Never Stop Learning.
I am interested in employing culturally sustaining pedagogy and research-based assessment methods as a professor and welcome all feedback on my teaching.
Spring 2023 Courses
Math 102 - Introduction to Biostatistics
For all course content, please refer to the Canvas website.
If you can't make it to Student Consultation Hours, set up an appointment. In the meantime, take the music of my office with you.
Spring 2023 Student Support Hours
In-Person - Tue. 12:30 - 1:50pm, 4 - 5pm, Thur. 12:30 - 1:50pm,
Previous Courses (Fresno State)
Mathematical Models with Technology (MATH 232)
A technology-assisted study of the mathematics used to model phenomena in statistics, natural science, and engineering.
Topics include simple linear regression, parameter inference, interval estimation, prediction, diagnostics and remedial measures, multiple linear regression, model selection and validation, generalized linear models, ridge regression, LASSO.
Mathematical Modeling (MATH 123)
Application of mathematical techniques to solve selected problems in areas such as ecology, biology, economics, finance, social sciences, life sciences, physical sciences and engineering. The emphasis will be on building mathematical models and on interpreting the solutions of these models in terms of real-life applications.
Introduction to usage in mathematics and statistics including computer algebra software, interpreted object-oriented high-level programming language, one programming language related to statistics, database management, optimization, and cloud computing.
Introduction to Biostatistics (MATH 102)
Introduction to statistical methods used in biological experiments and data analyses, with emphasis on interpretation, presentation, and writing statistical reports. Topics include describing and visualizing data, sampling methods, probability, experimental design, hypothesis testing, regression, ANOVA and nonparametric tests.
Elementary Statistics (MATH 11)
Illustration of statistical concepts: elementary probability models, sampling, descriptive measures, confidence intervals, testing hypotheses, chi-square, nonparametric methods, regression.
Exploring Statistics (MATH 137)
Descriptive and inferential statistics with a focus on applications to mathematics education. Use of technology and activities for student discovery and understanding of data organization, collection, analysis and inference.
University of California, Merced
Linear Analysis (Math 141) - Teaching Assistant and Guest Lecturer
Applied linear analysis of finite dimensional vector spaces. Review of matrix algebra, vector spaces, orthogonality, least-squares approximations, eigenvalue problems, positive definite matrices, singular value decomposition with applications in science and engineering.
Complex Analysis (Math 122) - Teaching Assistant and Guest Lecturer
Introduction to complex variables, analytic functions, contour integration and theory of residues. Mappings of the complex plane. Introduction to mathematical analysis.
Calculus II for Physical Sciences and Engineering (Math 22) - Teaching Assistant
Analytical and numerical techniques of integration with applications, infinite sequences and series, first order ordinary differential equations.
Calculus I (Math 11) - Teaching Assistant
Introduction to differential and integral calculus of functions of one variable, including exponential, logarithmic and trigonometric functions, emphasizing conceptual understanding and applying mathematical concepts to real-world problems (approximation, optimization)
Robert F. Kennedy High School
Algebra I - High School Mathematics Teacher
Introduction to solving systems of equations, graphing, and investigating linear relationships.
California High School Exit Exam (CAHSEE) - High School Mathematics Teacher