UB - University at Buffalo, The State University of New York

CSE Home > Graduate Academics > Graduate Courses > Courses

CSE Graduate Course Offerings

Entire Catalog

The CSE graduate program has offered these courses over the last five years. Many courses are offered every year, but some are offered irregularly. Click the "More »" links to see more details and histories of course offerings.

Semester

CSE 501 Introduction to Graduate Study in Computer Science & Engineering

This course gives necessary information about graduate studies in CSE for incoming Ph.D. students. Registration and attendance are required for all new Ph.D. students. Topics include: academic integrity, the nature of research, good teaching and TA skills, resources available for graduate study in computer science.

MS students should not take CSE 501.

CSE 503 Computer Science for Non-Majors I

This course introduces students to algorithm design and implementation in a modern, high-level, programming language (currently, Java). It emphasizes problem-solving by abstraction. There will also be a brief coverage of the social and ethical aspects of computing. Topics include data types, variables, expressions, basic imperative programming techniques including assignment, input/output, subprograms, parameters, selection, iteration, Boolean type, and expressions, and the use of aggregate data structures including arrays and records. Students will also have an introduction to the basics of abstract data types and object-oriented design, as well as the mathematics of computer science such as Boolean algebra, basic number theory, etc.

May not be counted toward the 30 hours for the M.S. or the 72 hours for the Ph.D.

CSE 504 Computer Science for Non-Majors II

This course is a continuation of CSE 503, in which heavy emphasis is placed on abstract data types (ADTs) and object-oriented methodology, where the student will be expected not only to understand ADTs, but also to design and implement robust ADTs using a modern, object-oriented, programming language. Topics such as encapsulation, polymorphism, templates, and inheritance will be emphasized. Essential topics to be integrated in this framework include the use of recursion; pointers; dynamic memory management; linked structures including linked lists, binary trees, stacks, queues, and other advanced data structures; and algorithms, including advanced searching and sorting algorithms. The analysis of algorithm complexity ("big O" notation) will be introduced.

May not be counted toward the 30 hours for the M.S. or the 72 hours for the Ph.D.

CSE 505 Fundamentals of Programming Languages

This course surveys concepts, constructs, and foundations of a variety of programming languages. Main topics are lambda-calculi, type systems, data and procedural abstraction, programming paradigms (object-oriented, functional, and logic), and formal semantics (denotational, operational and axiomatic). Languages of interest include C, C++, Java, Lisp, ML, Smalltalk, and Prolog. Programming projects are designed to deepen understanding of languages. Language-specific details are covered in the recitations which are closely coordinated with the lectures.

CSE 506 Emerging Comp Architecture

Course description is currently unavailable.

CSE 507 SOA And Web Services

May not be counted toward the 30 hours for the M.S. or the 72 hours for the Ph.D.

CSE 510 Special Topics

This course is used for newly-designed courses which are being developed by faculty members, usually in a new area of research.

CSE 512 Operating Systems Internals

This course uses an operating system (such as UNIX) as an example to teach the internal workings of Operating Systems. The material presented is more practical than the other Operating Systems related classes. The laboratory component of this course provides programming projects involving modifications to an operating system kernel (such as UNIX) on computers dedicated to use for this course. Topics covered include building the Operating System kernel, the system call interface, process management, kernel services provided for processes, the I/O system, the internal workings of the file system, device drivers, and the kernel support of Interprocess Communications.

See:http://www.dcsl.buffalo.edu

CSE 521 Introduction to Operating Systems

Concepts of operating systems described in terms of function, structure, and implementation; particular emphasis on multiprogramming. Example concepts are: concurrent programming, virtual memory, scheduling policies for CPU and secondary storage, deadlocks, file systems, and protection. Concepts will be illustrated with examples from existing operating systems.

CSE 522 Software Requirements Engineering

Success of the software engineering paradigm is predicated on the development of a quality software requirements document. This course reviews the software life cycle and the role of the software requirements document in the software engineering process. The components of a software requirements document are defined, presented, reviewed and critiqued in class. Students are provided the opportunity to engineer a requirements document for a system defined in class or an actual system required by business, industry or government. (Offered irregularly.)

CSE 524 Realtime & Embedded Systems

Course description is currently unavailable.

CSE 530 Computer Communications

An introduction to communication networks for computer and telecommunication applications. Review of stochastic processes and introductory queuing theory. Local area networks (such as Ethernet, Token Ring, and FDDI), wide area networks (such as SNA, and Internet), ISDN and SONET are considered. Focus is on the data link control, network and transport layers of the OSI protocol suite.

