Course Atlas
Graduate Math Courses
| MATH512 | Analysis II | Credits: 3 | ||
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| Content: Topics will include: Measure and integration theory on the real line as well as on a general measure space, Bounded linear functionals on L^p spaces. If time permits, Sobolev spaces and Fourier transforms will be introduced. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: Students are expected to have the background of Math 411-412 sequence or the equivalent. | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W302 | MW 8:30AM - 9:45AM | Shanshuang Yang |
| MATH516 | Numerical Analysis II | Credits: 3 | ||
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| Content: This course covers fundamental concepts of numerical analysis and scientific computing. Material includes numerical methods for curve fitting (interpolation, splines, least squares), differentiation, integration, and differential equations. It is assumed that students have a strong background in numerical linear algebra. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: Math 515, undergraduate course work in multivariable calculus and ordinary differential equations. An undergraduate course in numerical analysis would help, but is not absolutely essential. Prerequisites: This is a "hands on" course and students will be required to demonstrate their understanding of the concepts through programming assignments in MATLAB/Octave (help will be given for the novice programmer). | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W306 | MW 11:30AM - 12:45PM | Alessandro Veneziani |
| MATH522 | Algebra II | Credits: 3 | ||
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| Content: Continuation of 521. Topics: Modules, especially modules over a principal ideal domain, fields, Galois theory, representation of finite groups, Commutative algebra. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: Math 521. | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E406 | TuTh 2:30PM - 3:45PM | Raman Parimala |
| MATH528 | Algebraic Number Theory | Credits: 3 | ||
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| Content: TBA | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E406 | MW 11:30AM - 12:45PM | John Duncan |
| MATH532 | Graph Theory II | Credits: 3 | ||
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| Content: TBA | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E406 | MW 2:30PM - 3:45PM | Hao Huang |
| MATH546 | Intro. to Differential Geometry II | Credits: 3 | ||
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| Content: An introduction to Riemannian geometry and global analysis. Topics to be covered: Manifolds, Riemannian metrics, Connections, Curvature; Geodesics, Convexity, Topics in Global Analysis. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E408 | TuTh 11:30AM - 12:45PM | Vladimir Oliker |
| MATH550 | Functional Analysis | Credits: 3 | ||
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| Content: An introduction to concepts and applications including: metric and normed spaces, Hilbert and Banach spaces, linear operators and functionals, compactness in metric and normed spaces, Fredholm's solvability theory, spectral theory, calculus in metric and normed spaces, selected applications. | ||||
| Texts: A. Bressan, Lecture Notes on Functional Analysis. With Application to Partial Differential Equations, Graduate Studies in Mathematics 143, American Mathematical Society, Providence, RI, 2013. | ||||
| Assessments: TBA | ||||
| Prerequisites: Math 511, Math 512. | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E406 | TuTh 10:00AM - 11:15AM | Michele Benzi |
| MATH577R | Seminar in Combinatorics | Credits: 3 | ||
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| Content: The seminar in combinatorics is a research seminar for students and faculty. It runs weekly, and features speakers from outside Emory who come to talk about topics of interest to the Emory faculty. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W303 | M 4:00PM - 4:50PM | Dwight Duffus |
| MATH578R | Seminar in Algebra | Credits: 1-9 | ||
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| Content: Research topics in algebra of current interest to faculty and students. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W304 | Tu 4:00PM - 4:50PM | David Zureick-Brown |
| MATH579R | Seminar in Analysis | Credits: 3 | ||
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| Content: TBA | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W301 | F 2:00PM - 2:50PM | Lars Ruthotto |
| 2 | MSC W301 | Tu 4:00PM - 5:00PM | Vladimir Oliker | |
| MATH590 | Teaching Seminar | Credits: 3 | ||
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| Content: This seminar will concentrate on effective teaching techniques in mathematics. Topics included will include: General advice for new TA's. General advice for International TA's. Students will present several practice lectures over different levels of material. They will receive practice on quiz and test preparation. Syllabus information on courses most likely to be taught by new TA's will be supplied. General professional development information will also be included. | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W306 | F 11:00AM - 11:50AM | Bree Ettinger |
| MATH788 | Topics in Algebra | Credits: 3 | ||
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| Content: TBA | ||||
| Texts: TBA | ||||
| Assessments: TBA | ||||
| Prerequisites: TBA | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC E408 | TuTh 10:00AM - 11:15AM | David Zureick-Brown |
| MATH789R | Topics in Analysis: Numerical Methods for Deep Learning | Credits: 3 | ||
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| Content: This course provides students with the mathematical background needed to analyze and further develop numerical methods at the heart of deep learning. The course briefly reviews current trends in machine learning, classification, and in particular deep neural networks. Mathematical techniques covered in this class include numerical optimization, numerical differential equations, optimal control. | ||||
| Texts: Homework and additional course material will be made available using Canvas. | ||||
| Assessments: TBA | ||||
| Prerequisites: In order to succeed in this class, students need to have a solid background in multivariate calculus and linear algebra and some programming experience in MATLAB, Julia, or Python. In addition, students are also expected to have experience or skills in either numerical analysis (optimization, partial differential equations) or machine learning (e.g., CS534, CS584, or similar). | ||||
| Section | Location | Meeting Time | Instructor | Enrollment (max) | 1 | MSC W302 | WF 11:30AM - 12:45PM | Lars Ruthotto | 10 |