# Courses - Fall 2021

MATH 1011 Academic Support for MATH 1110

Reviews material presented in MATH 1110 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 1110 lectures.

Academic Career: UG Instructor: Mark Jauquet (maj29)
MATH 1012 Academic Support for MATH 1120

Reviews material presented in MATH 1120 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 1120 lectures or discussions.

Academic Career: UG Instructor: Brendan Caseria (bjc297)
MATH 1021 Academic Support for MATH 2210

Reviews material presented in MATH 2210 lectures, provides problem-solving techniques and tips as well as prelim review. Provides further instruction for students who need reinforcement. Not a substitute for attending MATH 2210 lectures or discussions.

Academic Career: UG Instructor: Brendan Caseria (bjc297)
MATH 1101 Calculus Preparation

Introduces topics in calculus: limits, rates of change, definition of and techniques for finding derivatives, relative and absolute extrema, and applications. The calculus content of the course is similar to 1/3 of the content covered in MATH 1106 and MATH 1110. In addition, the course includes a variety of topics of algebra, with emphasis on the development of linear, power, exponential, logarithmic, and trigonometric functions. Because of the strong emphasis on graphing, students will have a better understanding of asymptotic behavior of these functions.

Academic Career: UG Instructor: Mark Jauquet (maj29)
MATH 1105 Finite Mathematics for the Life and Social Sciences

Introduction to linear algebra, probability, and Markov chains that develops the parts of the theory most relevant for applications. Specific topics include equations of lines, the method of least squares, solutions of linear systems, matrices; basic concepts of probability, permutations, combinations, binomial distribution, mean and variance, and the normal approximation to the binomial distribution. Examples from biology and the social sciences are used.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Rhiannon Griffiths (rg636)
MATH 1110 Calculus I

Topics include functions and graphs, limits and continuity, differentiation and integration of algebraic, trigonometric, inverse trig, logarithmic, and exponential functions; applications of differentiation, including graphing, max-min problems, tangent line approximation, implicit differentiation, and applications to the sciences; the mean value theorem; and antiderivatives, definite and indefinite integrals, the fundamental theorem of calculus, substitution in integration, the area under a curve. Graphing calculators are used, and their pitfalls are discussed, as applicable to the above topics.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Prairie Wentworth-Nice (pew45)
MATH 1120 Calculus II

Focuses on integration: applications, including volumes and arc length; techniques of integration, approximate integration with error estimates, improper integrals, differential equations (separation of variables, initial conditions, systems, some applications). Also covers infinite sequences and series: definition and tests for convergence, power series, Taylor series with remainder, and parametric equations.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Feng Liang (fl363)
MATH 1300 Mathematical Explorations

For students who wish to experience how mathematical ideas naturally evolve. The course emphasizes ideas and imagination rather than techniques and calculations. Homework involves students in actively investigating mathematical ideas. Topics vary depending on the instructor. Some assessment through writing assignments.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Inna Zakharevich (iiz5)
MATH 1710 Statistical Theory and Application in the Real World

Introductory statistics course discussing techniques for analyzing data occurring in the real world and the mathematical and philosophical justification for these techniques. Topics include population and sample distributions, central limit theorem, statistical theories of point estimation, confidence intervals, testing hypotheses, the linear model, and the least squares estimator. The course concludes with a discussion of tests and estimates for regression and analysis of variance (if time permits). The computer is used to demonstrate some aspects of the theory, such as sampling distributions and the Central Limit Theorem. In the lab portion of the course, students learn and use computer-based methods for implementing the statistical methodology presented in the lectures.

