Course Schedule

Current semester Fall 2015, and future semesters are now available to view.

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Number

Name

Professor(s)

Meet Time

Room

CSCI-GA.1133-001
(1157) PAC I* Evan Korth
Office Hours T 6:30-9:00PM CIWW 201

An accelerated introduction to the fundamental concepts of computer science for students who lack a formal background in the field. Topics include algorithm design and program development; data types; control structures; subprograms and parameter passing; recursion; data structures; searching and sorting; dynamic storage allocation and pointers; abstract data types, such as stacks, queues, lists, and tree structures; generic packages; and an introduction to the principles of object-oriented programming. The primary programming language used in the course will be Java. Students should expect an average of 12-16 hours of programming and related course work per week.
CSCI-GA.1133-002
(1776) PAC I Recitation Scott Buckfelder W 7:10-8:00PM CIWW 317

An accelerated introduction to the fundamental concepts of computer science for students who lack a formal background in the field. Topics include algorithm design and program development; data types; control structures; subprograms and parameter passing; recursion; data structures; searching and sorting; dynamic storage allocation and pointers; abstract data types, such as stacks, queues, lists, and tree structures; generic packages; and an introduction to the principles of object-oriented programming. The primary programming language used in the course will be Java. Students should expect an average of 12-16 hours of programming and related course work per week.
CSCI-GA.1170-001
(1158) Fundamental Algorithms Yevgeniy Dodis
Office Hours T 5:10-7:00PM CIWW 109

Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, selection, binary search trees and balanced-tree strategies, tree traversal, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques.

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
CSCI-GA.1170-002
(1159) Fundamental Algorithms Recitation Maria Pershina R 5:10-6:00PM CIWW 109

Reviews a number of important algorithms, with emphasis on correctness and efficiency. The topics covered include solution of recurrence equations, sorting algorithms, selection, binary search trees and balanced-tree strategies, tree traversal, partitioning, graphs, spanning trees, shortest paths, connectivity, depth-first and breadth-first search, dynamic programming, and divide-and-conquer techniques.

Prerequisites: At least one year of experience with a high-level language such as Pascal, C, C++, or Java; and familiarity with recursive programming methods and with data structures (arrays, pointers, stacks, queues, linked lists, binary trees).
CSCI-GA.1180-001
(17764) Mathematical Techniques For CS Applications Margaret Wright
Office Hours M 5:10-7:00PM CIWW 512

An introduction to theory, computational techniques, and applications of linear algebra, probability and statistics. These three areas of continuous mathematics are critical in many parts of computer science, including machine learning, scientific computing, computer vision, computational biology, natural language processing, and computer graphics. The course teaches a specialized language for mathematical computation, such as Matlab, and discusses how the language can be used for computation and for graphical output. No prior knowledge of linear algebra, probability, or statistics is assumed.
CSCI-GA.2110-001
(1161) Programming Languages Benjamin Goldberg
Office Hours W 5:10-7:00PM CIWW 109

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-002
(1162) Programming Languages Recitation Deepti Verma R 7:10-8:00PM CIWW 1302

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-003
(2216) Programming Languages Cory Plock
Office Hours M 5:10-7:00PM CIWW 201

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-004
(1806) Programming Languages Recitation Vikramsreehari Mullachery R 8:10-9:00PM CIWW 1302

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2110-005
(25142) Programming Languages Recitation Deepti Verma R 1:00-1:50PM CIWW 312

Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

Prerequisites: Students taking this class should already have substantial programming experience.
CSCI-GA.2112-001
MATH-GA 2043-001
(1163) Scientific Computing Aleksandar Donev
Office Hours R 5:10-7:00PM CIWW 1302
Methods for numerical applications in the physical and biological sciences, engineering, and finance. Basic principles and algorithms; specific problems from various application areas; use of standard software packages.

