COLLEGE ALGEBRA-ANLYTC GEOMTRY

Prerequisites: score of 550 on the mathematics portion of the SAT completed within the last year, or the appropriate grade on the General Studies Mathematics Placement Examination. For students who wish to study calculus but do not know analytic geometry. Algebra review, graphs and functions, polynomial functions, rational functions, conic sections, systems of equations in two variables, exponential and logarithmic functions, trigonometric functions and trigonometric identities, applications of trigonometry, sequences, series, and limits.

This course may not be taken for credit after the successful completion of any course in the Calculus sequence.

• MW 11:40 a.m.-12:55 p.m.
• TR 6:10 p.m.-7:25 p.m.
• Instructor: Jiahe Shen
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• Instructor: Xiaorun Wu
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• 3 points

CALCULUS I

Prerequisites: (see Courses for First-Year Students). Functions, limits, derivatives, introduction to integrals, or an understanding of pre-calculus will be assumed. (SC)

• MW 4:10 p.m.-5:25 p.m.
• MW 6:10 p.m.-7:25 p.m.
• TR 10:10 a.m.-11:25 a.m.
• TR 1:10 p.m.-2:25 p.m.
• TR 4:10 p.m.-5:25 p.m.
• Instructor: Qiyao Yu
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• Instructor: Brian Harvie
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• Instructor: Roger W Van Peski
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• 3 points

CALCULUS II

Prerequisites: MATH UN1101 or the equivalent. Methods of integration, applications of the integral, Taylors theorem, infinite series. (SC)

• MW 10:10 a.m.-11:25 a.m.
• MW 4:10 p.m.-5:25 p.m.
• TR 10:10 a.m.-11:25 a.m.
• TR 11:40 a.m.-12:55 p.m.
• TR 1:10 p.m.-2:25 p.m.
• Instructor: Evan Sorensen
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• Instructor: Jingbo Wan
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• Instructor: Peter G Woit
  CULPA: 6 Info
• Instructor: Dawei Shen
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• Instructor: Andres Ibanez Nunez
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• 3 points

CALCULUS III

Prerequisites: MATH UN1101 or the equivalent Vectors in dimensions 2 and 3, complex numbers and the complex exponential function with applications to differential equations, Cramers rule, vector-valued functions of one variable, scalar-valued functions of several variables, partial derivatives, gradients, surfaces, optimization, the method of Lagrange multipliers. (SC)

• MW 2:40 p.m.-3:55 p.m.
• TR 1:10 p.m.-2:25 p.m.
• TR 4:10 p.m.-5:25 p.m.
• TR 6:10 p.m.-7:25 p.m.
• Instructor: Deeparaj Bhat
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• 3 points

CALCULUS IV

Prerequisites: MATH UN1102 and MATH UN1201 or the equivalent Multiple integrals, Taylor's formula in several variables, line and surface integrals, calculus of vector fields, Fourier series. (SC)

• MW 1:10 p.m.-2:25 p.m.
• TR 1:10 p.m.-2:25 p.m.
• Instructor: Ovidiu Savin
  CULPA: 22 Wikipedia Info
• Instructor: Sangiovanni Vincentelli Marco
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• 3 points

ACCELERATED MULTIVARIABLE CALC

Prerequisites: (MATH UN1101 and MATH UN1102) Vectors in dimensions 2 and 3, vector-valued functions of one variable, scalar-valued functions of several variables, partial derivatives, gradients, optimization, Lagrange multipliers, double and triple integrals, line and surface integrals, vector calculus. This course is an accelerated version of MATH UN1201 - MATH UN1202. Students taking this course may not receive credit for MATH UN1201 and MATH UN1202.

• TR 11:40 a.m.-12:55 p.m.
• Instructor: Marco Castronovo
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• 4 points

HONORS MATHEMATICS B

Prerequisites: (see Courses for First-Year Students). The second term of this course may not be taken without the first. Multivariable calculus and linear algebra from a rigorous point of view. Recommended for mathematics majors. Fulfills the linear algebra requirement for the major. (SC)

• TR 1:10 p.m.-2:25 p.m.
• Instructor: Jeanne Boursier
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• 4 points

INTRO TO HIGHER MATHEMATICS

Introduction to understanding and writing mathematical proofs. Emphasis on precise thinking and the presentation of mathematical results, both in oral and in written form. Intended for students who are considering majoring in mathematics but wish additional training. CC/GS: Partial Fulfillment of Science Requirement. BC: Fulfillment of General Education Requirement: Quantitative and Deductive Reasoning (QUA).