Distribution: (MQR-AS, SDS-AS)
Academic Career: UG Instructor: Andrew Ahn (aa993)
MATH 1910 Calculus for Engineers

Essentially a second course in calculus. Topics include techniques of integration, finding areas and volumes by integration, exponential growth, partial fractions, infinite sequences and series, tests of convergence, and power series.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Clifford Pollock (crp10)
MATH 1920 Multivariable Calculus for Engineers

Introduction to multivariable calculus. Topics include partial derivatives, double and triple integrals, line and surface integrals, vector fields, Green's theorem, Stokes' theorem, and the divergence theorem.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Jason Manning (jm882)
MATH 2210 Linear Algebra

Topics include vector algebra, linear transformations, matrices, determinants, orthogonality, eigenvalues, and eigenvectors. Applications are made to linear differential or difference equations. The lectures introduce students to formal proofs. Students are required to produce some proofs in their homework and on exams.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Alex Townsend (ajt253)
MATH 2220 Multivariable Calculus

Differential and integral calculus of functions in several variables, line and surface integrals as well as the theorems of Green, Stokes, and Gauss.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Inna Zakharevich (iiz5)
MATH 2230 Theoretical Linear Algebra and Calculus

Topics include vectors, matrices, and linear transformations; differential calculus of functions of several variables; inverse and implicit function theorems; quadratic forms, extrema, and manifolds; multiple and iterated integrals.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Ravi Ramakrishna (rkr5)
MATH 2310 Linear Algebra with Applications

Introduction to linear algebra for students who wish to focus on the practical applications of the subject. A wide range of applications are discussed and computer software may be used. The main topics are systems of linear equations, matrices, determinants, vector spaces, orthogonality, and eigenvalues. Typical applications are population models, input/output models, least squares, and difference equations.

Distribution: (MQR-AS, SMR-AS)
MATH 2810 Deductive Logic

A mathematical study of the formal languages of standard first-order propositional and predicate logic, including their syntax, semantics, and deductive systems. The basic apparatus of model theory will be presented. Various formal results will be established, most importantly soundness and completeness.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Alexander Kocurek (awk78)
MATH 2930 Differential Equations for Engineers

Introduction to ordinary and partial differential equations. Topics include: first-order equations (separable, linear, homogeneous, exact); mathematical modeling (e.g., population growth, terminal velocity); qualitative methods (slope fields, phase plots, equilibria, and stability); numerical methods; second-order equations (method of undetermined coefficients, application to oscillations and resonance, boundary-value problems and eigenvalues); and Fourier series. A substantial part of this course involves partial differential equations, such as the heat equation, the wave equation, and Laplace's equation. (This part must be present in any outside course being considered for transfer credit to Cornell as a substitute for MATH 2930.)

Distribution: (MQR-AS, SMR-AS)
MATH 2940 Linear Algebra for Engineers

Linear algebra and its applications. Topics include matrices, determinants, vector spaces, eigenvalues and eigenvectors, orthogonality and inner product spaces; applications include brief introductions to difference equations, Markov chains, and systems of linear ordinary differential equations. May include computer use in solving problems.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Ed Swartz (ebs22)
MATH 3040 Prove It!

In mathematics, the methodology of proof provides a central tool for confirming the validity of mathematical assertions, functioning much as the experimental method does in the physical sciences. In this course, students learn various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and in set theory and combinatorics, and then moving to applications and illustrations of these via topics in one or more of the three main pillars of mathematics: algebra, analysis, and geometry. Since cogent communication of mathematical ideas is important in the presentation of proofs, the course emphasizes clear, concise exposition.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: J.D. Quigley (jdq27)
MATH 3110 Introduction to Analysis

Provides a transition from calculus to real analysis. Topics include rigorous treatment of fundamental concepts in calculus: including limits and convergence of sequences and series, compact sets; continuity, uniform continuity and differentiability of functions. Emphasis is placed upon understanding and constructing mathematical proofs.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Birgit Speh (bes12)
MATH 3210 Manifolds and Differential Forms