Prerequisites: Multivariate calculus and linear algebra. Some programming experience recommended.
CSCI-GA.2130-001
(1164) Compiler Construction Kristoffer Rose
Office Hours
Eva Rose R 5:10-7:00PM CIWW 312
This is a capstone course based on compilers and modern programming languages. The topics covered include structure of one-pass and multiple-pass compilers; symbol table management; lexical analysis; traditional and automated parsing techniques, including recursive descent and LR parsing; syntax-directed translation and semantic analysis; run-time storage management; intermediate code generation; introduction to optimization; and code generation. The course includes a special compiler-related capstone project, which ties together concepts of algorithms, theory (formal languages), programming languages, software engineering, computer architecture, and other subjects covered in the MS curriculum. This project requires a substantial semester-long programming effort, such as construction of a language compilation or translation system that includes lexical and syntactic analyzers, a type checker, and a code generator.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2180-001
(2218) Financial Software Projects Scott Burton
Office Hours M 7:10-9:00PM CIWW 512
The theme of this course is an "applied case study" and focuses on fixed income markets. Topics covered include an overview of the markets, the inner workings of an investment bank, the market players, and where software engineers fit in. Students will be grouped into small teams to build a financial application using practical software engineering principles. Each team will build a risk management framework, starting with basic components.

Prerequisites: It is assumed that the students can code in C++. No prior experience in the financial sector domain is required.
CSCI-GA.2246-001
(2220) Open Source Tools Jeffrey Korn
Office Hours M 7:10-9:00PM CIWW 202
This course covers a brief history and philosophy of open source software, followed by an in-depth look at open source tools intended for developers. In particular, we will present an overview of the Linux operating system, command line tools (find, grep, sed), programming tools (GIT, Eclipse, DTrace), web and database tools (Apache, MySQL), and system administration tools. We will also cover scripting languages such as shell and Python.

Prerequisites: An understanding of modern operating systems and a working knowledge of a programming language, such as C, C++ or Java
CSCI-GA.2250-001
(1165) Operating Systems Hubertus Franke
Office Hours M 7:10-9:00PM CIWW 1302
The topics covered include a review of linkers and loaders and the high-level design of key operating systems concepts such as process scheduling and synchronization; deadlocks and their prevention; memory management, including (demand) paging and segmentation; and I/O and file systems, with examples from Unix/Linux and Windows. Programming assignments may require C, C++, Java, or C#.
CSCI-GA.2262-001
(1830) Data Communications and Networks Jean-Claude Franchitti
Office Hours R 7:10-9:00PM CIWW 312

This course teaches the design and implementation techniques essential for engineering robust networks. Topics include networking principles, Transmission Control Protocol/Internet Protocol, naming and addressing (Domain Name System), data encoding/decoding techniques, link layer protocols, routing protocols, transport layer services, congestion control, quality of service, network services, programmable routers and overlay networks.

Prerequisites: Students must have a working knowledge of fundamental data structures and associated algorithms. For some of the practical aspects of the course, a working knowledge of an object-oriented programming language (e.g., C++, C#, or preferably Java) is expected. An undergraduate course in data communication and networks is helpful but not required.
CSCI-GA.2270-001
(17241) Computer Graphics Kenneth Perlin
Office Hours W 5:10-7:00PM CIWW 101

Problems and objectives of computer graphics. Vector, curve, and character generation. Interactive display devices. Construction of hierarchical image list. Graphic data structures and graphics languages. Hidden-line problems; windowing, shading, and perspective projection. Curved surface generation display.

Prerequisites: CSCI-GA 1170 and CSCI-UA 140 (or an equivalent undergraduate course in linear algebra).
CSCI-GA.2271-001
(2221) Computer Vision Davi Geiger
Office Hours W 7:10-9:00PM CIWW 312

Basic techniques of computer vision and image processing. General algorithms for image understanding problems. Study of binary image processing, edge detection, feature extraction, motion estimation, color processing, stereo vision, and elementary object recognition. Mathematical, signal processing, and image processing tools. Relation of computer vision algorithms to the human visual system.