CSE 531 Analysis of Algorithms

The design and analysis of algorithms. Time and space complexity of algorithms. Big-O notation. Analysis of recursive procedures. Algorithms for solving problems from graph theory, computational geometry. NP-completeness. Approximation algorithms. Parallel algorithms, etc.

CSE 534 Multimedia Systems

This is an overview course covering the various aspects of Multimedia Systems. Topics include video representation, compression and transmission, multimedia databases, synchronization, multimedia networks and operating systems.

See:http://www.cse.buffalo.edu/courses/cse534

CSE 535 Information Retrieval

Course description is currently unavailable.

See:http://www.cedar.buffalo.edu/~rohini/CSE535/

CSE 536 Computational Biology

This course is designed for CSE and Bioinformatics graduate students. Computational Biology studies the problems arising from Biology using algorithmic techniques. Typical problems include: sequencing and alignment of DNA and protein sequences; construction and comparison of evolutionary trees. These problems are of central importance in Biology. The course provides insights that will help students gain a comprehensive understanding of computational problems in Biology, and techniques for designing efficient algorithms for solving these problems. Prerequisite: Basic understanding of programming, or molecular biology and genetics.

CSE 542 Software Engineering Concepts

This course introduces the terminology and concepts of software engineering. Following a discussion of how software engineering evolved in response to early practices of the computer industry, the concepts of well-engineered software, the software process and the management process model are presented. Additional topics include software requirements definition, software design, verification and validation, and software management. Graduate students are required to investigate and report on a topic relevant to the course. (Same as ECE 442).

CSE 543 Introduction to Language Processors

Theory, design, and implementation of a translator for a high-level programming language will be discussed. Topics include: lexical analysis, context-free grammars, parsing,LR-parsers, type checking, storage allocation, code generation and optimization, and error recovery; compiler construction tools LEX and YACC. These topics will be supported by programming projects. (Offered irregularly.)

CSE 545 Error Correcting Codes: Combinatorics, Algorithms, and Applications

Error correcting codes (or just codes) are systematic ways of introducing redundancy into data so that the original information can be recovered even when the data is corrupted. Codes are used ubiquitously in communication systems and data storage. The study of error correcting codes (or coding theory) started with the seminal works of Shannon and Hamming in the late 1940s and has been an active cross-disciplinary research area since then. This course will discuss the theoretical aspects of codes and will focus mostly on the worst-case noise model pioneered by Hamming. However, we will discuss quite a few results on the stochastic noise model pioneered by Shannon. The course will roughly cover three parts: (i) combinatorial aspects of codes, i.e. the limit of what can and cannot be achieved with codes; (ii) computationally efficient algorithms for using codes; and (ii) application of codes in theoretical computer science. Major developments in coding theory since the 1990s will be emphasized.

CSE 547 High Performance Computing 1

The first semester of a two-semester course sequence that will introduce students to the fundamental concepts of scientific computing, with particular attention given to algorithms that are well-suited to high performance computer architectures. The first semester will concentrate on computational linear algebra, including iterative and direct methods for solving linear systems and for eigenvalue problems, and the use of BLAS and other public domain libraries.

CSE 548 High Perform Computing 2

Course description is currently unavailable.

CSE 552 VLSI (Very Large Scale Integration) Testing

A sequel to CSE 497/597, Introduction to VLSI Electronics, the project work for this course includes testing of the chip fabricated in 497/597. Lectures include MOS transistor fundamentals, automatic test pattern generation, design for testability, built-in test techniques, design simulation at switch and gate levels, fault simulation at behavioral levels, software tools and equipment for testing, semi-custom VLSI chips, wafer scale integration, and analog circuit test and diagnosis.

CSE 555 Introduction to Pattern Recognition

Foundations of pattern recognition algorithms and machines, including statistical and structural methods. Data structures for pattern representation, feature discovery and selection, classification vs. description, parametric and non-parametric classification, supervised and unsupervised learning, use of contextual evidence, clustering, recognition with strings, and small sample-size problems. programming projects.

See:http://www.cse.buffalo.edu/~jcorso/t/CSE555

CSE 556 Topics in Visualization

Introduction to relevant topics and concepts in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concept, animation techniques, pattern analysis, and computational methods. Tools and techniques for practical visualization. Elements of related fields including computer graphics, human perception, computer vision, imaging science, multimedia, human‐computer interaction, computational science, and information theory. Covers examples from a variety of scientific, medical, interactive multimedia, and artistic applications. Hands‐on exercises and projects.

