Head of Department: Professor Alexander A. Shvartsman
Department Office: Room 250, Information Technologies Engineering Building
Computer Science and Engineering courses were formerly offered under the CS department abbreviation using the same course numbers.
Three credits. Two class periods and two 1-hour program design periods. Not open for credit to students who have passed CSE 110C or CSE 1010 or CSE 1100. Students who anticipate extensive study or use of computers in their future work should take CSE 1100–1102 rather than this course.
Introduction to computer applications in the humanities, social sciences, business, and other fields. Influence of the computer on modern society and technology. Elements of computer usage in the solution of numeric and non-numeric problems including introduction to programming methods.
Three credits. Two 1-hour lectures and one 2-hour laboratory. Not open for credit to students who have passed CSE 110 or 1100.
Introduction to computing logic, algorithmic thinking, computing processes, a programming language and computing environment. Knowledge obtained in this course enables use of the computer as an instrument to solve computing problems. Representative problems from science, mathematics, and engineering will be solved.
Two credits. Two class periods of lecture and one 1-hour of laboratory period per week. No previous programming experience required. Not open for credit to students who have passed CSE 110C.
Problem solving with the computer, basics of data representation and computer organization, procedural and object-oriented programming in a modern language including control structures, functions and parameter passing, one and two dimensional arrays, numerical error and basic numerical methods. Examples taken from various disciplines. Programming projects required. Intellectual property issues discussed.
Principles of object oriented programming including classes, polymorphism, encapsulation and information hiding, and inheritance. Principles of object oriented design. Program debugging and documentation techniques. Implementation and simple analysis of algorithms for sorting and searching. Event-driven programming and the use of libraries for user interfaces. Introduction to computer history. Programming assignments.
Introduction to research in computational biology through lectures, computer lab exercises, and mentored research projects. Topics include gene and genome structure, gene regulation, mechanisms of inheritance, biological databases, sequence alignment, motif finding, human genetics, forensic genetics, stem cell development, comparative genomics, early evolution, and modeling complex systems. CA 3.
Three credits. Two 1-hour lectures and one 2-hour laboratory. Prerequisite: CSE 1010.
An introduction to computer programming in a structured programming language including fundamental elements of program design and analysis. Data and functional abstraction as tools for constructing correct, efficient, and intelligible programs for a variety of common computing problems.
Introduction to fundamental data structures and algorithms. The emphasis is on understanding how to efficiently implement different data structures, communicate clearly about design decisions, and understand the relationships among implementations, design decisions, and the four pillars of object-oriented programming: abstraction, encapsulation, inheritance, and polymorphism.
Three credits. Three class periods of lecture. Prerequisite: CSE 1102. Students who have passed CSE 124C will receive only 2 credits for this course.
Fundamental concepts of data structures and the algorithms that proceed from them. Implementation and use of linked lists, stacks, queues, trees, priority queues, heaps and graphs. Emphasis on recursion, abstract data types, object oriented design, and associated algorithms and complexity issues. Design using specifications and requirements. Basic computer organizations, including memory organizations and allocations issues. Programming assignments.
Software engineering concepts including the software life cycle and other software-development process models. Specification techniques, design methodologies, performance analysis, and verification techniques. Team-oriented software design and development, and project management techniques. Use of appropriate design and debugging tools for a modern programming language. Homework and laboratory projects that emphasize design and the use/features of a modern programming language.
Four credits. Three class periods and one 2-hour laboratory period. Prerequisite: CSE 1010 or 1100 or 1102 and secondary school physics or PHYS 1010 or 1501; ENGL 1010 or 1011 or 2011. Not open to students who have passed CSE 207.
Representation of digital information. Analysis, design, and evaluation of combinational and sequential logic circuits. Debugging techniques. Use of computer facilities for circuit simulation, CAD, and report preparation and presentation. Introduction to structure and operation of digital computers. Design projects. Written reports with revisions are required for each project.