Prerequisites: CSCI-GA 1170
CSCI-GA.2420-001
MATH-GA 2010-001
(1166) Numerical Methods I Georg Stadler R 5:10-7:00PM CIWW 101
Numerical linear algebra. Approximation theory. Quadrature rules and numerical integration. Nonlinear equations and optimization. Ordinary differential equations. Elliptic equations. Iterative methods for large, sparse systems. Parabolic and hyperbolic equations.

Prerequisites: Corequisite: linear algebra.
CSCI-GA.2433-001
(1824) Database Systems Eric Mann-Hielscher
Office Hours T 7:10-9:00PM CIWW 312
Database system architecture. Modeling an application and logical database design. The relational model and relational data definition and data manipulation languages. Design of relational databases and normalization theory. Physical database design. Concurrency and recovery. Query processing and optimization.
CSCI-GA.2434-001
(1167) Advanced Database Systems Dennis Shasha
Office Hours T 5:10-7:00PM CIWW 101
This is a capstone course emphasizing large-scale database systems. This course studies the internals of database systems as an introduction to research and as a basis for rational performance tuning. Topics include concurrency control, fault tolerance, operating system interactions, query processing, and principles of tuning. Database capstone projects involve topics such as design, concurrency control, interactions, and tuning. These projects include some or all of the following elements: formation of a small team, project proposal, literature review, interim report, project presentation, and final report.

Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250.
CSCI-GA.2560-001
(17239) Artificial Intelligence Ernest Davis
Office Hours W 5:10-7:00PM CIWW 312

There are many cognitive tasks that people do easily and almost unconsciously but that have proven extremely difficult to program on a computer. Artificial intelligence is the problem of developing computer systems that can carry out these tasks. This course covers problem solving and state space search; automated reasoning; probabilistic reasoning; planning; and knowledge representation.
CSCI-GA.2566-001
(2223) Foundations Of Machine Learning Mehryar Mohri
Office Hours M 5:10-7:00PM CIWW 1302

This course introduces the fundamental concepts and methods of machine learning, including the description and analysis of several modern algorithms, their theoretical basis, and the illustration of their applications. Many of the algorithms described have been successfully used in text and speech processing, bioinformatics, and other areas in real-world products and services. The main topics covered are probability and general bounds; PAC model; VC dimension; perceptron, Winnow; support vector machines (SVMs); kernel methods; decision trees; boosting; regression problems and algorithms; ranking problems and algorithms; halving algorithm, weighted majority algorithm, mistake bounds; learning automata, Angluin-type algorithms; and reinforcement learning, Markov decision processes (MDPs).

Prerequisites: CSCI-GA 1180.
CSCI-GA.2930-002
MATH-GA 2830-002
(25629) Advanced Topics in Applied Math: Fast Analysis-Based Algorithms Michael O'Neil M 1:25-3:15PM CIWW 512
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2945-002
MATH-GA 2011-002
(1168) Advanced Topics in Numerical Analysis: Approximation Theory & Practice Lloyd N. Trefethen TR 1:25-3:15PM CIWW 1302
Topics vary each semester.

Prerequisites: Topics determine prerequisites.
CSCI-GA.2965-001
(1169) Heuristic Problem Solving Dennis Shasha
Office Hours T 7:10-9:00PM CIWW 317
This course revolves around several problems new to computer science (derived from games or puzzles in columns for Dr. Dobb’s Journal, Scientific American, and elsewhere). The idea is to train students to face a new problem, read relevant literature, and come up with a solution. The solution entails winning a contest against other solutions. The winner receives candy. The best solutions become part of an evolving “Omniheurist” Web site that is expected to get many visitors over the years. The course is for highly motivated, mathematically adept students. It is open to supported Ph.D. students and well-qualified master’s students. Class size has been around 10 in the past, and instructor and students have all gotten to know one another very well. Algorithmic and programming knowledge is the main prerequisite. It also helps to be familiar with a rapid prototyping language such as Matlab, Mathematica, K, or Python, or to be completely fluent in some other language.