CSE 560 Data Models and Query Languages

The course focuses on the issues of data models and query languages that are relevant for building present-day database applications. The following topics are addressed: Entity-Relationship data model, relational data model, relational query languages, object data models, constraints and triggers, XML and Web databases, the basics of indexing and query optimization.

CSE 561 Design Perf Wireless Chan

Course description is currently unavailable.

CSE 562 Database Systems

The basic design principles of systems managing very large databases will be discussed. Topics will include: database design, data models, integrity constraints, query languages, database file organization, indexing, query processing and optimization, transaction processing. Students will implement one or more modules of a prototype database system.

CSE 563 Knowledge Representation

This course is an introduction to the issues and techniques of representing knowledge and belief in a computer system. Of course, a representation is useless unless it can be used for some purpose. The main purpose of items of knowledge and belief is reasoning about and with them. Thus, the field is often called "Knowledge Representation and Reasoning", or "KRR". It is our belief that formal logic provides the basic foundation to KRR. So this course may be considered a course in computational logic. However, there are many systems of logic. The most well-known logics were designed to form the foundations of mathematics, rather than the foundations of human-like representation and reasoning. So this course examines several systems of logic, how they are defined, how reasoning procedures can be implemented for them, and how they can be used for human-like reasoning problems. This course provides a basic grounding in KRR for people interested in: Artificial Intelligence; Cognitive Science; Computational Linguistics; Database Systems; Logic Programming; Philosophy of Mind and of Language; and applications areas that employ formal representations of ontologies.

CSE 564 Game Theory & Computer Networks

Course description is currently unavailable.

CSE 565 Computer Security

This course is intended to give an in-depth understanding of computer system security. Security encomp asses hacker challenges, malicious break-ins and insider threats. Topics include: Basic Encryption and Decryption - Rivest-Shamir-Adelman (RSA) Encryption, El Gamal and Digital Signature Algorithms, Hash Algorithms, Kerberos; Program Security - Virus, Trojan Horse, Malicious Code, Covert Channels; Design of Trusted OS; Network Security - Firewalls, Tripwires; Intrusion Detection - Audit Trail-Based Schemes, Concurrent Intrusion Detection.

CSE 566 Wireless Networks Security

Wireless networking has become increasingly popular these days. Wireless networks have adopted many security mechanisms from the wired world. But wireless networks face larger amount of inherent limitations than the wired world. Threats like intercepting and unauthorized access to wireless traffic are common. More mature solutions to the security problems demand the need of understanding the current technologies and the security flaws. This course covers the basics of wireless networks security from both modes of operation -- the infrastructure mode and the ad hoc mode.

CSE 567 Computational Linguistics

Introduction to computational models of understanding natural languages. Syntactic and semantic parsing, generation, knowledge-representation techniques.

CSE 573 Introduction to Computer Vision and Image Processing

This course is an introduction to those areas of Artificial Intelligence that deal with fundamental issues and techniques of computer vision and image processing. The emphasis is on physical, mathematical, and information-processing aspects of the vision. Topics to be covered include image formation, edge detection and segmentation, convolution, image enhancement techniques, extraction of features such as color, texture, and shape, object detection, 3-D vision, and computer vision system architectures and applications.

CSE 574 Introduction to Machine Learning

Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning.

See:http://www.cedar.buffalo.edu/~srihari/CSE574/index.html

CSE 575 Introduction to Cognitive Science

An introduction to cognitive science, an interdisciplinary approach to the computational study of human cognition. Methodology, assumptions, and research problems of cognitive science and such cognitive-science disciplines as anthropology, artificial intelligence, linguistics, neurosciences, philosophy, psychology, etc. Emphasis will be placed on joint efforts of these disciplines in investigating issues in the nature of the mind, intelligence, language, perception, memory, etc. Students will be encouraged to participate in colloquia sponsored by the Center for Cognitive Science.

CSE 584 Philosophy Of Computer Science

Course description is currently unavailable.

CSE 586 Large-Scale Distributed Systems

This course addresses some of the fundamental challenges in the design, implementation and deployment of large scale distributed systems including connection establishment, event handling, interprocess communication, storage management, static and dynamic component configuration, concurrency and synchronization. It will also cover issues related to distributed objects such as mobility, security, naming, location, evolution, autonomy and negotiations. Possible solutions will be analyzed and expressed using objects, processes, services, components and frameworks at various levels of granularity. This course focuses on practical solutions using the latest server-side and middleware technology.