A manifold is a type of subset of Euclidean space that has a well-defined tangent space at every point. Such a set is amenable to the methods of multivariable calculus. After a review of some relevant calculus, this course investigates manifolds and the structures that they are endowed with, such as tangent vectors, boundaries, orientations, and differential forms. The notion of a differential form encompasses such ideas as area forms and volume forms, the work exerted by a force, the flow of a fluid, and the curvature of a surface, space, or hyperspace. The course re-examines the integral theorems of vector calculus (Green, Gauss, and Stokes) in the light of differential forms and applies them to problems in partial differential equations, topology, fluid mechanics, and electromagnetism.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Liam Mazurowski (lmm334)
MATH 3230 Introduction to Differential Equations

A brief one-semester introduction to the theory and techniques of both ordinary and partial differential equations. Topics for ordinary differential equations may include initial-value and two-point boundary value problems, the basic existence and uniqueness theorems, continuous dependence on data, stability of fix-points, numerical methods, special functions. Topics for partial differential equations may include the Poisson, heat and wave equations, boundary and initial-boundary value problems, maximum principles, continuous dependence on data, separation of variables, Fourier series, Green's functions, numerical methods, transform methods.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Jonas Juul (jsj85)
MATH 3320 Introduction to Number Theory

An introductory course on number theory, the branch of algebra that studies the deeper properties of integers and their generalizations. Usually includes most of the following topics: the Euclidean algorithm, continued fractions, Pythagorean triples, Diophantine equations such as Pell's equation, congruences, quadratic reciprocity, binary quadratic forms, Gaussian integers, and factorization in quadratic number fields. May include a brief introduction to Fermat's Last Theorem.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Michael Stillman (mes15)
MATH 3610 Mathematical Modeling

Introduction to the theory and practice of mathematical modeling. This course compares and contrasts different types of mathematical models (discrete vs. continuous, deterministic vs. stochastic), focusing on advantages, disadvantages and limits of applicability for each approach. Case-study format covers a variety of application areas including economics, physics, sociology, traffic engineering, urban planning, robotics, and resource management. Students learn how to implement mathematical models on the computer and how to interpret/describe the results of their computational experiments.

Distribution: (MQR-AS, SMR-AS)
MATH 4130 Honors Introduction to Analysis I

Introduction to the rigorous theory underlying calculus, covering the real number system and functions of one variable. Based entirely on proofs. The student is expected to know how to read and, to some extent, construct proofs before taking this course. Topics typically include construction of the real number system, properties of the real number system, continuous functions, differential and integral calculus of functions of one variable, sequences and series of functions.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Terence Harris (tlh236)
MATH 4200 Differential Equations and Dynamical Systems

Covers ordinary differential equations in one and higher dimensions: qualitative, analytic, and numerical methods. Emphasis is on differential equations as models and the implications of the theory for the behavior of the system being modeled and includes an introduction to bifurcations.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: William Clark (wac76)
MATH 4220 Applied Complex Analysis

Covers complex variables, Fourier transforms, Laplace transforms and applications to partial differential equations. Additional topics may include an introduction to generalized functions.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Evan Randles (edr62)
MATH 4250 Numerical Analysis and Differential Equations

Introduction to the fundamentals of numerical analysis: error analysis, approximation, interpolation, numerical integration. In the second half of the course, the above are used to build approximate solvers for ordinary and partial differential equations. Strong emphasis is placed on understanding the advantages, disadvantages, and limits of applicability for all the covered techniques. Computer programming is required to test the theoretical concepts throughout the course.

Distribution: (MQR-AS, SMR-AS)
MATH 4310 Linear Algebra

Introduction to linear algebra, including the study of vector spaces, linear transformations, matrices, and systems of linear equations. Additional topics are quadratic forms and inner product spaces, canonical forms for various classes of matrices and linear transformations.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Nicolas Templier (npt27)
MATH 4330 Honors Linear Algebra

Honors version of a course in advanced linear algebra, which treats the subject from an abstract and axiomatic viewpoint. Topics include vector spaces, linear transformations, polynomials, determinants, tensor and wedge products, canonical forms, inner product spaces, and bilinear forms. Emphasis is on understanding the theory of linear algebra; homework and exams include at least as many proofs as computational problems.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Shankar Sen (ss70)
MATH 4370 Computational Algebra