• TR 1:10 p.m.-2:25 p.m.
• Instructor: Giulia Sacca
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• 3 points

INTRODUCTION TO MATHEMATICS PROOFS

INTRO TO MATHEMATICAL PRO

This is a seminar course that covers the basics of mathematical proofs and in particular the epsilon-delta argument in single variable calculus.

Students who have little experience with mathematical proofs are strongly encouraged to take this course concurrently with Honors Math, Into to Modern Algebra, or Intro to Modern Analysis.

• F 1 p.m.-3 p.m.
• Instructor: Julien Dubedat
  CULPA: 4 Info
• 0 points

LINEAR ALGEBRA

Matrices, vector spaces, linear transformations, eigenvalues and eigenvectors, canonical forms, applications. (SC)

• TR 10:10 a.m.-11:25 a.m.
• TR 11:40 a.m.-12:55 p.m.
• TR 4:10 p.m.-5:25 p.m.
• Instructor: Qiao He
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• 3 points

Linear Algebra and Probability

Linear algebra with a focus on probability and statistics. The course covers the standard linear algebra topics: systems of linear equations, matrices, determinants, vector spaces, bases, dimension, eigenvalues and eigenvectors, the Spectral Theorem and singular value decompositions. It also teaches applications of linear algebra to probability, statistics and dynamical systems giving a background sufficient for higher level courses in probability and statistics. The topics covered in the probability theory part include conditional probability, discrete and continuous random variables, probability distributions and the limit theorems, as well as Markov chains, curve fitting, regression, and pattern analysis. The course contains applications to life sciences, chemistry, and environmental life sciences. No a prior i background in the life sciences is assumed.

This course is best suited for students who wish to focus on applications and practical approaches to problem solving. It is recommended to students majoring in engineering, technology, life sciences, social sciences, and economics. Math majors, joint majors, and math concentrators must take MATH UN2010 Linear Algebra, which focuses on linear algebra concepts and foundations that are needed for upper-level math courses. MATH UN2015 (Linear Algebra and Probability) does NOT replace MATH UN2010 (Linear Algebra) as prerequisite requirements of math courses. Students may not receive full credit for both courses MATH UN2010 and MATH UN2015.

• MW 2:40 p.m.-3:55 p.m.
• Instructor: George Dragomir
  CULPA: 5 Info
• 3 points

ORDINARY DIFFERENTIAL EQUATIONS

Prerequisites: MATH UN1102 and MATH UN1201 or the equivalent. Special differential equations of order one. Linear differential equations with constant and variable coefficients. Systems of such equations. Transform and series solution techniques. Emphasis on applications.

• MW 10:10 a.m.-11:25 a.m.
• TR 11:40 a.m.-12:55 p.m.
• Instructor: Dawei Shen
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• Instructor: Panagiota Daskalopoulos
  CULPA: 19 Wikipedia Info
• 3 points

ANALYSIS AND OPTIMIZATION

Prerequisites: MATH UN1102 and MATH UN1201 or the equivalent and MATH UN2010. Mathematical methods for economics. Quadratic forms, Hessian, implicit functions. Convex sets, convex functions. Optimization, constrained optimization, Kuhn-Tucker conditions. Elements of the calculus of variations and optimal control. (SC)

• TR 10:10 a.m.-11:25 a.m.
• Instructor: Xi S Shen
  h-index: 4 Info
• 3 points

NUMBER THEORY AND CRYPTOGRAPHY

Prerequisites: one year of calculus. Prerequisite: One year of Calculus. Congruences. Primitive roots. Quadratic residues. Contemporary applications.

• MW 10:10 a.m.-11:25 a.m.
• Instructor: Siddhi Krishna
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• 3 points

PARTIAL DIFFERENTIAL EQUATIONS

Prerequisites: (MATH UN2010 and MATH UN2030) or the equivalent introduction to partial differential equations. First-order equations. Linear second-order equations; separation of variables, solution by series expansions. Boundary value problems.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Simon Brendle
  CULPA: 1 Wikipedia Info
• 3 points

DISCRETE TIME MODELS IN FINANC

Prerequisites: (MATH UN1102 and MATH UN1201) or (MATH UN1101 and MATH UN1102 and MATH UN1201) and MATH UN2010 Recommended: MATH UN3027 (or MATH UN2030 and SIEO W3600). Elementary discrete time methods for pricing financial instruments, such as options. Notions of arbitrage, risk-neutral valuation, hedging, term-structure of interest rates.