Prerequisites: CSCI-GA 1170 and an ability to prototype algorithms rapidly.
CSCI-GA.3033-001
(1170) Special Topics: Production Quality Software Michael Schidlowsky
Office Hours W 5:10-7:00PM CIWW 317

In this course, students learn to develop production quality software. Lectures present real-world development practices that maximize software correctness and minimize development time. A special emphasis is placed on increasing proficiency in a particular programming language by doing weekly development projects and participating in code reviews.

Assignments become more sophisticated as the semester progresses, eventually incorporating unit tests, build scripts, design patterns, and other techniques. The course culminates with an assignment that requires students to contribute to an open-source project of their choice.
CSCI-GA.3033-002
(1171) Special Topics: Distributed Systems Jinyang Li
Office Hours T 5:10-7:00PM CIWW 312

Distributed systems help programmers aggregate the resource of many networked computers to construct highly available and scalable services, such as peta-byte storage, massively parallel computation. This class teaches the abstractions, design and implementation techniques that allow you to build fast, scalable, fault-tolerant distributed systems. Topics include multithreading, network programming, consistency, naming, fault tolerance, and security and several case studies of distributed systems.

This class is a graduate-level course, but undergraduate students are welcome! The course consists of lectures and a series of programming labs.
CSCI-GA.3033-003
(1172) Special Topics: Music Software Projects Scott Burton
Office Hours F 4:00-5:50PM CIWW 312

Did you ever wonder why there are 12 notes in the western music scale? Or how the intervals between notes came to be? When were the first musical scales developed or "discovered" and how (and why) have they been modified since? Who were the key innovators of western music theory over the last few centuries?

It is not uncommon for software developers to have an affinity for music. After all, the creation of both software and music is part art and part science. Further, music and computing are built upon fundamental mathematical principles. While it is not required to understand music theory to be a good player, understanding why we are constrained to a certain set of notes is an enlightening topic - for musicians and non-musicians alike.

This course is for students interested in both music and software construction!
CSCI-GA.3033-004
(1173) Special Topics: Graphics Processing Units (GPUs): Architecture & Programming Mohamed Zahran
Office Hours T 5:10-7:00PM CIWW 317

In this course, we will cover architectural aspects and capabilities of modern GPUs (graphics processing unit) and will learn how to program GPUs to solve different type of problems. Many computations can be performed much faster on the GPU than on a traditional processor. This is why GPUs are present now in almost all computers; and the majority of Top 500 supercomputers in the world are built around GPUs. GPUs are no longer restricted to graphics applications but are now used for a diverse set of applications and domains. This introduces the concept of general-purpose GPUs or GPGPUs, which is the main subject of this course.

Prerequisites: This is a capstone course and has CSCI-GA 1170 Fundamental Algorithms, CSCIGA 2110 Programming Languages and CSCI-GA 2250 Operating Systems as prerequisites.
CSCI-GA.3033-005
(1174) Special Topics: Principles of Software Security Patrick Cousot
Office Hours M 5:10-7:00PM CIWW 312

Traditionally, computer security is enforced by the operating system, which uses special hardware support to ensure security properties at application boundaries. However, the proliferation of successful attacks, such as viruses, worms, SQL injection, and cross-site scripting, shows that traditional approaches to security are insufficient. Adversaries exploit weaknesses both in the operating system itself, bypassing any protection mechanisms, and more and more frequently at the application level, where the operating system provides very limited guarantees. In this class we consider how programming language techniques can be used to fill the security gap by defending against application-level attacks. The approach is based on the static analysis of the program source to certify security properties.
CSCI-GA.3033-006
(1175) Special Topics: Realtime & Big Data Analytics Suzanne McIntosh
Office Hours R 7:10-9:00PM CIWW 102

This course will introduce technologies at the foundation of the Big Data movement that have facilitated scalable management of vast quantities of data collected through realtime and near realtime sensing. We will also explore the tools enabling the acquisition of near realtime data in the social domain, the fusion of those data when in flight and at rest, and their meaningful representation in graphical visualizations. Students are required to complete weekly reading and/or programming assignments and demonstrate mastery of course topics by developing and demonstrating a software project of their choosing. Class time will be set aside for project proposal and final demo.