CSE 587 Data Intensive Computing

Course description is currently unavailable.

CSE 589 Modern Networking Concepts

This course introduces basic elements of modern computer and telecommunication networks. a hybrid five-layer reference model resembling the popular TCP/IP model and the OSI's seven- layer model will be discussed. In each layer, the state-of-the-art hardware and software technologies are introduced. These include, for example, fiber-optic and mobile/cellular communications in the physical layer; wavelength/time division multiple access protocols in the data link layer; traffic shaping and policing in the network layer; ATM adaptation layer protocols in the transport layer, and finally, network security and multimedia communications in the application layer.

CSE 590 Computer Architecture

This course will provide an in-depth understanding of the inner workings of modern digital computer systems and trade-offs present at the hardware-software interface. Topics include: computer abstractions and technology, cost and performance analysis, instruction set architecture, computer arithmetic, datapath and controller design, pipelining, memory systems, input-output systems, and interrupts and exceptions. Projects requiring the use of software tools like the SPIM simulator for MIPS R2000/R3000 RISC processors and the Verilog hardware description language will be given to help crystallize concepts presented in class.

CSE 591 System On Chip

Course description is currently unavailable.

CSE 593 Introduction to VLSI Electronics

Very large scale integration (VLSI) design principles, CMOS gates, layout, simulation, CAD tools, semi-custom integrated circuit chip design, project required.

CSE 596 Introduction to the Theory of Computation

Turing machines, RAMs, decidable and computably enumerable sets, partial computable functions; Church-Turing thesis; undecidable problems, diagonalization, Recursion Theorem, Rice's Theorem, Kleene Normal Form Theorem. Time and space complexity bounds, complexity classes, Savitch's Theorem, NL = coNL. NP-completeness, Cook-Levin Theorem, polynomial hierarchy, complete problems for other complexity classes.

See:http://www.cse.buffalo.edu/courses/cse596

CSE 598 Graduate Internship

For use by graduate students requiring academic credit for practical training.

CSE 601 Data Mining and Bioinformatics

This course focuses on data mining and data warehousing techniques and their applications in bioinformatics. The course explains the broad scope of bioinformatics, discusses the theory and practice of computational methods and software, and provides insight that will help students gain a comprehensive understanding of the bioinformatics field. Major topics include biological data storage, retrieval, and modeling; data mining literature for biology; distributed and parallel biological databases; visualization tools for biological data analysis; statistical methods for gene expression analysis; molecular sequence analysis; protein-protein interaction analysis; identification and classification of genes and regulatory elements; and biological information integration, interoperability, and bio-ontology.

CSE 603 Parallel & Distributed Processing

This course is meant for anyone interested in the design and use of advanced computer systems of today and the future. The course will cover principles of modern parallel and distributed systems embodied in several current systems. There will be programming assignments involving the use of these parallel systems for application problem solving using one or more parallel programming environments (PVM, MPI, Java). Course coverage includes: introduction to parallel computing, basic communication operations, performance and scalability analysis of parallel systems, parallel algorithms for dense matrix computations, sorting, and searching, load balancing, applications of parallel processing in different application domains, architectures of shared-memory multiprocessors and scalable multiprocessors, interconnection network design, and fault tolerance in parallel systems.

CSE 605 Advanced Concepts in Programming Languages

This course will discuss advanced concepts in the design and implementation of programming languages. It is the second in a two-course graduate-level sequence on programming languages - the first being CSE 505. Advanced language concepts will be drawn from type systems, object-oriented, functional, and logic programming languages. the course will also cover integration of two or more programming paradigms as well as implementation issues underlying these paradigms. In-depth understanding of these concepts will be gained through programming projects.

CSE 606 Parallel Architecture

The organization of parallel computer systems. Different parallel architectures, such as SIMD and MIMD parallel computers, shared-memory and distributed-memory computers, as well as dataflow architectures, will be discussed. Concepts will be illustrated by discussing some existing systems.

CSE 620 Advanced Networking Concepts

Course description is currently unavailable.

CSE 622 Advanced Computer Systems

Course description is currently unavailable.

CSE 626 Data Mining

Introduction to data mining and knowledge discovery in databases: the identification of valid, novel, potentially useful, and ultimately understandable patterns in large data repositories. Studies its principles, algorithms, implementations, and applications. (Offered irregularly.)

See:http://www.cedar.buffalo.edu/~srihari/CSE626/

CSE 630 Adv Wireless Netw Concept

Course description is currently unavailable.

