Course Descriptions (GSAS Bulletin)
(2015 - 2017)
Preparatory Accelerated Courses
Intensive Introduction to Graduate Study in Computer
Science I (PAC I)
CSCI-GA 1133 Korth. 4 points. 2015-16, 2016-17
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.
Intensive Introduction to Graduate Study in Computer
Science II (PAC II)
CSCI-GA 1144 Prerequisite: CSCI-GA 1133 or departmental permission. Zahran. 4 points. 2015-16, 2016-17
This course builds directly on the foundation developed in PAC I, covering the essentials of computer organization through the study of assembly language programming and C, as well as introducing the students to the analysis of algorithms. Topics include: (1) Assembly language programming for the Intel chip family, emphasizing computer organization, the Intel x86 instruction set, the logic of machine addressing, registers and the system stack. (2) Programming in the C language, a general-purpose programming language which also has low-level features for systems programming. (3) An introduction to algorithms, including searching, sorting, graph algorithms and asymptotic complexity. Examples and assignments reinforce and refine those first seen in PAC I and often connect directly to topics in the core computer science graduate courses, such as Programming Languages, Fundamental Algorithms, and Operating Systems.
Algorithms and Theoretical Computer Science
CSCI-GA 1170 Spencer, Yap, Dodis, Siegel. 3 points. 2015-16, 2016-17
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.
Mathematical Techniques for Computer Science Applications
CSCI-GA 1180 Davis, Kedem,Wright. 3 points. 2015-16, 2016-17
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.
Elements of Discrete Mathematics
CSCI-GA 2340 Prerequisites: May not be taken by students who have received a grade of B or better in CSCI-GA 1170. Staff. 3 points. 2015-16, 2016-17
Introduction to the central mathematical concepts that arise in computer science. Emphasis is on proof and abstraction. Topics include proof techniques; combinatorics; sets, functions, and relations; discrete structures; order of magnitude analysis; formal logic; formal languages and automata.
CSCI-GA 3230 Spencer. 3 points. 2015-16, 2016-17
This course covers numerous topics related to random graphs, including generalized randomized structures, random processes, probabilistic methods and Erdös Magic. Also covered are branching processes, phase transitions for large random evolutions, derandomization via conditional expectations and semidefinite programming derandomization techniques. Algorithms, probability and discrete mathematics all appear, but concepts will be defined from scratch. Emphasis will be on methods of asymptotic calculation.
Honors Analysis of Algorithms
CSCI-GA 3520 Prerequisites: Permission of the instructor for master’s students. Yap, Siegel. 4 points. 2015-16, 2016-17
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.
Programming Languages and Compilers
CSCI-GA 2110 Goldberg. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2130 Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250. Grimm. 3 points. 2015-16, 2016-17
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.
Honors Programming Languages
CSCI-GA 3110 Prerequisite: permission of the instructor for master’s students. Cousot. 4 points. 2015-16, 2016-17
The course will introduce a panorama of programming languages concepts underlying the main programming language paradigms (such as imperative, functional, object-oriented, logic, concurrent, and scripting languages) and present in detail the formal methods (code semantics, specification, and verification) used in modern high quality assurance tools for software safety and security. A programming project (design and implementation of an interpreter/compiler for an dynamic object-oriented mini-language) will be programmed in OCaml, a multiparadigm language introduced at the beginning of the course.
Honors Compilers and Computer Languages
CSCI-GA 3130 Prerequisites: permission of the instructor for master’s students. Staff. 4 points. 2015-16, 2016-17
Lexical scanning and scanner generation from regular expressions; LL, LR, and universal parser generation from context-free grammars; syntax-directed translation and attribute grammars; type and general semantic analysis; code generation, peephole optimization, and register allocation; and global program analysis and optimization. Provides experience using a variety of advanced language systems and experimental system prototypes.
Open Source Tools
CSCI-GA 2246 Prerequisites: An understanding of modern operating systems and a working knowledge of a programming language, such as C, C++ or Java. Staff. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2250 Grimm, Gottlieb. 3 points. 2015-16, 2016-17
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#.