Prerequisites: CSCI-GA 2250 or equivalent Operating Systems course; programming experience in C/C++ or Java for assignments and final project; CSCI-GA 2262, CSCI-GA 2620, or undergraduate course in networks. A familiarity with databases will be useful.
CSCI-GA.3033-007
(1176) Special Topics: Social Multiplayer Games Yoav Zibin
Office Hours R 5:10-7:00PM CIWW 517

The course will teach how to develop online casual multiplayer games using open technologies such as HTML5, JavaScript, AngularJS, Ionic, Bootstrap, PhoneGap, Grunt, and testing using Karma, Jasmine, Protractor. The course has two big projects: a turn-based and a real-time multiplayer game. The course will also teach about artificial-intelligence for games, ranking systems, physics-based engines, and integrating with social platforms. The course will not concern with 3D graphics.
CSCI-GA.3033-008
(17255) Special Topics: Statistical Natural Language Processing Slav Petrov
Office Hours T 5:10-7:00PM CIWW 512

In this course we will explore statistical, model based approaches to natural language processing. There will be a focus on corpus-driven methods that make use of supervised and unsupervised machine learning methods and algorithms. We will examine some of the core tasks in natural language processing, starting with simple word-based models for text classification and building up to rich, structured models for syntactic parsing and machine translation. In each case we will discuss recent research progress in the area and how to design efficient systems for practical user applications. In the course assignments you will construct basic systems and then improve them through a cycle of error analysis and model redesign. This course assumes a good background in basic probability and a strong ability and interest to program in Java. The class is open to graduate as well as undergraduate students.
CSCI-GA.3033-009
MCC-GE 2130-001
(20034) Special Topics: Topics in Digital Media Helen Nissenbaum
Office Hours R 2:00-4:10PM CIWW 412

Information technology and digital media, often associated with threats to privacy, are increasingly called upon to protect, preserve, and enhance it. This graduate-level, project-based course observes both sides of the story through a multidisciplinary lens. It examines topical policy issues as well as controversial systems and technologies that both threaten privacy, and are called in service of its protection. Course modules may include Web tracking, biometric Identification, big data, quantified self, Internet of things, and social networks. For each of these, it will survey underlying technologies and related ethical, legal, and policy issues. Ideally, the course will attract students with diverse backgrounds, some in technical fields others in the social sciences and humanities, who will collaborate on term projects.
CSCI-GA.3033-010
(24717) Special Topics: Transformation to Cloud Computing Nikolai Joukov
Office Hours R 7:10-9:00PM CIWW 512

For many enterprises, taking advantage of cloud computing involves migrating existing applications from the traditional IT (Information Technology) infrastructure to cloud, as opposed to merely developing new cloud applications. The existing applications have great value for an enterprise, often representing billions of dollars of investment and business intelligence. As the cost of the IT infrastructure increasing, enterprises see a real opportunity to reduce the cost and gain flexibility by using cloud. Critical to achieving the goal is an effective transformation of existing applications to cloud. There is science and engineering to the process. In this course, students will learn the science behind the process and the engineering of successful transformation. In contrast to the incremental, organic, and routine changes to enterprise applications, transformation activities are planned, highly coordinated, and involve large-scale changes. Students will learn about the drivers for transformation, the economics of migration to cloud, the systematic approaches to transformations, and the steps involved in the process. IBM researchers, who are experts in the transformation methodology and cloud computing, will teach the course. A key component of the course is the set of three homework assignments which provide the student an opportunity to practice the transformation steps exemplifying the conceptual and practical challenges involved.
CSCI-GA.3033-011
(25448) Special Topics: Predictive Analytics Anasse Bari
Office Hours W 5:10-7:00PM CIWW 201

