Courses

Analysis of Big Data (QCR)
Subject associations
ORF 350

This course is a theoretically oriented introduction to the statistical tools that underpin modern machine learning, whose hallmarks are large datasets and/or complex models. Topics include a rigorous analysis of dimensionality reduction, a survey of models ranging from regression to neural networks, and an analysis of learning algorithms.

Computing and Optimization for the Physical and Social Sciences (QCR)
Subject associations
ORF 363 / COS 323

An introduction to several fundamental and practically-relevant areas of modern optimization and numerical computing. Topics include computational linear algebra, first and second order descent methods, convex sets and functions, basics of linear and semidefinite programming, optimization for statistical regression and classification, and techniques for dealing with uncertainty and intractability in optimization problems. Extensive hands-on experience with high-level optimization software. Applications drawn from operations research, statistics and machine learning, economics, control theory, and engineering.

Computing and Optimization for the Physical and Social Sciences (QCR)
Subject associations
ORF 363 / COS 323

An introduction to several fundamental and practically-relevant areas of modern optimization and numerical computing. Topics include computational linear algebra, first and second order descent methods, convex sets and functions, basics of linear and semidefinite programming, optimization for statistical regression and classification, and techniques for dealing with uncertainty and intractability in optimization problems. Extensive hands-on experience with high-level optimization software. Applications drawn from operations research, statistics and machine learning, economics, control theory, and engineering.

Computing and Optimization for the Physical and Social Sciences (QCR)
Subject associations
ORF 363 / COS 323

An introduction to several fundamental and practically-relevant areas of modern optimization and numerical computing. Topics include computational linear algebra, first and second order descent methods, convex sets and functions, basics of linear and semidefinite programming, optimization for statistical regression and classification, and techniques for dealing with uncertainty and intractability in optimization problems. Extensive hands-on experience with high-level optimization software. Applications drawn from operations research, statistics and machine learning, economics, control theory, and engineering.

Electronic Commerce
Subject associations
ORF 401

Electronic commerce, traditionally the buying and selling of goods using electronic technologies, extends to essentially all facets of human interaction when extended to services, particularly information. The course focuses on both the software and the hardware aspects of traditional aspects as well as the broader aspects of the creation, dissemination and human consumption electronic services. Covered will be the physical, financial and social aspects of these technologies

Energy and Commodities Markets
Subject associations
ORF 455 / ENE 455

This course is an introduction to commodities markets (oil, gas, metals, electricity, etc.), and quantitative approaches to capturing uncertainties in their demand and supply. We start from a financial perspective, and traditional models of commodity spot prices and forward curves. Then we cover modern topics: game theoretic models of energy production (OPEC vs. fracking vs. renewables); quantifying the risk of intermittency of solar and wind output on the reliability of the electric grid (mitigating the duck curve); financialization of commodity markets; carbon emissions markets. We also discuss economic and policy implications.

Financial Risk and Wealth Management
Subject associations
ORF 435

This course covers the basic concepts of measuring, modeling and managing risks within a financial optimization framework. Topics include single and multi-stage financial planning systems. Implementation from several domains within asset management and goal based investing. Machine learning algorithms are introduced and linked to the stochastic planning models. Python and optimization exercises required.

Financial Risk and Wealth Management
Subject associations
ORF 435

This course covers the basic concepts of measuring, modeling and managing risks within a financial optimization framework. Topics include single and multi-stage financial planning systems. Implementation from several domains within asset management and goal based investing. Machine learning algorithms are introduced and linked to the stochastic planning models. Python and optimization exercises required.

Fundamentals of Queueing Theory (QCR)
Subject associations
ORF 407

This is an introduction to the stochastic models inspired by the dynamics of resource sharing. Topics discussed include: early motivating communication systems (telephone and computer networks); modern applications (call centers, healthcare operations, and urban planning for smart cities); and key formulas (from Erlang blocking and delay to Little's law). We also review supporting stochastic theories like equilibrium Markov chains along with Markov, Poisson and renewal processes.

Fundamentals of Statistics (QCR)
Subject associations
ORF 245 / EGR 245

A first introduction to probability and statistics. This course will provide background to understand and produce rigorous statistical analysis including estimation, confidence intervals, hypothesis testing and regression and classification. Applicability and limitations of these methods will be illustrated using a variety of modern real world data sets and manipulation of the statistical software R.

Fundamentals of Statistics (QCR)
Subject associations
ORF 245 / EGR 245

A first introduction to probability and statistics. This course will provide background to understand and produce rigorous statistical analysis including estimation, confidence intervals, hypothesis testing and regression and classification. Applicability and limitations of these methods will be illustrated using a variety of modern real world data sets and manipulation of the statistical software R.