Structure and operation of digital systems and computers. Fundamentals of digital logic. Machine organization, control and data paths, instruction sets, and addressing modes. Hardwired and microprogrammed control. Memory systems organization. Discussion of alternative architectures such as RISC, CISC, and various parallel architectures.
Three credits. Prerequisite: CSE 1102.
Mathematical methods for characterizing and analyzing discrete systems. Modern algebraic concepts, logic theory, set theory, grammars and formal languages, and graph theory. Application to the analysis of computer systems and computational structures.
The global and societal impact of computer science and engineering decisions, professional and ethical responsibility.
Three credits. Prerequisite: CSE 2102; open only to Computer Science and Engineering and Computer Science majors.
Study of areas in which computer science interacts with ethical issues, and issues of public policy. Topics of professional growth, development, and responsibility. Practice in the analysis of complex issues brought about by modern technology.
Introduction to system-level programming with an emphasis on C programming, process management, and small scale concurrency with multi-threaded programming. Special attention will be devoted to proficiency with memory management and debugging facilities both in a sequential and parallel setting.
Two credits. Prerequisite or corequisite: CSE 3100; open only to students in the School of Engineering and declared Computer Science minors.
Leverages existing knowledge of C and covers all the essential capabilities of the most recent C++ standard, illustrating their specificities as well as how the language can be used to model object-oriented implementation of a number of classic problems.
Introduction to computer networks and data communications. Network types, components and topology, protocol architecture, routing algorithms, and performance. Case studies including LAN and other architectures.
Design and evaluation of control and data structures for digital systems. Hardware design languages are used to describe and design alternative register transfer level architectures and control units with a micro-programming emphasis. Consideration of computer architecture, memories, digital interfacing timing and synchronization, and microprocessor systems.
Digital designing with PLA and FPGA, A/D and D/A conversion, floating point processing, ALU design, synchronous and asynchronous controllers, control path; bus master; bus slave; memory interface; I/O interface; logic circuits analysis, testing, and troubleshooting; PBC; design and manufacturing.
Introduction to computer security and the design of secure computer systems. Introduction to applied cryptography, including basic elements of symmetric-key and public-key ciphers, authentication, and key exchange. Security issues in operating systems, software, databases, and networks. Attacks and countermeasures. Ethical, legal and business aspects.
Design and analysis of efficient computer algorithms. Algorithm design techniques, including divide-and-conquer, depth-first search, and greedy approaches. Worst-case and average-case analysis. Models of computation. NP-complete problems
Formal models of computation, such as finite state automata, pushdown automata, and Turing machines, and their corresponding elements in formal languages (regular, context-free, recursively enumerable). The complexity hierarchy. Church’s thesis and undecidability. NP completeness. Theoretical basis of design and compiler construction.
Introduction to the probabilistic techniques which can be used to represent random processes in computer systems. Markov processes, generating functions and their application to performance analysis. Models which can be used to describe the probabilistic performance of digital systems.
Three credits. Three 1-hour lectures and one 1-hour laboratory period. Prerequisite: CSE 2050 or 2100. Cannot be taken after CSE 4302 or 4901. This course and CSE 2304 may not both be taken for credit. This course and CSE 243 may not both be taken for credit.
Structure and operation of digital systems and computers. Machine organization, control and data paths, instruction sets, and addressing modes. Integer and floating-point arithmetic, the memory hierarchy, the I/O subsystem. Assembly language and basic program organization, interrupts, I/O, and memory allocation.
(Also offered as BME 4800.) Three credits. Prerequisite: BIOL 1107, CSE 1100 or 1010 or 1729 and either STAT 3025Q or STAT 3345Q; open only to Biomedical Engineering majors, others by instructor consent.
Fundamental mathematical models and computational techniques in bioinformatics. Exact and approximate string matching, suffix trees, pairwise and multiple sequence alignment, Markov chains and hidden Markov models. Applications to sequence analysis, gene finding, database search, phylogenetic tree reconstruction.