CSE 632 Analysis of Algorithms II

This course is a continuation of CSE 531. Algorithms for solving problems in graph theory, computational geometry; approximation algorithms etc.

CSE 633 Parallel Algorithms

The course will focus on the design, implementation, and analysis of a parallel solution to an interesting problem on a state-of-the-art high-end computing system. The students will learn how to program contemporary shared-memory, distributed-memory, and GPGPU-based high-end computing systems. The course will also cover the design and analysis of fundamental parallel algorithms. Time and space complexity of solutions to problems from areas that include computational geometry, image analysis, and graph theory will be considered. Architectures include the PRAM, mesh, pyramid, mesh-of-trees, and hypercube.

CSE 634 Advanced Topics in Multimedia Systems

An introduction to 3D imaging and graphics, image understanding paradigms, mathematical morphology, object representation and manipulation techniques using hierarchical and heterarchical representations. Specialized architectures for 3D image processing.

CSE 635 Advanced Info Retrieval

Course description is currently unavailable.

CSE 636 Data Integration

This course surveys selected theoretical and practical issues arising in data integration. Data integration has been recognized as a research topic of great practical importance. The availability of integrated data from multiple, independent, heterogenous, data sources is crucial for many applications. Data integration requires combining and matching information in different sources and resolving a variety of conflicts. XML is becoming a de facto data-integration standard. With the number of data sources growing very quickly, data integration is bound to become even more important in the future.

See:http://www.cse.buffalo.edu/~chomicki/cse636-f12.html

CSE 642 Techniques of Artificial Intelligence

A second graduate course in AI covering programming techniques for AI and surveying AI topics not covered in other graduate-level courses. Topics will vary according to instructor and student interests. (Offered irregularly.)

CSE 646 Wireless Networking & Mobile Computing

In Part I, we will discuss issues in point-to-point communication where the communicating devices are directly connected. In Part II, we assume that the communicating devices may or may not be directly connected and are part of a network of devices. We will discuss architectural issues in this context, as well as issues pertaining to routing data, congestion control, communication protocols involved, etc. In Part III, we assume that application programs running on various devices are communicating among themselves. Protocol design and architectural issues will be the primary focus of this part. (Offered irregularly.)

CSE 663 Advanced Topics in Knowledge Representation

A second graduate course in knowledge representation and reasoning covering such topics as automated theorem proving, semantic network implementation, etc., and surveying knowledge representation and reasoning topics not covered in other graduate-level courses. Topics will vary according to instructor and student interests.

CSE 664 Applied Cryptography and Computer Security

As a crucial part of computer security, cryptography has become increasingly important. However, due to the mathematically complex nature of cryptography, misunderstandings, misuses, and abuses of cryptographic techniques are very common. There is a huge gap between the theory of cryptography and its application. In this course, we study cryptography in a rigorous manner. Our focus is correct application of cryptographic techniques in practical scenarios, rather than the mathematical foundations of these techniques. We stress careful design and analysis of secure systems using existing building blocks. Topics to be covered include private communications (DES, AES, ECB, CBC, RSA, Rabin), identification and authentication techniques (passwords, certificates, SSH, Kerberos), secure protocols (digital cash, Internet auction, electronic voting).

See:http://www.cse.buffalo.edu/~szhong/courses/664

CSE 666 Biometrics & Image Analysis

Survey of techniques for computer processing and analysis of images produced by modern scanning devices. Representation of 2- and 3-dimensional images, orthogonal transformations, boundary detection, segmentation, computational geometry and topology, shape characterization, time-varying images, description of spatial organization. Topics will be illustrated by programming projects in computer vision and computed tomography.

See:http://cubs.buffalo.edu/govind/cse666_2009.php

CSE 667 Advanced Computational Linguistics

This course aims to provide students with an overview of the key areas which make up the field called Computational Linguistics, an understanding of the major challenges of the field as well as the major application areas for language processing techniques, and the skills to implement fundamental language processing algorithms.

This course expands upon the content covered in CSE/LIN 567.

CSE 668 Animate Vision Principles for 3D Image Sequences

Conventional approaches to computer vision based on complete reconstruction of the contents of arbitrary single images have met with limited success. More recently, elements of biological vision systems such as goal-directed sensing behaviors, reliance on image sequences and motion, and the importance of stereopsis have been applied to machine vision systems with considerable success. In this course the design of computer vision systems in light of animate vision principles is developed.