Fundamentals of Statistics (QCR)
Subject associations
ORF 245 / EGR 245

A first introduction to probability and statistics. This course will provide background to understand and produce rigorous statistical analysis including estimation, confidence intervals, hypothesis testing and regression. Applicability and limitations of these methods will be illustrated in the light of modern data sets and manipulation of the statistical software R. Precepts are based on real data analysis.

High Frequency Markets: Models and Data Analysis
Subject associations
ORF 445

An introduction to the theory and practice of high frequency trading in modern electronic financial markets. We give an overview of the institutional landscape and basic empirical features of modern equity, futures, and fixed income markets. We discuss theoretical models for market making and price formation. Then we dig into detailed empirical aspects of market microstructure and how these can be used to construct effective trading strategies. Course work will be a mixture of theoretical and data-driven problems. Programming environment will be a mixture of the R statistical environment, with the Kdb database language.

Independent Research Project
Subject associations
ORF 376

Independent research or investigation resulting in a report in the student's area of interest under the supervision of a faculty member. Open to sophomores and juniors.

Independent Research Project
Subject associations
ORF 375

Independent research or investigation resulting in a substantial formal report in the student's area of interest under the supervision of a faculty member.

Independent Research Project
Subject associations
ORF 375

Independent research or investigation resulting in a substantial formal report in the student's area of interest under the supervision of a faculty member.

Introduction to Financial Mathematics (QCR)
Subject associations
ORF 335 / ECO 364

Financial Mathematics is concerned with designing and analyzing products that improve the efficiency of markets, and create mechanisms for reducing risk. This course develops quantitative methods for these goals: the notions of arbitrage and risk-neutral pricing in discrete time, specific models such as Black-Scholes and Heston in continuous time, and calibration to market data. Credit derivatives, the term structure of interest rates, and robust techniques in the context of volatility options will be discussed, as well as lessons from the financial crisis.

Introduction to Monte Carlo Simulation
Subject associations
ORF 409

An introduction to the uses of simulation and computation for analyzing stochastic models and interpreting real phenomena. Topics covered include generating discrete and continuous random variables, stochastic ordering, the statistical analysis of simulated data, variance reduction techniques, statistical validation techniques, nonstationary Markov chains, and Markov chain Monte Carlo methods. Applications are drawn from problems in finance, manufacturing, and communication networks. Students will be encouraged to program in Python. Office hours will be offered for students unfamiliar with the language.

Introduction to Monte Carlo Simulation
Subject associations
ORF 409

An introduction to the uses of simulation and computation for analyzing stochastic models and interpreting real phenomena. Topics covered include generating discrete and continuous random variables, stochastic ordering, the statistical analysis of simulated data, variance reduction techniques, statistical validation techniques, nonstationary Markov chains, and Markov chain Monte Carlo methods. Applications are drawn from problems in finance, manufacturing, and communication networks. Students will be encouraged to program in Python. Office hours will be offered for students unfamiliar with the language.

Networks
Subject associations
ORF 387

This course showcases how networks are widespread in society, technology, and nature, via a mix of theory and applications. It demonstrates the importance of understanding network effects when making decisions in an increasingly connected world. Topics include an introduction to graph theory, game theory, social networks, information networks, strategic interactions on networks, network models, network dynamics, information diffusion, and more.

Networks
Subject associations
ORF 387

This course showcases how networks are widespread in society, technology, and nature, via a mix of theory and applications. It demonstrates the importance of understanding network effects when making decisions in an increasingly connected world. Topics include an introduction to graph theory, game theory, social networks, information networks, strategic interactions on networks, network models, network dynamics, information diffusion, and more.

Optimal Learning (QCR)
Subject associations
ORF 418

This course develops several methods that are central to modern optimization and learning problems under uncertainty. These include dynamic programming, linear quadratic regulator, Kalman filter, multi-armed bandits and reinforcement learning. Representative applications and numerical methods are emphasized.

Optimal Learning (QCR)
Subject associations
ORF 418

This course develops several methods that are central to modern optimization and learning problems under uncertainty. These include dynamic programming, linear quadratic regulator, Kalman filter, multi-armed bandits and reinforcement learning. Representative applications and numerical methods are emphasized.