(Also offered as ECE 3431.) Three credits. Prerequisite: CSE 1100 or 1010 or 1729 and MATH 2110Q and MATH 2410Q; open only to students in the School of Engineering. Prerequisite or corequisite: MATH 2210Q.
Introduction to the numerical algorithms fundamental to scientific computation. Equation solving, function approximation, integration, difference and differential equations, special computer techniques. Emphasis is placed on efficient use of computers to optimize speed and accuracy in numerical computations. Extensive digital computer usage for algorithm verification.
Computational methods for genomic data analysis. Topics covered include statistical modeling of biological sequences, probabilistic models of DNA and protein evolution, expectation maximization and Gibbs sampling algorithms, genomic sequence variation, and applications in genomics and genetic epidemiology.
Credits by arrangement. Prerequisites and recommended preparation vary. Open only to students in the School of Engineering. With a change in content, this course may be repeated for credit.
Classroom course in special topics as announced in advance for each semester.
Credits by arrangement, not to exceed 4 in any semester. Prerequisite: Consent of instructor and department head; open only to students in the School of Engineering.
Exposes the student to management principles and practices and the knowledge and skills necessary to develop an education project and to perform a research project.
Introduction to the formal definition of programming language syntax and semantics. Design and realization of programming language processing systems such as assemblers, compilers, and interpreters.
Three credits. Prerequisite: CSE 3502; open only to students in the School of Engineering.
The study of programming language features and programming paradigms. Data types, control, run-time environments, and semantics. Examples of procedural, functional, logical, and object-oriented programming. Features used for parallel and distributed processing. Classic and current programming languages and environments.
Introduction to the theory, design, and implementation of software systems to support the management of computing resources. Topics include the synchronization of concurrent processes, memory management, processor management, scheduling, device management, file systems, and protection.
Three credits. Three 1-hour lectures. Prerequisite: CSE 2300W; CSE 2304 or 3666; open only to students in the School of Engineering. This course and CSE 243 may not both be taken for credit. Cannot be taken after CSE 4901.
Organization and architecture of modern computer systems. Emphasis is on alternatives and advances to the basic Von Neumann architecture: topics such as pipelining, memory hierarchy and management, multiprocessor and alternative architectures, reconfigurable hardware, and other techniques for performance enhancement.
Three credits. Prerequisite: CSE 3400; open only to students in the School of Engineering and declared Computer Science minors.
Computer security and the design of secure systems. Cryptographic tools. Operating system security and access control. Network, software and database security. Randomness generation. Malicious software. Anonymity and privacy. Various attacks and countermeasures. Ethical, legal and business aspects.
The principle and practices of how to provide secure communication between computer systems. Includes protection techniques at the physical, network, transport layers, and major approaches in Internet security. This class will cover how cryptography is applied in network security. Topics include: denial-of-service, DNS, BGP, IPSec, SSL/TLS, Authentication/Kerberos, VPNs, PKI, firewalls, intrusion detection/prevention systems, blockchains, and wireless security.
Introduction to parallel systems. Fundamentals of the theory of parallel systems. Models of parallel machines. Limitations of parallel systems. Paradigmatic algorithms. Vectorization. Arithmetic structures. Classical parallel architectures.
Focuses on basic concepts of data science and big data analytics. Different algorithmic techniques employed to process data will be discussed. Specific topics include: Parallel and out-of-core algorithms and data structures, rules mining, clustering algorithms, text mining, string algorithms, data reduction techniques, and learning algorithms. Applications such as motif search, k-locus association, k-mer counting, error correction, sequence assembly, genotype-phenotype correlations, etc. will be investigated.
Three credits. Prerequisite: CSE 3500; open only to students in the School of Engineering.
Fundamentals of data base design and data indexing techniques. Hierarchical, network, and relational data models. Data base design theory. Query languages, their implementation and optimization. Data base security and concurrent data base operations.
