UB - University at Buffalo, The State University of New York Computer Science and Engineering
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CSE Graduate Course Offerings

Entire Catalog

The CSE Graduate Program has offered these courses over the last ten 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.

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 Computer Architecture

Course description is currently unavailable.

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 508 Programming With Python

Course description is currently unavailable.

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.

http://www.dcsl.buffalo.edu

CSE 517 Intro To R Programming

Course description is currently unavailable.

CSE 520 Embedded Architectures

Course description is currently unavailable.

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 Object Oriented Analysis, Design, and Implementation

This course will cover the systematic design of object-oriented programs, including software requirements, high-level design using the Unified Modeling Language (UML), and use-case driven coding in a modern object-oriented language. The course will also cover design patterns, code contracts, distributed objects and interoperability, web services, as well as static- and dynamic-typed object-oriented languages.

CSE 522 Object Oriented Analysis, Design, and Implementation

This course will cover the systematic design of object-oriented programs, including software requirements, high-level design using the Unified Modeling Language (UML), and use-case driven coding in a modern object-oriented language. The course will also cover design patterns, code contracts, distributed objects and interoperability, web services, as well as static- and dynamic-typed object-oriented languages.

CSE 524 Realtime & Embedded Systems

Course description is currently unavailable.

CSE 527 Embedded Processors

Course description is currently unavailable.

CSE 527 Modern Computer Systems

Computer system architecture, architecture support of compilers, computing system processor design of memory and peripherals, operating system structures and hardware interfacing. C and assembly language programming on SPARC RISC processors. Standard calling conventions and stack frame usage. Operating system services. Directly programmed interfaces, interrupt services interfaces and data acquisition systems. Custom interface design for a standard bus.

CSE 529 Algs For Modern Computer Syst

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.

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

CSE 535 Information Retrieval

Course description is currently unavailable.

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 541 Programing Multi/core Arch

Course description is currently unavailable.

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 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.

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 and Performance Analysis of Computer Systems

Introduces performance analysis techniques for the application of high performance computer system design. Advanced topics in computer architecture and computer communications are examined via simulation and analytical modeling. Develops mathematical tools based on stochastic processes, discrete mathematics, combinatorics and queuing theory to study the behavior of computer systems.

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.

http://mjolnir.cse.buffalo.edu/teaching/cse-562/

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 568 Robotics Algorithms

Course description is currently unavailable.

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.

http://www.cse.buffalo.edu/courses/cse573

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.

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 581 Computational Geometry

This course number has been changed to CSE 680.

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 587 Information Structures

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.

http://www.cse.buffalo.edu/~lusu/cse4589/

CSE 590 Computer Architecture

Course description is currently unavailable.

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.

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/bioinformatic

Course description is currently unavailable.

CSE 601 Data Mining and Bioinformatics

This course focuses on the fundamental techniques in data mining, including data warehousing, frequent pattern mining, clustering, classification, anomaly detection and feature selection methods. Specifically, we will cover the following topics: Data warehousing--model design; Frequent pattern mining--association rules mining; Clustering--partition-based, hierarchical-based, density-based approaches, spectral clustering; Feature selection--dimensionality reduction; Classification--decision-tree, Bayesian, rule-based, SVM, ensemble methods; Anomaly detection--statistics-based, density-based, clustering-based; Evaluation and validation of data mining results; Correlation analysis--metrics and analysis; Graph and network mining; Visualization of patterns--mapping between high-dimensional data and low-dimensional data; and Multi-source information integration. To demonstrate how data mining techniques are applied to various domains, we focus on the software systems design of bioinformatics, discussing the applications of data warehousing and data mining in biological and biomedical related fields. The class discusses various software systems and provides insight that will help students gain a comprehensive understanding of the bioinformatics field. Projects will be designed based on these applications.

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 604 Fault Tolerant Computing

Basic frameworks of fault tolerance, dynamic and hybrid redundancy. Practical fault tolerant systems. Intermittent fault models, concurrent testing, built-in testing, recovery block scheme and rollback recovery. Fault tolerant multiprocessors. Performance evaluation of fault tolerant 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 610 Special Topics

The course will be focused on sensing on two main platforms:

You will have ample access to hardware for the projects.

The primary objective of the course will be demonstratable research projects in sensing on one of these two platforms. Research groups will be 1-3 students depending on enrollment. We will identify the project in the first two weeks of class, and spend the rest of the semester hacking on the individual projects. Project will form a significant portion of the grade.

Course structure:

  • First third of the class will be lectures on modern algorithms for visual sensing and their applications. During this time, we will have three-four assignments to get you acclimatized with the algorithms
  • Rest of the class will be readings in recent research. All students will require writing short critiques of the readings weekly. Each student will be assigned a topic when he/she will lead the discussion in one of the classes.

