Teaching Awards
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1. Postdoctoral Scholar Excellence Award (for Teaching and Mentoring Students), Iowa State University, 2021.
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2. MSCS Teaching Assistant Award, University of Illinois at Chicago, 2018.
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Students Evaluations
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RateMyProfessor (current one at UCSD)
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RateMyProfessor (students reviews (ISU))
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Past Teaching
Past, current and upcoming courses at University of California, San Diego:
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1. Precalculus (summer special session)
2. Introduction to Probability and Statistics (Large lecture, ≃ 400 students.)
Description: Events and probabilities, conditional probability, Bayes’ formula. Discrete and continuous random variables: mean, variance; binomial, Poisson distributions, normal, uniform, exponential distributions, central limit theorem. Sample statistics, confidence intervals, hypothesis testing, regression. Applications. Introduction to software for probabilistic and statistical analysis. Emphasis on connections between probability and statistics, numerical results of real data, and techniques of data analysis.
3. Mathematical Reasoning (Large lecture, ≃ 150 students.)
Description:This course uses a variety of topics in mathematics to introduce the students to rigorous mathematical proof, emphasizing quantifiers, induction, negation, proof by contradiction, naive set theory, equivalence relations and epsilon-delta proofs.
4. Introduction to Numerical Analysis (Large lecture, ≃ 170 students.)
Description: This course covers analysis of numerical methods for linear algebraic systems and least squares problems. Topics include orthogonalization methods. Ill conditioned problems. Eigenvalue and singular value computations.
5. Modern Algebra I (Large lecture, ≃ 140 students.)
Description: First course in a two-quarter introduction to abstract algebra with some applications. Emphasis on group theory. Topics include definitions and basic properties of groups, properties of isomorphisms, subgroups.
6. Modern Algebra II (Large lecture, ≃ 100 students.)
Description: Second course in a two-quarter introduction to abstract algebra with some applications. Emphasis on rings and fields. Topics include definitions and basic properties of rings, fields, and ideals, homomorphisms, irreducibility of polynomials.
7. Discrete Mathematics and Graph Theory (Large lecture, ≃ 175 students.)
Description: Basic concepts in graph theory, including trees, walks, paths, and connectivity, cycles, matching theory, vertex and edge-coloring, planar graphs, flows and combinatorial algorithms, covering Hall’s theorems, the max-flow min-cut theorem, Euler’s formula.
Description: Second course in linear algebra from a computational yet geometric point of view. Elementary Hermitian matrices, Schur’s theorem, normal matrices, and quadratic forms. Moore-Penrose generalized inverse and least square problems. Vector and matrix norms. Characteristic and singular values. Canonical forms. Determinants and multilinear algebra.
8. Applied Linear Algebra (Large lecture, ≃ 175 students.)
Description: Second course in linear algebra from a computational yet geometric point of view. Elementary Hermitian matrices, Schur’s theorem, normal matrices, and quadratic forms. Moore-Penrose generalized inverse and least square problems. Vector and matrix norms. Characteristic and singular values. Canonical forms. Determinants and multilinear algebra.
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9. Topics in Combinatorics (with a focus on Matroid Theory)
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Iowa State University as Instructor:
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1. Abstract Algebra I (Basic properties of integers, divisibility and unique factorization. Polynomial rings over a field. Congruence. Introduction to abstract rings, homomorphisms, and ideals. Roots and irreducibility of polynomials. Introduction to groups.)
2. Calculus II
3. Calculus I
4. Calculus for Business (Large lecture, ≃ 150 students.)
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University of Illinois at Chicago as Instructor:
1. Linear Algebra for Business
2. Calculus I
3. Calculus II
4. Math Enrichment Program
5. Summer Enrichment Mathematics Workshop
6. Emerging Scholar's Program (a Treisman-style workshop for Calculus)
University of Illinois at Chicago as Teaching Assistant:
1. Pre-calculus
2. Calculus I
3. Calculus II
4. Calculus III
5. Mathematical Reasoning
6. College Algebra​
7. Intermediate Algebra​
8. Graph Theory (Graduate course)​
9. Linear Algebra for Business
10. Introduction to Statistics
11. Introduction to Statistics for the Life Sciences
12. Advanced Linear Algebra (Graduate course)
13. Differential Equations
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Rochester Institute of Technology as Teaching Assistant:
1. Calculus I
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Sharif University of Technology of Iran as Teaching Assistant:
1. Abstract Algebra