Predictive analytics is the art and science of extracting useful information from historical data and present data for the purpose of predicting future trends. In this course, students will have an introduction to the phases of the analytics lifecycle and a basic understanding of a variety of tools and machine learning techniques to analyze data to discover forward insights. Several techniques will be introduced; including data pre-processing techniques, data clustering algorithms, data classification algorithms, association rules data mining algorithms, recommender systems, etc.

Applications from bio-informatics, social networks analytics, and text mining will be covered. Highlights from industrial use cases will be covered to demonstrate how Predictive Analytics relates to improving business performance and impacting better decisions. This is an introductory course that will provide students with basic skills of the new generation of data scientists that will allow them to structure, analyze and derive useful insights from data that could help make better decisions.
CSCI-GA.3033-012
(25426) Special Topics: Computational Machine Learning Zaid Harchaoui
Office Hours W 7:10-9:00PM CIWW 201

Machine learning studies the question "how can we build computer programs that automatically improve their performance through experience?" This course primarily focuses on computationally-efficient machine learning, i.e. theoretically-grounded methods and algorithms to analyse large amounts of data with successful performance. Such large scales arise in applications such as information retrieval, social recommendation, computer vision, genomics, astrophysics. The course will cover both the theoretical and methodological aspects, and a variety of real-world applications.

Prerequisites: Students are required to have taken Fundamental Algorithms (CSCI-GA.1170) and Mathematical Techniques for Computer Science Applications (CSCI-GA.1180). Previous hands-on experience dealing with data for analysis/prediction/modelling (eg speech processing, computer vision, natural language processing, modelling of observational data, etc.) is recommended.
CSCI-GA.3205-001
(17240) Applied Cryptography & Network Security Zvi Kedem
Office Hours M 7:10-9:00PM CIWW 312
This course first introduces the fundamental mathematical cryptographic algorithms, focusing on those that are used in current systems. To the extent feasible, the mathematical properties of the cryptographic algorithms are justified, using elementary mathematical tools. Second, actual security mechanisms and protocols, mainly those employed for network traffic that rely on the previously introduced cryptographic algorithms, are presented. The topics covered include introduction to basic number-theoretical properties, public/private and symmetric key systems, secure hash functions, digital signature standards, digital certificates, IP security, e-mail security, Web security, and stand-alone computer privacy and security tools.
CSCI-GA.3210-001
MATH-GA 2170-001
(1862) Introduction To Cryptography Oded Regev
Office Hours M 11:00-12:50PM CIWW 517
The primary focus of this course is on definitions and constructions of various cryptographic objects, such as pseudorandom generators, encryption schemes, digital signature schemes, message authentication codes, block ciphers, and others, time permitting. The class tries to understand what security properties are desirable in such objects, how to properly define these properties, and how to design objects that satisfy them. Once a good definition is established for a particular object, the emphasis will be on constructing examples that provably satisfy the definition. Thus, a main prerequisite of this course is mathematical maturity and a certain comfort level with proofs. Secondary topics, covered only briefly, are current cryptographic practice and the history of cryptography and cryptanalysis.

Prerequisites: Strong mathematical background
CSCI-GA.3250-001
(2227) Honors Operating Systems Michael Walfish
Office Hours TR 3:30-4:45PM CIWW 312
Operating-system structure. Processes. Process synchronization. Language mechanisms for concurrency. Deadlocks: modeling, prevention, avoidance, and recovery. Memory management. File-system interface. Secondary storage. Distributed systems: layered system design, managing distributed processes, distributed shared memory, fault-tolerance. CPU scheduling. Queuing and performance: analysis of single M/M/1 queue and others. Protection and security. Advanced security concepts: threat monitoring, encryption, and public keys.