Introduction to algebraic geometry and computational algebra. In this course, students learn how to compute a Gröbner basis for polynomials in many variables. Covers the following applications: solving systems of polynomial equations in many variables, solving diophantine equations in many variables, 3-colorable graphs, and integer programming. Such applications arise, for example, in computer science, engineering, economics, and physics.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Irena Peeva (ivp1)
MATH 4410 Introduction to Combinatorics I

Combinatorics is the study of discrete structures that arise in a variety of areas, particularly in other areas of mathematics, computer science, and many areas of application. Central concerns are often to count objects having a particular property (e.g., trees) or to prove that certain structures exist (e.g., matchings of all vertices in a graph). The first semester of this sequence covers basic questions in graph theory, including extremal graph theory (how large must a graph be before one is guaranteed to have a certain subgraph) and Ramsey theory (which shows that large objects are forced to have structure). Variations on matching theory are discussed, including theorems of Dilworth, Hall, König, and Birkhoff, and an introduction to network flow theory. Methods of enumeration (inclusion/exclusion, Möbius inversion, and generating functions) are introduced and applied to the problems of counting permutations, partitions, and triangulations.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Karola Meszaros (km626)
MATH 4520 Classical Geometries and Modern Applications

An introduction to projective, hyperbolic, and spherical geometry and their modern applications.  The course will be divided into short modules with an emphasis on participation, discovery, and student projects and presentations. In addition to proving theorems, students will have the opportunity to make, build, 3D print, or program something related to the course material as a project component. We will cover classical theorems and techniques (e.g. stereographic projection and conics), and also see how classical geometry is used in and relates to other areas of mathematics (e.g. topology, via Euler characteristic) and in applications such as computer vision, networks, or architectural drawing.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Kathryn Mann (kpm85)
MATH 4530 Introduction to Topology

Topology may be described briefly as qualitative geometry. This course begins with basic point-set topology, including connectedness, compactness, and metric spaces. Later topics may include the classification of surfaces (such as the Klein bottle and Möbius band), elementary knot theory, or the fundamental group and covering spaces.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Martin Kassabov (mdk35)
MATH 4710 Basic Probability

Introduction to probability theory, which prepares the student to take MATH 4720. The course begins with basics: combinatorial probability, mean and variance, independence, conditional probability, and Bayes formula. Density and distribution functions and their properties are introduced. The law of large numbers and the central limit theorem are stated and their implications for statistics are discussed.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Laurent Saloff-Coste (lps2)
MATH 4860 Applied Logic

Topics chosen from the following: Propositional Logic, First-Order Logic, and Higher Order logic, both classical and intuitionistic versions, including completeness, incompleteness and compactness results. Natural deduction and tableaux style logics and connection to  the lambda calculus and programming languages and logics, and program verification.

Distribution: (MQR-AS, SMR-AS)
Academic Career: UG Instructor: Bob Constable (rlc7)
MATH 4900 Supervised Research

An independent research course by arrangement with an individual professor.  The goal is for the student to perform an independent investigation into a specific mathematical question.  The student and professor will set expectations and grading policies at the beginning of the term.

Academic Career: UG Instructor: Marcelo Aguiar (ma18)

An independent reading course by arrangement with an individual professor. The goal is for the student to master a body of mathematics outside the normal curriculum. The student and professor will set expectations and grading policies at the beginning of the term.

Academic Career: UG Instructor: Marcelo Aguiar (ma18)
MATH 4980 Special Study for Mathematics Teaching

Examines principles underlying the content of the secondary school mathematics curriculum, including connections with the history of mathematics, technology, and mathematics education research. One credit is awarded for attending two Saturday workshops (see math.cornell.edu/math-5080) and writing a paper. Other credit options are available for students completing additional work, such as tutoring at a local middle school or completing a research paper or project.