CSE 671 Secure Wireless Sensor Networks

Course description is currently unavailable.

CSE 672 Bayesian Vision

The course takes an in-depth look at various Bayesian methods in computer and medical vision. Through the language of Bayesian inference, the course will present a coherent view of the approaches to various key problems such as detecting objects in images, segmenting object boundaries, and recognizing objects. The course is roughly partitioned into two halves: modeling and inference. In the first half, it will cover both classical models such as weak membrane models and Markov random fields as well as more recent models such as conditional random fields, latent Dirichlet allocation, and topic models. In the second half, it will focus on inference algorithms. Methods include PDE boundary evolution algorithms such as region competition, discrete optimization methods such as graph-cuts and graph-shifts, and stochastic optimization methods such as data-driven Markov chain Monte Carlo. An emphasis will be placed on both the theoretical aspects of this field as well as the practical application of the models and inference algorithms.

CSE 673 Computational Vision

Examines the task of making computers ``see,'' including: image formation, low-level processes for extracting the basic properties of images, image analysis, computational theories of human/machine perception, geometric reconstruction, scene analysis, and model-based vision systems.

CSE 674 Advanced Machine Learning

Machine Learning techniques are a systematic approach to designing information processing systems, such as those for classification and regression, wherein significant uncertainty exists in the data. In the machine learning approach, input-output relationships are learnt from representative samples. This course will build upon basic techniques covered in the pre-requisite courses and cover advanced topics to include: graphical models (including Bayesian networks), mixture models and expectation maximization, approximate inference, sampling methods, continuous latent variables, sequential data, and combining models.

See:http://www.cedar.buffalo.edu/~srihari/CSE574

CSE 678 Face and Gesture Recognition

Face and gesture recognition is an advanced technology that utilizes the intrinsic physiological or behavioral traits of individuals for machine-based automatic and reliable identification. It attracts much attention due to the increasing demand for the security, privacy, and health care-related human-centered applications. This course covers the state-of-the-art face and gesture recognition technologies, including face/human detection, face/body tracking, face recognition, head/body pose estimation, expression recognition, body language recognition, gait analysis, hand/body/eye gesture, action/activity analysis, and so forth. Multimodal, multimodality, and soft-biometric frameworks will also be discussed. Fundamental knowledge covered by the course includes pattern recognition, feature extraction, classifier, probabilistic models, image processing, and machine learning. Tools and techniques for practical face and gesture recognition system design as well as hands-on exercises and projects will be provided.

CSE 680 Computational Geometry

This course introduces students to the essentials of Computational Geometry and presents an in-depth study of the fundamental techniques used in this field. Topics to be covered include geometric searching, convex hulls, proximity computations, intersections, graph drawing, and other special topics. Applications to problems from other fields such as Computer Graphics, Computer Vision, Software Engineering, Databases, Robotics, and Geographical Information Systems will also be discussed. (Formerly, CSE 581.)

CSE 681 Formal Languages 1

Languages and their representation; regular, context-free, context-sensitive, and type-0 grammars; characterization by automata used as recognizers; complexity issues in formal languages; decision problems; LR(k) grammars; biologically motivated formal language theory. (Offered irregularly.)

CSE 691 Advanced VLSI Design

Advanced techniques in VLSI design, design for performance, physical design automation, synthesis, analog and mixed-mode design techniques, field programmable gate arrays, technology and architectural issues in VLSI, special purpose VLSI design.

See:http://www.cse.buffalo.edu/~rsridhar/cse691/

CSE 694 Topics in Algorithms - Probabilistic Analysis and Randomized Algorithms

Probabilistic analysis and randomized algorithms have become an indispensible tool in virtually all areas of Computer Science, ranging from combinatorial optimization, machine learning, data streaming, approximation algorithms analysis and designs, complexity theory, coding theory, to communication networks and secured protocols. This course has two major objectives: (a) it introduces key concepts, tools and techniques from probability theory which are often employed in solving many Computer Science problems, and (b) it presents many examples from three major themes: computational learning theory, randomized/probabilistic algorithms, and combinatorial constructions and existential proofs.

In addition to the probabilistic paradigm, students are expected to gain substantial discrete mathematics problem solving skills essential for computer scientists and engineers.

This course was formerly called CSE 594.

CSE 696 Computational Complexity

Nonuniform classes: Circuit classes and relations to uniform classes; parallel complexity: Alternating Turing machines, uniformity conditions, NC; Probabilistic classes; Toda's Theorem, interactive protocols.