Course Objective:

  • Serious implementation project in sensing systems. I expect the work to be something that can be submitted to a workshop - or with work through summer/fall, submitted to a research conference.
  • Introduction to visual sensing algorithms
  • Introduction to research methodology. This includes reading research papers, writing critiques, research presentation, and executing research through the project
  • Help masters students identify interesting research projects in AI/Systems

http://www.cse.buffalo.edu/~kdantu/cse610/

CSE 620 Advanced Networking Concepts

Course description is currently unavailable.

CSE 622 Advanced Computer Systems

This is an advanced graduate course that looks at design and implementation of large software systems. The current incarnation of the course is focused on Android Open Source Project. Classes will consist of three main components---readings in modern computer systems from recent research literature, class lectures on Android framework and Linux kernel, and a significant project implemented by groups of three to four students. The course will also consist of four assignments in the first third of the course which will get the students acquainted with Android internals. The main focus of the course is a term project that involves significant implementation, likely modification and/or addition to the Android kernel or framework. The projects are intended to have a research flavor, and help both masters and PhD students to get involved in a research project. Projects will be assigned at the start of class, and bi-weekly meetings will project groups will be held to ensure regular progress. Students are expected to do a mid-term presentation mid-way through the course with the project goals, implementation outline, and a list of research contributions. The last day of class will have an open demo/poster session for the department to show off the projects along with presentations to present the conclusion.

http://www.cse.buffalo.edu/~stevko/courses/cse622/

CSE 622 Computer Systems Theory

Theoretical results in performance evaluation of computer systems introduced through synthetic and analytic models of system structure; techniques for verifying properties of concurrent processes; issues in multiprogramming operating system mechanism such as naming and binding, protection, reliability, and recovery.

CSE 622 Advanced Computer Systems

This is an advanced graduate course that looks at design and implementation of large software systems. The current incarnation of the course is focused on Android Open Source Project. Classes will consist of three main components---readings in modern computer systems from recent research literature, class lectures on Android framework and Linux kernel, and a significant project implemented by groups of three to four students. The course will also consist of four assignments in the first third of the course which will get the students acquainted with Android internals. The main focus of the course is a term project that involves significant implementation, likely modification and/or addition to the Android kernel or framework. The projects are intended to have a research flavor, and help both masters and PhD students to get involved in a research project. Projects will be assigned at the start of class, and bi-weekly meetings will project groups will be held to ensure regular progress. Students are expected to do a mid-term presentation mid-way through the course with the project goals, implementation outline, and a list of research contributions. The last day of class will have an open demo/poster session for the department to show off the projects along with presentations to present the conclusion.

http://www.cse.buffalo.edu/~stevko/courses/cse622/

CSE 622 Computer Systems Theory

Theoretical results in performance evaluation of computer systems introduced through synthetic and analytic models of system structure; techniques for verifying properties of concurrent processes; issues in multiprogramming operating system mechanism such as naming and binding, protection, reliability, and recovery.

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.)

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 635 Multimedia Information Retrieval

This course will cover both traditional, text-based information retrieval (IR) techniques, as well as newer techniques for multimedia information retrieval. Although text-based IR is a well-established field, the area of multimedia IR is an emerging discipline. Techniques for automatically analyzing/extracting content from other modalities such as images, video and speech will be explored. In each case, we will discuss content-analysis techniques as well as indexing and retrieval techniques will be examined. Various case studies will be presented. The latter part of the course will focus on techniques for combining information obtained from various media sources in both the indexing and retrieval stages. This includes multimodal query formulation/ decomposition, relevance judgment/feedback, evaluation techniques, as well as convenient user interfaces for multimedia querying.

CSE 636 Data Integration

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.

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 Ntwkg & Mob Comp

Course description is currently unavailable.

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 651 Emerging App In Embed Sys

Course description is currently unavailable.

CSE 651 Semantics of Programming Languages

This is an advanced course in the semantics of programming languages and the mathematical theory of program correctness. Various program semantics, notably operational and denotational, are studied and compared. Then formal systems for a number of programming languages are studied and, on the basis of the semantics, their soundness and completeness proved. (Offered irregularly.)

CSE 655 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, the use of contextual evidence, clustering, and small sample-size problems. Programming projects will include handling of pictorial and textual patterns.