Optimization
Subject associations
ORF 307 / EGR 307

This course focuses on analytical and computational tools for optimization. We will introduce least-squares optimization with multiple objectives and constraints. We will also discuss linear optimization modeling, duality, the simplex method, degeneracy, interior point methods and network flow optimization. Finally, we will cover integer programming and branch-and-bound algorithms. A broad spectrum of real-world applications in engineering, finance and statistics is presented.

Probability and Stochastic Systems
Subject associations
ORF 309 / EGR 309 / MAT 380

An introduction to probability and its applications. Topics include: basic principles of probability; Lifetimes and reliability, Poisson processes; random walks; Brownian motion; branching processes; Markov chains

Probability and Stochastic Systems
Subject associations
ORF 309 / EGR 309 / MAT 380

An introduction to probability and its applications. Topics include: basic principles of probability; Lifetimes and reliability, Poisson processes; random walks; Brownian motion; branching processes; Markov chains

Probability and Stochastic Systems
Subject associations
ORF 309 / EGR 309 / MAT 380

An introduction to probability and its applications. Topics include: basic principles of probability; Lifetimes and reliability, Poisson processes; random walks; Brownian motion; branching processes; Markov chains.

Regression and Applied Time Series
Subject associations
ORF 405

An introduction to popular statistical approaches in regression and time series analysis. Topics will include theoretical aspects and practical considerations of linear, nonlinear, and nonparametric modeling (kernels, neural networks, and decision trees).

Regression and Applied Time Series
Subject associations
ORF 405

An introduction to popular statistical approaches in regression and time series analysis. Topics will include theoretical aspects and practical considerations of linear, nonlinear, and nonparametric modeling (kernels, neural networks, and decision trees).

Senior Project
Subject associations
ORF 479

Students conduct a one-semester project. Topics chosen by students with approval of the faculty. A written report is required at the end of the term.

Senior Thesis
Subject associations
ORF 478

A formal report on research involving analysis, synthesis, and design, directed toward improved understanding and resolution of a significant problem. The research is conducted under the supervision of a faculty member, and the thesis is defended by the student at a public examination before a faculty committee. The senior thesis is equivalent to a year-long study and is recorded as a double course in the Spring.

Senior Thesis
Subject associations
ORF 478

A formal report on research involving analysis, synthesis, and design, directed toward improved understanding and resolution of a significant problem. The research is conducted under the supervision of a faculty member, and the thesis is defended by the student at a public examination before a faculty committee. The senior thesis is equivalent to a year-long study and is recorded as a double course in the Spring.

Special Topics in Operations Research and Financial Engineering: Financial Technology and Data-Driven Innovation
Subject associations
ORF 473

Over recent decades, novel data sources and machine learning models have enabled rapid evolution across financial services. This course focuses on ongoing innovations in consumer lending. The technical material spans finance and machine learning topics, including fairness and explainability, important in lending and also more broadly. The class integrates technical topics with critical explorations of business practices informed by readings, class discussion and outside speakers, and includes work with industry data sets.

Special Topics in Operations Research and Financial Engineering: Financial Technology and Data-Driven Innovation
Subject associations
ORF 473

Over recent decades, novel data sources and machine learning models have enabled rapid evolution across financial services. This course focuses on ongoing innovations in consumer lending. The technical material spans finance and machine learning topics, including fairness and explainability, important in lending and also more broadly. The class integrates technical topics with critical explorations of business practices informed by readings, class discussion and outside speakers, and includes work with industry data sets.

Special Topics in Operations Research and Financial Engineering: Financial Technology and Data-Driven Innovation
Subject associations
ORF 473

Over recent decades, novel data sources and machine learning models have enabled rapid evolution across financial services. This course focuses on ongoing innovations in consumer lending. The technical material spans finance and machine learning topics, including fairness and explainability, important in lending and also more broadly. The class integrates technical topics with critical explorations of business practices informed by readings, class discussion and outside speakers, and includes work with industry data sets.

Special Topics in Operations Research and Financial Engineering: Network Game Theory
Subject associations
ORF 474

An introduction to network games. Topics will include: A crash course on state games, introduction to graph theory and network games, games with incomplete information and auctions, non-atomic games, signals and correlated equilibria.

Transportation Systems Analysis
Subject associations
ORF 467

Studied is the transportation sector of the economy from a technology and policy planning perspective. The focus is on the methodologies and analytical tools that underpin policy formulation, capital and operations planning, and real-time operational decision making within the transportation industry. Case studies of innovative concepts such as "value" pricing, real-time fleet management and control, GPS-based route guidance systems, automated transit systems and autonomous vehicles will provide a practical focus for the methodologies. Class project in lieu of final exam focused on major issue in Transportation Systems Analysis.