Prerequisites: Permission of the instructor for master’s students
CSCI-GA.3520-001
(1177) Honors Analysis of Algorithms Victor Shoup
Office Hours MW 3:30-4:45PM CIWW 102
Design of algorithms and data structures. Review of searching, sorting, and fundamental graph algorithms. In-depth analysis of algorithmic complexity, including advanced topics on recurrence equations and NP-complete problems. Advanced topics on lower bounds, randomized algorithms, amortized algorithms, and data structure design as applied to union-find, pattern matching, polynomial arithmetic, network flow, and matching.

Prerequisites: Permission of the instructor for master’s students.
CSCI-GA.3812-001
(1178) Information Technology Projects * Jean-Claude Franchitti
Office Hours M 6:10-9:10PM CIWW 317

This is a capstone course that connects students directly with real-world information technology problems. The goal of this course is to teach the skills needed for success in real-world information technology via a combination of classroom lectures and practical experience with large projects that have been specified by local “clients.” The typical clients are primarily companies, but can also be government agencies or nonprofit organizations. Each project lasts for the entire semester and is designed to involve the full software project life cycle. Examples of such projects are development of software to solve a business problem, including specifying requirements, writing and testing prototype code, and writing a final report; and evaluation of commercial software to be purchased to address a business problem, including gathering requirements, designing an architecture to connect the new software with existing systems, and assessing the suitability of available software products.

Prerequisites: For MS in IS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms and two of the following three courses: CSCI-GA 2262 Data Communications & Networks; CSCI-GA 2250 Operating Systems; CSCI-GA 2433 Database Systems. For MS in CS students: Successful completion of CSCI-GA 1170 Fundamental Algorithms, CSCI-GA 2110 Programming Languages, and CSCI-GA 2250 Operating Systems. PERMISSION OF THE DEPARTMENT REQUIRED.
CSCI-GA.3813-001
(1179) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-002
(1180) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-003
(1181) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-004
(1182) Adv Lab MS * Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-005
(1183) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-006
(1184) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-007
(1185) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3813-008
(1186) Adv Lab PhD ** Faculty -

Large-scale programming project or research in cooperation with a faculty member.

Prerequisites: Permission of the faculty project supervisor and the Director of Graduate Studies.
CSCI-GA.3840-001
(1187) Master's Thesis Research * Faculty -

Prerequisites: Approval of a faculty adviser and the Director of Graduate Studies for the M.S. programs.
CSCI-GA.3850-001
(1188) PhD Seminar: Cryptography** Yevgeniy Dodis
Office Hours T 12:30-3:15PM CIWW 412
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3850-004
(1189) PhD Seminar: Formal Methods** Thomas Wies
Office Hours R 11:00-12:30PM CIWW 412
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3850-006
(2230) PhD Seminar: Machine Learning Mehryar Mohri
Office Hours M 3:45-5:00PM CIWW 1314
Graduate seminars serve as loosely structured forums for exploring research topics from broad areas of computer science. They are designed to foster dialogue by bringing together faculty and students from a given area and to encourage the exchange of ideas. As such, they bridge the gap between more structured course offerings and informal research meetings. Subject matter varies by section.

Prerequisites: Permission of the instructor.
CSCI-GA.3860-001
(1190) PhD Thesis Research ** Faculty -

Prerequisites: Permission of the thesis adviser or director of graduate studies for the Ph.D. program.

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Indicates controlled enrollment (permission number required for registration). Contact your program advisor.
**

Indicates controlled enrollment (permission number required for registration). Contact Santiago Pizzini (pizzini@cs.nyu.edu).
***

Indicates controlled enrollment (permission number required for registration). Contact the instructor.

Classroom Locations

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