• MW 6:10 p.m.-7:25 p.m.
• Instructor: Mikhail Smirnov
  CULPA: 16 Info
• 3 points

SUPERVISED READINGS II

Prerequisites: The written permission of the faculty member who agrees to act as sponsor (sponsorship limited to full-time instructors on the staff list), as well as the permission of the Director of Undergraduate Studies. The written permission must be deposited with the Director of Undergraduate Studies before registration is completed. Guided reading and study in mathematics. A student who wishes to undertake individual study under this program must present a specific project to a member of the staff and secure his or her willingness to act as sponsor. Written reports and periodic conferences with the instructor. 

Supervising Readings do NOT count towards major requirements, with the exception of an advanced written approval by the DUS.

• Instructor: Julien Dubedat
  CULPA: 4 Info
• 1-3 points

ANALYTIC NUMBER THEORY

Prerequisites: MATH UN3007 A one semeser course covering the theory of modular forms, zeta functions, L -functions, and the Riemann hypothesis. Particular topics covered include the Riemann zeta function, the prime number theorem, Dirichlet characters, Dirichlet L-functions, Siegel zeros, prime number theorem for arithmetic progressions, SL (2, Z) and subgroups, quotients of the upper half-plane and cusps, modular forms, Fourier expansions of modular forms, Hecke operators, L-functions of modular forms.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Amadou Bah
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• 3 points

INTRO MODERN ALGEBRA I

Prerequisites: MATH UN1102 and MATH UN1202 and MATH UN2010 or the equivalent. The second term of this course may not be taken without the first. Groups, homomorphisms, normal subgroups, the isomorphism theorems, symmetric groups, group actions, the Sylow theorems, finitely generated abelian groups.

• MW 2:40 p.m.-3:55 p.m.
• Instructor: Michael Thaddeus
  CULPA: 24 Wikipedia Info
• 3 points

INTRO TO MOD ALGEBRA II

Prerequisites: MATH UN1102 and MATH UN1202 and MATH UN2010 or the equivalent. The second term of this course may not be taken without the first. Rings, homomorphisms, ideals, integral and Euclidean domains, the division algorithm, principal ideal and unique factorization domains, fields, algebraic and transcendental extensions, splitting fields, finite fields, Galois theory.

• MW 2:40 p.m.-3:55 p.m.
• Instructor: Robert D Friedman
  CULPA: 44 Info
• 3 points

ALGEBRAIC NUMBER THEORY

Prerequisites: MATH GU4041 and MATH GU4042 or the equivalent Algebraic number fields, unique factorization of ideals in the ring of algebraic integers in the field into prime ideals. Dirichlet unit theorem, finiteness of the class number, ramification. If time permits, p-adic numbers and Dedekind zeta function.

• TR 4:10 p.m.-5:25 p.m.
• Instructor: Yujie Xu
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• 3 points

ALGEBRAIC CURVES

Prerequisites: (MATH GU4041 and MATH GU4042) and MATH UN3007 Plane curves, affine and projective varieties, singularities, normalization, Riemann surfaces, divisors, linear systems, Riemann-Roch theorem.

• MW 11:40 a.m.-12:55 p.m.
• Instructor: Yoonjoo Kim
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• 3 points

INTRO TO ALGEBRAIC TOPOLOGY

Prerequisites: MATH UN2010 and MATH GU4041 and MATH GU4051 The study of topological spaces from algebraic properties, including the essentials of homology and the fundamental group. The Brouwer fixed point theorem. The homology of surfaces. Covering spaces.

• TR 11:40 a.m.-12:55 p.m.
• Instructor: Soren Galatius
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• 3 points

INTRO MODERN ANALYSIS I

Prerequisites: MATH UN1202 or the equivalent, and MATH UN2010. The second term of this course may not be taken without the first. Real numbers, metric spaces, elements of general topology, sequences and series, continuity, differentiation, integration, uniform convergence, Ascoli-Arzela theorem, Stone-Weierstrass theorem.

• MW 1:10 p.m.-2:25 p.m.
• Instructor: Julien Dubedat
  CULPA: 4 Info
• 3 points

INTRO MODERN ANALYSIS II

The second term of this course may not be taken without the first. Power series, analytic functions, Implicit function theorem, Fubini theorem, change of variables formula, Lebesgue measure and integration, function spaces.

