# Teaching

Below you can find a list of courses I am currently teaching as well as courses I have taught in the past. More details can be found on the webpages for the individual courses. Courses marked with a

*****are new courses I have developed.#### Upcoming Courses (Spring 2025)

#### Past Courses

MATH 2318

MATH 6397

MATH 6366

MATH 6397

MATH 2318

MATH 6366

MATH 3336

MATH 6366

MATH 3336

MATH 3336

MATH 6397

MATH 6366

MATH 2331

MATH 6366

MATH 2331

MATH 6366

MATH 2331

MATH 2331

**Linear Algebra**( Course Webpage; Spring 2024)MATH 6397

**Computational and Mathematical Methods in Data Science***( Course Webpage; Spring 2024)MATH 6366

**Optimization Theory**( Course Webpage; Fall 2023 )MATH 6397

**Bayesian Inverse Problems and UQ***( Course Webpage; Spring 2023 )MATH 2318

**Linear Algebra**( Course Webpage; Spring 2023 )MATH 6366

**Optimization Theory**( Course Webpage; Fall 2022 )MATH 3336

**Discrete Mathematics**( Course Webpage; Spring 2022 )MATH 6366

**Optimization Theory**( Course Webpage; Fall 2021 )MATH 3336

**Discrete Mathematics**( Course Webpage; Fall 2021 )MATH 3336

**Discrete Mathematics**( Course Webpage; Spring 2021 )MATH 6397

**Applied Inverse Problems***( Course Webpage; Fall 2020 )MATH 6366

**Optimization Theory**( Course Webpage; Fall 2020 )MATH 2331

**Linear Algebra**( Course Webpage; Spring 2020 )MATH 6366

**Optimization Theory**( Course Webpage; Fall 2019 )MATH 2331

**Linear Algebra**( Course Webpage; Spring 2019 )MATH 6366

**Optimization Theory**( Course Webpage; Fall 2018 )MATH 2331

**Linear Algebra**( Course Webpage; Spring 2018 )MATH 2331

**Linear Algebra**( Course Webpage; Fall 2017 )#### References

Here's a list of books and online resources related to courses I teach and research I do.

Inverse Problems

*An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems*by L. Tenorio. SIAM 2017*.**An Introduction to the Mathematical Theory of Inverse Problems*by A. Kirsch, Springer, 1996.*Computational Inverse Problems*by C. Vogel, SIAM Press, 2002.*Computational Uncertainty Quantification for Inverse Problems*by J. Bardsley. SIAM Press 2018.*Discrete Inverse Problems: Insight and Algorithms*by P.C. Hansen, SIAM Press, 2010.*Inverse Problem Theory and Methods for Model Parameter Estimation*by Albert Tarantola, SIAM Press, 2004.*Rank-Deficient and Discrete Ill-Posed Problems*by P.C. Hansen, SIAM Press, 1998.*Parameter Estimation and Inverse Problems*by R. C. Aster, B. Borchers and C. H. Thurber, Elsevier, 2019.*Statistical and Computational Inverse Problems by*J. Kaipio and E. Somersalo, Springer, 2005.

Optimization

*Convexity and Optimization in R^n*by Leonard D. Berkovitz. John Wiley and Sons 2002.*Convex Optimization*by S. Boyd and L. Vandenberghe. Cambridge University Press 2004.*Introduction to Nonlinear Optimization*by A. Beck. SIAM 2014.*Lectures on Convex Optimization*by Yurii Nesterov. Springer 2018.*Numerical Optimization*by J. Nocedal and S. J. Wright. Springer 2006.*Optimization with PDE Constraints*by M. Hinze, R. Pinnau, M. Ulbrich, and S. Ulbrich. Springer 2009*Perspectives in Flow Control and Optimization*by M. D. Gunzburger. SIAM 2003.

Uncertainty Quantification

*An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems*by L. Tenorio. SIAM 2017*.**Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering*by Christian Soize. Springer 2017.*Introduction to Uncertainty Quantification*by T. J. Sullivan. Springer 2015.

Applied & Computational Mathematics

*Computational Methods in Geophysical Electromagnetics*by Eldad Haber. SIAM 2015.*Foundations of Computational Imaging: A Model-Based Approach*by Charles A. Bouman. SIAM 2022.