Networks and Distributed Systems
CSCI-GA 2620 Prerequisites: A course in undergraduate networks and/or operating systems; programming experience in C/C++ or Java is helpful for the final project. Subramanian. 3 points. 2015-16, 2016-17
A course in computer networks and large-scale distributed systems. Teaches the design and implementation techniques essential for engineering both robust networks and Internet-scale distributed systems. The goal is to guide students so they can initiate and critique research ideas in networks and distributed systems and implement and evaluate a working system that can handle a real-world workload. Topics include routing protocols, network congestion control, wireless networking, peer-to-peer systems, overlay networks and applications, distributed storage systems, and network security.
Data Communications and Networks
CSCI-GA 2262 Prerequisite: CSCI-GA 2250 or an undergraduate networking course. Franchitti. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2433 Kedem, Franchitti. 3 points. 2015-16, 2016-17
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.
Advanced Database Systems
CSCI-GA 2434 Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250. Shasha. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2440 Prerequisites: CSCI-GA 1170, CSCI-GA 2110, and CSCI-GA 2250. Franchitti. 3 points. 2015-16, 2016-17
This is a capstone course focusing on large-scale software development. This course presents modern software engineering techniques and examines the software life cycle, including software specification, design, implementation, testing, and maintenance. Object-oriented design methods are also considered. Software engineering projects involve creation of a large-scale software system and require some or all of the following elements: formation of a small team, project proposal, literature review, interim report, project presentation, and final report.
CSCI-GA 2631 Prerequisites: CSCI-GA 1170 and CSCI-GA 2250. Staff. 3 points. 2015-16, 2016-17
Concepts underlying distributed systems: synchronization, communication, fault tolerance, and performance. Examined from three points of view: (1) problems, appropriate assumptions, and algorithmic solutions; (2) linguistic constructs; and (3) some typical systems.
Honors Operating Systems
CSCI-GA 3250 Prerequisites: permission of the instructor for master’s students. Grimm, Walfish 4 points. 2015-16, 2016-17
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.
Graphics and Vision
CSCI-GA 2270 Prerequisite: CSCI-GA 1170. Perlin. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2271 Prerequisite: CSCI-GA 1170. Geiger. 3 points. 2015-16, 2016-17
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.
CSCI-GA 2560 Geiger, Davis. 3 points. 2015-16, 2016-17
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 2565 Prerequisites: undergraduate course in linear algebra and strong programming skills for implementation of algorithms studied in class. Recommended: knowledge of vector calculus, elementary statistics, and probability theory. Staff. 3 points. 2015-16, 2016-17
This course covers a wide variety of topics in machine learning, pattern recognition, statistical modeling, and neural computation. The course covers the mathematical methods and theoretical aspects but primarily focuses on algorithmic and practical issues.
Foundations of Machine Learning
CSCI-GA 2566 Mohri. 3 points. 2015-16, 2016-17
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).
Web Search Engines
CSCI-GA 2580 Prerequisites: recommend CSCI-GA 1180. Davis. 3 points. 2015-16, 2016-17
Discusses the design of general and specialized Web search engines and the extraction of information from the results of Web search engines. Topics include Web crawlers, database design, query language, relevance ranking, document similarity and clustering, the “invisible” Web, specialized search engines, evaluation, natural language processing, data mining applied to the Web, and multimedia retrieval.
CSCI-GA 2585 Prerequisites: Familiarity with basics in linear algebra, probability and analysis of algorithms. No specific knowledge about signal processing or other engineering material is required. Mohri. 3 points. 2015-16, 2016-17
This course gives a computer science presentation of automatic speech recognition, the problem of transcribing accurately spoken utterances, and presents algorithms for creating large-scale speech recognition systems. The algorithms and techniques presented are now used in most research and industrial systems. The objective of the course is not only to familiarize students with particular algorithms used in speech recognition, but also to use that as a basis to explore general concepts of text and speech, as well as machine learning algorithms relevant to a variety of other areas in computer science. The course will make use of several software libraries and will study recent research and publications in this area.