• TR 4:10 p.m.-5:25 p.m.
• Instructor: Francesco Lin
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• 3 points

INTRO-DIFFERENTIABLE MANIFOLDS

Prerequisites: (MATH GU4051 or MATH GU4061) and MATH UN2010 Concept of a differentiable manifold. Tangent spaces and vector fields. The inverse function theorem. Transversality and Sards theorem. Intersection theory. Orientations. Poincare-Hopf theorem. Differential forms and Stokes theorem.

• MW 10:10 a.m.-11:25 a.m.
• Instructor: Sven Hirsch
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• 3 points

ADVANCED PROBABILITY THEORY

This course will cover advance topics in probability, including: the theory of martingales in discrete and in continuous time; Brownian motion and its properties, stochastic integration, ordinary and partial stochastic differential equations; Applications to optimal filtering, stopping, control, and finance; Continuous-time Markov chains, systems of interacting particles, relative entropy dissipation, notions of information theory; Electrical networks, random walks on graphs and groups, percolation.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Ioannis Karatzas
  CULPA: 7 h-index: 58 Info
• 3 points

MATHEMATICS AND THE HUMANITIES

This course is being taught by two senior faculty members who are theorists and practitioners in disciplines as different as mathematics and literary criticism. The instructors believe that in today's world, the different ways in which theoretical mathematics and literary criticism mold the imaginations of students and scholars, should be brought together, so that the robust ethical imagination that is needed to combat the disintegration of our world can be produced. Except for the length of novels, the reading is no more than 100 pages a week.

Our general approach is to keep alive the disciplinary differences between literary/philosophical (humanities) reading and mathematical writing.  Some preliminary questions we have considered are: the survival skills of the logicist school over against the Foundational Crisis of the early 20th century; by way of Wittgenstein and others, we ask, Are mathematical objects real? Or are they linguistic conventions? We will consider the literary/philosophical use of mathematics, often by imaginative analogy; and the role of the digital imagination in the humanities: Can so-called creative work as well as mathematics be written by machines? Guest faculty from other departments will teach with us to help students and instructors understand various topics.  We will close with how a novel animates “science” in prose, stepping out of the silo of disciplinary mathematics to the arena where mathematics is considered a code-name for science: Christine Brooke-Rose’s novel
Subscript
.

• T 4:10 p.m.-6 p.m.
• 4 points

INTRO TO THE MATH OF FINANCE

Prerequisites: MATH UN1102 and MATH UN1201 , or their equivalents. Introduction to mathematical methods in pricing of options, futures and other derivative securities, risk management, portfolio management and investment strategies with an emphasis of both theoretical and practical aspects. Topics include: Arithmetic and Geometric Brownian ,motion processes, Black-Scholes partial differential equation, Black-Scholes option pricing formula, Ornstein-Uhlenbeck processes, volatility models, risk models, value-at-risk and conditional value-at-risk, portfolio construction and optimization methods.

• MW 7:40 p.m.-8:55 p.m.
• Instructor: Mikhail Smirnov
  CULPA: 16 Info
• 3 points

NUMERICAL METHODS IN FINANCE

Prerequisites: some familiarity with the basic principles of partial differential equations, probability and stochastic processes, and of mathematical finance as provided, e.g. in MATH W5010. Prerequisites: some familiarity with the basic principles of partial differential equations, probability and stochastic processes, and of mathematical finance as provided, e.g. in MATH W5010. Review of the basic numerical methods for partial differential equations, variational inequalities and free-boundary problems. Numerical methods for solving stochastic differential equations; random number generation, Monte Carlo techniques for evaluating path-integrals, numerical techniques for the valuation of American, path-dependent and barrier options.

• MW 7:40 p.m.-8:55 p.m.
• MW 5:25 p.m.-6:40 p.m.
• Instructor: Tat Sang Fung
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• Instructor: Luca Capriotti
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• 3 points

MATH FINANCE PRACTITIONERS SEM

Prerequisites: MATH W5010 or knowledge of J. Hulls book Options, futures. Prerequisites: Math GR5010 or knowledge of J. Hulls book Options, futures. Seminar consists of presentations and mini-courses by leading industry specialists in quantitative finance. Topics include portfolio optimization, exotic derivatives, high frequency analysis of data and numerical methods. While most talks require knowledge of mathematical methods in finance, some talks are accessible to general audience.

