers, Enrique S. Quintana-Orti, Robert A. van de Geijn

The Mathsters Series
by Maggie Myers

About Me

Dr. Maggie Myers was a lecturer for the Department of Computer Science and Division of Statistics and Scientific Computing. She taught undergraduate and graduate courses in Bayesian Statistics. Her research activities range from informal learning opportunities in mathematics education to formal derivation of linear algebra algorithms.

Earlier in her career she was a senior research scientist with the Charles A. Dana Center and consultant to the Southwest Educational Development Lab (SEDL). Her partnerships (in marriage and research) with Prof. van de Geijn have lasted for decades and seem to be surviving the development of this MOOC.

Courses and Programs taught by Maggie Myers