An introduction to the fundamentals of modern cryptography focusing on development of secure cryptographic tools based on hard computational problems. Topics include one-way functions, pseudorandom generators, encryption, digital signatures, and protocols.
Representation of two- and three-dimensional data, internal representation of data structures, transformations, mapping of data to graphics screen, graphics hardware. Programming projects are assigned.
Three credits. Prerequisite: CSE 3500; open only to students in the School of Engineering.
An extension of sorting, searching, selection, and graph algorithms to geometric problems. This includes algorithms and data structures for constructing geometric objects, computing geometric properties, and answering geometric queries as well as techniques for the analysis of their correctness and complexity.
Three credits. Prerequisite: CSE 3500; open only to students in the School of Engineering.
Design and implementation of intelligent systems, in areas such as natural language processing, expert reasoning, planning, robotics, problem solving and learning. Students will design their own versions of “classic” AI problems, and complete one substantial design project.
Introduction to computer security and the design of secure systems. Cryptographic tools. Operating system security and access control. Network, software and database security. Randomness generation. Malicious software. Digital rights management, anonymity and privacy. Various attacks and countermeasures. Ethical, legal and business aspects.
Introduction to the basic concepts, challenges, and methods for designing networked embedded systems. Examines related hardware, software, and system-level design. Hardware topics include various design alternatives (such as microcontrollers, digital signal processors (DSP), and field-programmable gate array (FPGA)) in resource-constrained environments. Software issues include operating systems, programming languages, program verification and analysis. System-level topics include autonomous wireless sensor network design, power and resource management, security and privacy.
Three credits. Prerequisite: CSE 2102; instructor and department head consent; open only to students in the School of Engineering. May be taken twice for credit.
Experimental design project undertaken by the student by special arrangement with a faculty member of the Department of Computer Science and Engineering.
Three credits. One 4-hour laboratory period. Prerequisites and recommended preparation vary. Open only to students in the School of Engineering. With a change in content, this course may be repeated for credit.
Design and implementation of complex software and/or hardware systems to solve problems posed by either student groups or the instructor.
Software laboratory that explores selected issues in networking and distributed systems. Topics include: Berkeley sockets; TCP and IP; atm apis; latency and bandwidth; performance models; performance evaluation of different network fabrics; MPI; simple CORBA; performance characteristics of MPI, Java, RMI, and CORBA; implementation and evaluation of a client-server system.
The first semester of the required two-semester major design experience. Working on a team, students will propose, design, produce, and evaluate a software and/or hardware system. Will culminate in the delivery of the design, analysis, and initial working system, to be used as a basis for CSE 4940, formal public presentation, and written documentation. Oral and written progress reports are required.
Three credits. Prerequisite: CSE 4939W; open only to Computer Science and Engineering and Computer Science majors.
The second semester of the required year long major design experience. The semester will be spent developing, testing, and evaluating the software and/or hardware system begun in CSE 4939W. The project will culminate in the delivery of a working system and will include a formal, public presentation, and written documentation. Oral and written progress reports are required.
Discussion of the design process; project statement, specification, project planning scheduling and division of responsibility, ethics in engineering design, safety, environmental considerations, economic constraints, liability, manufacturing, and marketing. Projects are carried out using a team-based approach. Selection and analysis of a design project to be undertaken in CSE 4951/ECE 4902 is carried out. Written progress reports, a proposal, an interim report, a final report, and oral presentations are required.
Design of a device, circuit, system, process, or algorithm. Team solution to an engineering design problem as formulated in CSE 4950/ECE 4901, from first concepts through evaluation and documentation. Written progress reports, a final report, and oral presentations are required.
Three credits. Hours by arrangement. Prerequisite: Senior standing in Computer Science, Computer Science and Engineering, or Computer Engineering. Requires consent of instructor and Department Head. Not limited to honors students.
Students are expected to choose an advisor and seek approval of a thesis topic by the time of registration. Students will author a formal thesis based on independent research conducted under the advisor supervision. Thesis proposal and final thesis must follow the guidelines developed by the department.