• TR 7:40 p.m.-8:55 p.m.
• Instructor: Mikhail Smirnov
  CULPA: 16 Info
• 3 points

PROG FOR QUANT & COMP FINANCE

This course covers programming with applications to finance. The applications may include such topics as yield curve building and calibration, short rate models, Libor market models, Monte Carlo simulation, valuation of financial instruments such as options, swaptions and variance swaps, and risk measurement and management, among others. Students will learn about the underlying theory, learn coding techniques, and get hands-on experience in implementing financial models and systems.

• F 6:10 p.m.-8 p.m.
• Instructor: Ka-Yi Ng
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• 3 points

FINANCIAL RISK MGMT & REGULATION

Prerequisites: student expected to be mathematically mature and familiar with probability and statistics, arbitrage pricing theory, and stochastic processes. The course will introduce the notions of financial risk management, review the structure of the markets and the contracts traded, introduce risk measures such as VaR, PFE and EE, overview regulation of financial markets, and study a number of risk management failures. After successfully completing the course, the student will understand the basics of computing parametric VaR, historical VaR, Monte Carlo VaR, cedit exposures and CVA and the issues and computations associated with managing market risk and credit risk. The student will be familiar with the different categories of financial risk, current regulatory practices, and the events of financial crises, especially the most recent one.

• W 7:40 p.m.-9:30 p.m.
• Instructor: Harvey Stein
  h-index: None Info
• 3 points

MATH MTHDS-FIN PRICE ANALYSIS

Course covers modern statistical and physical methods of analysis and prediction of financial price data. Methods from statistics, physics and econometrics will be presented with the goal to create and analyze different quantitative investment models.

• S 7 p.m.-9:20 p.m.
• Instructor: Alexei Chekhlov
  CULPA: 3 h-index: 10 Info
• 3 points

MULTI-ASSET PORTFOLIO MGMT

The course will cover practical issues such as: how to select an investment universe and instruments, derive long term risk/return forecasts, create tactical models, construct and implement an efficient portfolio,to take into account constraints and transaction costs, measure and manage portfolio risk, and analyze the performance of the total portfolio.

• MW 6:10 p.m.-7:25 p.m.
• 3 points

Machine Learning for Finance

The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace, but still nascent in its potential.  This course provides an overview of ML applications for finance use cases including trading, investment management, and consumer banking. 

Students will learn how to work with financial data and how to apply ML algorithms using the data.  In addition to providing an overview of the most commonly used ML models, we will detail the regression, KNN, NLP, and time series deep learning ML models using desktop and cloud technologies. 

The course is taught in Python using Numpy, Pandas, scikit-learn and other libraries.  Basic programming knowledge in any language is required.

• S 2:40 p.m.-4:30 p.m.
• Instructor: Renzo Silva
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• 3 points

Credit Analytics

This course uses a combination of lectures and case studies to introduce students to the modern credit analytics. The objective for the course is to cover major analytic concepts, ideas with a focus on the underlying mathematics used in both credit risk management and credit valuation.  We will start from an empirical analysis of default probabilities (or PD), recovery rates and rating transitions. Then we will introduce the essential concepts of survival analysis as a scientific way to study default.  For credit portfolio we will study and compare different approaches such as CreditPortfolio View, CreditRisk+ as well as copula function approach. For valuation we will cover both single name and portfolio models.

• F 1:10 p.m.-3:40 p.m.
• Instructor: David X Li
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• 3 points

INTEREST RATES MODELS

The objective of this course is to introduce students to interest rates models and to build step by step a coherent understanding of the interest rates world, from the stripping of a yield curve to the modern frameworks of option pricing. Adopting a practitioner’s perspective, it will put an emphasis on building a strong intuition on the products and models, and will adopt a balanced approach between formal derivation and concrete applications.

• F 6:10 p.m.-8 p.m.
• Instructor: Paul-Guillaume Fournie
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• 3 points

A MATHEMATICAL APPROACH TO GENERATIVE AI

GENERATIVE AI IN FINANCE

Generative AI (“GenAI") is reshaping the global economy and the future of work by revolutionizing problem-solving, optimizing complex systems, and enabling data-driven decision-making. Its profound impact spans across natural language understanding, image generation, and predictive analytics, marking a paradigm shift that necessitates a deep and rigorous understanding of its mathematical foundations. This course is designed to equip students with a comprehensive framework for exploring the mathematical principles underpinning GenAI. Emphasizing statistical modeling, optimization, and computational techniques, the curriculum provides the essential tools to develop and analyze cutting-edge generative models.