Academic Career: UG Instructor: Mary Ann Huntley (mh688)
MATH 5080 Special Study for Teachers

Examines principles underlying the content of the secondary school mathematics curriculum, including connections with the history of mathematics, technology, and mathematics education research. One credit is awarded for attending two Saturday workshops (see math.cornell.edu/math-5080) and writing a paper.

Academic Career: GR Instructor: Mary Ann Huntley (mh688)
MATH 5250 Numerical Analysis and Differential Equations

Introduction to the fundamentals of numerical analysis: error analysis, approximation, interpolation, numerical integration. In the second half of the course, the above are used to build approximate solvers for ordinary and partial differential equations. Strong emphasis is placed on understanding the advantages, disadvantages, and limits of applicability for all the covered techniques. Computer programming is required to test the theoretical concepts throughout the course.

MATH 5410 Introduction to Combinatorics I

Combinatorics is the study of discrete structures that arise in a variety of areas, particularly in other areas of mathematics, computer science, and many areas of application. Central concerns are often to count objects having a particular property (e.g., trees) or to prove that certain structures exist (e.g., matchings of all vertices in a graph). The first semester of this sequence covers basic questions in graph theory, including extremal graph theory (how large must a graph be before one is guaranteed to have a certain subgraph) and Ramsey theory (which shows that large objects are forced to have structure). Variations on matching theory are discussed, including theorems of Dilworth, Hall, König, and Birkhoff, and an introduction to network flow theory. Methods of enumeration (inclusion/exclusion, Möbius inversion, and generating functions) are introduced and applied to the problems of counting permutations, partitions, and triangulations.

Academic Career: GR Instructor: Karola Meszaros (km626)
MATH 6110 Real Analysis

MATH 6110-MATH 6120 are the core analysis courses in the mathematics graduate program. MATH 6110 covers measure and integration and functional analysis.

Academic Career: GR Instructor: Camil Muscalu (fm69)
MATH 6210 Measure Theory and Lebesgue Integration

Covers measure theory, integration, and Lp spaces.

Academic Career: GR Instructor: Benjamin Dozier (bed47)
MATH 6310 Algebra

MATH 6310-MATH 6320 are the core algebra courses in the mathematics graduate program. MATH 6310 covers group theory, especially finite groups; rings and modules; ideal theory in commutative rings; arithmetic and factorization in principal ideal domains and unique factorization domains; introduction to field theory; tensor products and multilinear algebra. (Optional topic: introduction to affine algebraic geometry.)

Academic Career: GR Instructor: Marcelo Aguiar (ma18)
MATH 6340 Commutative Algebra with Applications in Algebraic Geometry

Covers Dedekind domains, primary decomposition, Hilbert basis theorem, and local rings.

Academic Career: GR Instructor: Irena Peeva (ivp1)
MATH 6520 Differentiable Manifolds

MATH 6510-MATH 6520 are the core topology courses in the mathematics graduate program. MATH 6520 is an introduction to geometry and topology from a differentiable viewpoint, suitable for beginning graduate students. The objects of study are manifolds and differentiable maps. The collection of all tangent vectors to a manifold forms the tangent bundle, and a section of the tangent bundle is a vector field. Alternatively, vector fields can be viewed as first-order differential operators. Students study flows of vector fields and prove the Frobenius integrability theorem. In the presence of a Riemannian metric, the notions of parallel transport, curvature, and geodesics are development. Students examine the tensor calculus and the exterior differential calculus and prove Stokes' theorem. If time permits, de Rham cohomology, Morse theory, or other optional topics are introduced.

Academic Career: GR Instructor: James West (jew13)
MATH 6640 Hyperbolic Geometry

An introduction to the topology and geometry of hyperbolic manifolds. The class will begin with the geometry of hyperbolic n-space, including the upper half-space, Poincaré disc, and Lorentzian models. Particular attention will be paid to the cases n=2 and n=3. Hyperbolic structures on surfaces will be parametrized using Teichmüller space, and discrete groups of isometries of hyperbolic space will be discussed. Other possible topics include the topology of hyperbolic manifolds and orbifolds; Mostow rigidity; hyperbolic Dehn filling; deformation theory of Kleinian groups; complex and quaternionic hyperbolic geometry; and convex projective structures on manifolds.