CSE 662 Languages and Runtimes for Big Data

Coursework consists of lectures and a multi-stage final project. Students are expected to attend all lectures. Projects may be performed individually or in groups. Projects will be evaluated in three stages through code deliverables, reports, and group meetings with either or both of the instructors. During these meetings, instructors will question the entire group extensively about the group’s report, deliverables, and any related tools and technology. After the taking the course, students should be able to: • Design domain specific query languages, by first developing an understanding the com- mon tropes of a target domain, exploring ways of allowing users to efficiently express those tropes, and developing ways of mapping the resulting programs to an efficient evaluation strategy. • Identify concurrency challenges in data-intensive computing tasks, and address them through locking, code associativity, and correctness analysis. • Understand a variety of index data structures, as well as their application and use in data management systems for high velocity, volume, veracity, and/or variety data. • Understand query and program compilation techniques, including the design of in- termediate representations, subexpression equivalence, cost estimation, and the construction of target-representation code.

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).

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.

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

CSE 666 Image Analysis

Course description is currently unavailable.

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 667 Advanced Topics in Computational Linguistics

A second graduate course in computational linguistics covering such topics as parsing, computational semantics, discourse processing, etc., and surveying computational-linguistics topics not covered in other graduate-level courses. Topics will vary according to instructor and student interests.

CSE 668 Advanced Robotics

Course description is currently unavailable.

CSE 668 Advanced Robotics

This class focuses on robotic algorithms that allow mobile robots to operate successfully in unknown and unstructured environments. Currently many of the most successful algorithms utilize probabilistic approaches that explicitly encode uncertainty, use these representations to assimilate new sensor data, and base their decisions both on the content and quality of information. The material covered in this class includes the most prevalent and successful models and techniques and will give you the necessary tools to incorporate current results, e.g. SLAM implementations and sampling based planners, into your own robots.

CSE 668 Advanced Robotics

Course description is currently unavailable.

CSE 668 Advanced Robotics

This class focuses on robotic algorithms that allow mobile robots to operate successfully in unknown and unstructured environments. Currently many of the most successful algorithms utilize probabilistic approaches that explicitly encode uncertainty, use these representations to assimilate new sensor data, and base their decisions both on the content and quality of information. The material covered in this class includes the most prevalent and successful models and techniques and will give you the necessary tools to incorporate current results, e.g. SLAM implementations and sampling based planners, into your own robots.

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.

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

CSE 675 Stochastic Simulation & Inference

An emerging application for the stochastic process is analyzing complex natural and social systems using data collected from sensor networks and the World Wide Web that tracks the temporal evolution of those systems. By applying the stochastic process to data, we can improve commuter traffic, tune organizational efficiency, and control the spread of epidemics. In this course, we will learn how to construct and simulate the Markov processes that are the common abstractions of many dynamic systems, and learn the mathematical properties of these processes. Overall, this hands-on course trains students to apply stochastic-process thinking to the temporal dynamics of complex systems, as captured by data.

CSE 675 Stochastic Simul & Inference

Course description is currently unavailable.

CSE 675 Stochastic Simulation & Inference

An emerging application for the stochastic process is analyzing complex natural and social systems using data collected from sensor networks and the World Wide Web that tracks the temporal evolution of those systems. By applying the stochastic process to data, we can improve commuter traffic, tune organizational efficiency, and control the spread of epidemics. In this course, we will learn how to construct and simulate the Markov processes that are the common abstractions of many dynamic systems, and learn the mathematical properties of these processes. Overall, this hands-on course trains students to apply stochastic-process thinking to the temporal dynamics of complex systems, as captured by data.

CSE 675 Stochastic Simul. & Inference

Course description is currently unavailable.

CSE 676 Deep Learning

Course description is currently unavailable.

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.

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.

CSE 696 Computational Complexity

Course description is currently unavailable.

CSE 700 Independent Study

Course description is currently unavailable.

CSE 701 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 702 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 703 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 704 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 705 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 706 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 707 Robotics Seminar

Course description is currently unavailable.

CSE 708 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 709 Seminars

Course description is currently unavailable.

CSE 709 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 709 Seminar

Course description is currently unavailable.

CSE 709 Seminar

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 710 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 711 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 712 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 713 Seminars

Course description is currently unavailable.

CSE 714 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 715 Seminars

Course description is currently unavailable.

CSE 716 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 717 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 718 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 719 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 720 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 721 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 722 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 723 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 725 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 726 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 727 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 728 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 730 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 734 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 735 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 736 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 737 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 740 Seminars

Course description is currently unavailable.

CSE 741 Seminars

This course is a seminar. Seminar topics change every semester. Please refer to seminar instance topics and descriptions by semester.

CSE 745 Seminars

Course description is currently unavailable.

CSE 746 Seminars

Course description is currently unavailable.

CSE 749 Seminars

Course description is currently unavailable.

CSE 799 Supervised Research

Course description is currently unavailable.

CSE 800 Thesis Guidance

Course description is currently unavailable.

Seminars

These seminars are coming soon. You may still be able to register for them.