• S 4:30 p.m.-6:20 p.m.
• Instructor: Faculty
  h-index: 37 Info
• 3 points

INTRODUCTION TO QUANTITATIVE BALANCE SHE

QUANT BALANCE SHEET STRAT

This course introduces students to a quantitative approach to defining and executing on commercial bank balance sheet strategy. Students will receive working knowledge of analyzing, managing and optimizing interest rate risk, liquidity risk and capital risk exposures of commercial bank balance sheets. The course also provides an overview of quantitative approaches to evaluation of business trends within the US commercial banking industry which informs balance sheet strategy of a typical commercial bank.

• S noon-2 p.m.
• 3 points

MAFN FIELDWORK

Prerequisites: all 6 MAFN core courses, at least 6 credits of approved electives, and the instructors permission. See the MAFN website for details. This course provides an opportunity for MAFN students to engage in off-campus internships for academic credit that counts towards the degree. Graded by letter grade. Students need to secure an internship and get it approved by the instructor.

• Instructor: Mikhail Smirnov
  CULPA: 16 Info
• 1-3 points

Career Development for Quantitative Fina

Career Develop for Quant

This course helps the students understand the job search process and develop the professional skills necessary for career advancement. The students will not only learn the best practices in all aspects of job-seeking but will also have a chance to practice their skills. Each class will be divided into two parts: a lecture and a workshop.

In addition, the students will get support from Teaching Assistants who will be available to guide and prepare the students for technical interviews.

• MW 11:40 a.m.-12:55 p.m.
• Instructor: Mikhail Smirnov
  CULPA: 16 Info
• 0 points

THE TEACHING OF MATHEMATICS

A seminar required of all incoming graduate students, designed to instill effective teaching techniques.

• T 2:40 p.m.-3:55 p.m.
• Instructor: George Dragomir
  CULPA: 5 Info
• 0 points

ANALYSIS II

Continuation of MATH GR6151x (see Fall listing).

• TR 10:10 a.m.-11:25 a.m.
• Instructor: Daniela de Silva
  CULPA: 21 Wikipedia Info
• 4.5 points

PROBABILITY II

Prerequisites: MATH GR6151 MATH G4151 Analysis & Probability I. Continuation of MATH GR6152x (see fall listing).

• TR 11:40 a.m.-12:55 p.m.
• Instructor: Ivan Corwin
  CULPA: 1 Wikipedia h-index: 34 Info
• 4.5 points

COMPLEX ANALYSIS/RIEMANN SURF

Continuation of MATH GR6175x (see Fall listing).

• TR 1:10 p.m.-2:25 p.m.
• Instructor: Duong H Phong
  Wikipedia Info
• 4.5 points

ARITH & ALGEBRAIC GEOMETRY

Affine and projective varieties; schemes; morphisms; sheaves; divisors; cohomology theory; curves; Riemann-Roch theorem.

• MW 4:10 p.m.-5:25 p.m.
• Instructor: Aise Johan de Jong
  CULPA: 5 Wikipedia Info
• 4.5 points

ALGEBRAIC TOPOLOGY II

Continuation of MATH GR6307x (see Fall listing).

• MW 1:10 p.m.-2:25 p.m.
• Instructor: Lucy Yang
  Info
• 4.5 points

LIE GROUPS & REPRESENTATIONS

Continuation of MATH GR6343x (see Fall listing).

• MW 2:40 p.m.-3:55 p.m.
• Instructor: Andrei Okounkov
  CULPA: 1 Wikipedia h-index: 55 Info
• 4.5 points

MODERN GEOMETRY

Continuation of Mathematics GR6402x (see Fall listing).

• MW 10:10 a.m.-11:25 a.m.
• Instructor: Elena Giorgi
  h-index: 5 Info
• 4.5 points

ALGEBRAIC NUMBER THEORY

Local and global fields, group cohomology, local class field theory, global class field theory and applications.

• MW 11:40 a.m.-12:55 p.m.
• Instructor: Gyujin Oh
  Info
• 4.5 points

TOPICS IN NUMBER THEORY

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Dorian Goldfeld
  CULPA: 23 Wikipedia Info
• 4 points