Academic Career: GR Instructor: Jason Manning (jm882)
MATH 6710 Probability Theory I

A mathematically rigorous course in probability theory which uses measure theory but begins with the basic definitions of independence and expected value in that context. Law of large numbers, Poisson and central limit theorems, and random walks.

Academic Career: GR Instructor: Lionel Levine (ll432)
MATH 6740 Mathematical Statistics II

Focuses on the foundations of statistical inference, with an emphasis on asymptotic methods and the minimax optimality criterion. In the first part, the solution of the classical problem of justifying Fisher's information bound in regular statistical models will be presented. This solution will be obtained applying the concepts of contiguity, local asymptotic normality and asymptotic minimaxity. The second part will be devoted to nonparametric estimation, taking a Gaussian regression model as a paradigmatic example. Key topics are kernel estimation and local polynomial approximation, optimal rates of convergence at a point and in global norms, and adaptive estimation. Optional topics may include irregular statistical models, estimation of functionals and nonparametric hypothesis testing.

Academic Career: GR Instructor: Michael Nussbaum (mn66)
MATH 6840 Recursion Theory

Covers theory of effectively computable functions; classification of recursively enumerable sets; degrees of recursive unsolvability; applications to logic; hierarchies; recursive functions of ordinals and higher type objects; generalized recursion theory.

Academic Career: GR Instructor: Anil Nerode (an17)
MATH 7110 Topics in Analysis

Selection of advanced topics from analysis. Course content varies.

Academic Career: GR Instructor: Camil Muscalu (fm69)
MATH 7130 Functional Analysis

Covers topological vector spaces, Banach and Hilbert spaces, and Banach algebras. Additional topics selected by instructor.

Academic Career: GR Instructor: Terence Harris (tlh236)
MATH 7160 Topics in Partial Differential Equations

Selection of advanced topics from partial differential equations. Content varies.

Academic Career: GR Instructor: Timothy Healey (tjh10)
MATH 7290 Seminar on Scientific Computing and Numerics

Talks on various methods in scientific computing, the analysis of their convergence properties and computational efficiency, and their adaptation to specific applications.

Academic Career: GR Instructor: Anil Damle (asd239)
Alex Townsend (ajt253)
MATH 7370 Topics in Number Theory

Selection of advanced topics from number theory. Course content varies.

Academic Career: GR Instructor: Ravi Ramakrishna (rkr5)
MATH 7510 Berstein Seminar in Topology

A seminar on an advanced topic in topology or a related subject. Content varies. The format is usually that the participants take turns to present.

Academic Career: GR Instructor: Kathryn Mann (kpm85)
MATH 7550 Topology and Geometric Group Theory Seminar

A weekly seminar in which visiting or local speakers present results in topology, geometric group theory, or related subjects.

MATH 7610 Topics in Geometry

Selection of advanced topics from modern geometry. Content varies.

Academic Career: GR Instructor: Xin Zhou (xz636)
MATH 7670 Topics in Algebraic Geometry

Selection of topics from algebraic geometry. Content varies.

Academic Career: GR Instructor: Daniel Halpern-Leistner (dsh233)
MATH 7720 Topics in Stochastic Processes

Selection of advanced topics from stochastic processes. Content varies.

Academic Career: GR Instructor: Laurent Saloff-Coste (lps2)
MATH 7810 Seminar in Logic

A twice weekly seminar in logic. Typically, a topic is selected for each semester, and at least half of the meetings of the course are devoted to this topic with presentations primarily by students. Opportunities are also provided for students and others to present their own work and other topics of interest.

Academic Career: GR Instructor: Justin Moore (jtm237)
MATH 7900 Supervised Reading and Research

Supervised research for the doctoral dissertation.

Academic Career: GR Instructor: Karola Meszaros (km626)