Natural Language Processing
CSCI-GA 2590 Grishman. 3 points. 2015-16, 2016-17
Survey of the techniques used for processing natural language. Syntactic analysis: major syntactic structures of English; alternative formalisms for natural language grammar; parsing algorithms; analyzing coordinate conjunction; parsing with graded acceptability. Semantic analysis: meaning representations; analysis of quantificational structure; semantic constraints; anaphora resolution; analysis of sentence fragments. Analysis of discourse and dialog. Text generation. Students get some experience using a natural language parser and a natural language query interface. Brief weekly written assignments and a term project involving a mixture of library research and programming (mostly in LISP). This course reviews some of the recent work in this area, including the following topics: statistical models of language; entropy and perplexity; n-gram word models: acquisition and smoothing, part-of-speech models; finite state models: hidden Markov models, acquisition procedures; probabilistic context-free grammars: acquisition procedures; semantic models: word-concurrence, word classes; applications in information retrieval, speech recognition, and machine translation.
Heuristic Problem Solving
CSCI-GA 2965 Prerequisites: CSCI-GA 1170 and an ability to prototype algorithms rapidly. Shasha. 3 points. 2015-16, 2016-17
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.
Logic and Verification
Logic in Computer Science
CSCI-GA 2390 Prerequisites: strong mathematical background and instructor permission for master’s students. Barrett, Mishra. 3 points. 2015-16, 2016-17
A beginning graduate-level course in mathematical logic with motivation provided by applications in computer science. There are no formal prerequisites, but the pace of the class requires that students can cope with a significant level of mathematical sophistication. Topics include propositional and first-order logic; soundness, completeness, and compactness of first-order logic; first-order theories; undecidability and Godel’s incompleteness theorem; and an introduction to other logics such as second-order and temporal logic.
Applied Cryptography and Network Security
CSCI-GA 3205 Kedem. 3 points. 2015-16, 2016-17
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.
Introduction to Cryptography
CSCI-GA 3210 Prerequisites: strong mathematical background. Regev, Dodis. 3 points. 2015-16, 2016-17
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.
CSCI-GA 3220 Prerequisite: CSCI-GA 3210. Dodis. 3 points. 2015-16, 2016-17
Basics of computational number theory for cryptography. Identification protocols. Digital signatures. Public-key encryption. Additional selected topics.
Computation for Science and Society
Financial Software Projects
CSCI-GA 2180 Prerequisites: It is assumed that the students can code in C++. No prior experience in the financial sector domain is required. Staff. 3 points. 2015-16, 2016-17
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.
Projects, Seminars, and Research
Information Technology Projects
CSCI-GA 3812 Prerequisites: Permission of the instructor. Franchitti, Korth. 3 points. 2015-16, 2016-17
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.
CSCI-GA 3813 Prerequisites: permission of the faculty project supervisor and the Director of Graduate Studies for the M.S. Programs. Staff. 1-3 points per term for master’s students, 1-12 points per term for Ph.D. students. 2015-16, 2016-17
Large-scale programming project or research in cooperation with a faculty member or a professional internship
Master’s Thesis Research
CSCI-GA 3840 Prerequisite: approval of a faculty adviser and the Director of Graduate Studies for the M.S. programs. Staff. 3-6 points. 2015-16, 2016-17
Ph.D. Research Seminar
CSCI-GA 3850 Prerequisite: permission of the instructor. Staff. 1 point. 2015-16, 2016-17
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.
Ph.D. Thesis Research
CSCI-GA 3860 Prerequisite: permission of the thesis adviser or director of graduate studies for the Ph.D. program. Staff. 1-12 points per term. 2015-16, 2016-17
Special Topics in Computer
CSCI-GA 3033 Prerequisites vary according to topic. Staff. 3 points. 2015-16, 2016-17
Topics vary each semester. Recent offerings:
Algorithmic and Economic aspects
of the Internet
Cloud Computing: Concepts & Practice
Computational Number Theory & Algebra
Graphics Processing Units (GPUs): Architecture & Programming
Music Software Projects
Principles of Software Security
Production Quality Software
Programming Paradigms for Concurrency
Social Multiplayer Games
Realtime & Big Data Analytics
Statistical Natural Language Processing