CSE has presented these seminars since Spring 2000. Seminars are unique events, so don't plan on any of these particular seminar topics being offered again. To learn more about the content discussed in a past seminar, contact the faculty member who taught it.

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  • CSE Demo Day

    RESEARCH SPOTLIGHT

    CSE Demo Day

    CSE students gather in the Davis Atrium to demonstrate their semesterly capstone projects and current research projects.

  • CSE Awards Reception

    Awards Reception

    CSE End of the Year Awards Reception

    We will be holding our End of the Year Awards Reception on December 16th at the Center for Tomorrow. All are welcome to attend! Please RSVP.

  • CSE Industrical Career Day

    Research Spotlight

    Industrial Career Day

    Industry Representatives will be making presentations and providing table displays. Food will be available at each session, and you will receive a free t-shirt for attending!
    Please RSVP!

  • CSE Alumni Student Reception

    Research Spotlight

    Alumni Student Reception

    Meet with current students, alumni, board members and company representatives. Come network, learn about our cutting edge research and outstanding academic programs, and meet our world-class faculty.

  • Tripathi and Grads image

    Research Spotlight

    Silicon Valley Alumni Reception

    Were you in Mountain View, CA on September 27th?

    Have a look at the photos of our alumni event!

  • Tripathi and Grads image

    Research Spotlight

    Presidential Welcome

    President Tripathi stops by to welcome our Fall 2016 incoming computer science grad students!

  • Save the Date image

    Research Spotlight

    Save the Date

    CSE's 50th anniversary gala celebration will be September 28—October 1, 2017. Will you help us plan it? Let us know which events you'd like to attend by taking this short survey.

  • Tech Savvy 11 image

    Research Spotlight

    Tech Savvy 11

    CSE ran a workshop at AAUW's Tech Savvy 11. Pictured (l-r) are Sada Haider, Lakshmi Ethiraj, Dr. Carl Alphonce, Aishani Bhalla, and Julia Cordani (not pictured: S. Doddi, W. Shi, M. Arnold, V. Kaplinsky, and R. Roberts).

  • Woman Eating Apple image

    Research Spotlight

    This necklace 'hears' what you eat

    Assistant Professor Wenyao Xu and his research partners at China's Northeastern University are developing Autodietary, a high-tech, food-tracking necklace. Read the full press release here.

  • Dimitrios Koutsonikolas image

    Research Spotlight

    Dr. Koutsonikolas wins NSF CAREER Award

    Assistant Professor Dimitrios Koutsonikolas won the NSF CAREER Award for his "CAREER: A Millimeter-Wave Multi-Layer WLAN Architecture for Multi-Gigabit, Always-On Connectivity".

  • Jing Gao image

    Research Spotlight

    Dr. Gao wins NSF CAREER Award

    Assistant Professor Jing Gao won the NSF CAREER Award for her proposal titled, "CAREER: Mining Reliable Information from Crowdsourced Data". The award is expected to total over $500K.

  • 2015 SEAS Faculty Awards image

    Research Spotlight

    2015 SEAS Faculty Award Winners (CSE)

    CSE faculty win awards at the 2015 SEAS Faculty Awards ceremony. Above: Qiao, Alphonce, Rudra, Ko. Below: Xu, Ren, Upadhyaya, Koutsonikolas, Gao.

  • 2015 SEAS Faculty Awards image

    Research Spotlight

    2015 SEAS Faculty Award Winners (CSE)

    Another shot of CSE faculty award winners at the 2015 SEAS Faculty Awards ceremony. Wu, Koutsonikolas, Xu, Ren, Upadhyaya, Rudra, Ko, Alphonce, Gao.

  • Qiao Chair image

    Research Spotlight

    Dr. Qiao Begins Term as CSE Chair

    CSE announces Chunming Qiao's appointment as CSE department chair in our 2015-2016 promotional postcard.

  • UBay image

    Research Spotlight

    International acclaim for Dr. Govindaraju

    UB Interim VP for Research and SUNY Distinguished Professor Venu Govindaraju receives international career honor for his research contributions.

  • UBay image

    Research Spotlight

    UBay 2015

    UB Interim VP for Research and SUNY Distinguished Professor Venu Govindaraju socializes with some of the 60 alums who attended the inaugural meeting of the UB Engineering Chapter of the Bay Area, UBay, in Palo Alto, CA.

  • Tech Savvy 10 image

    Research Spotlight

    Tech Savvy 10

    CSE students ran a workshop at AAUW's Tech Savvy 10. Pictured (l-r) are Savannah Towey, Meg Arnold, Sanjee Choudhery, Dr. Carl Alphonce, Bich Vu, and Christina Nowak (not pictured: Allison Palum).

  • CSRC Lab Image

    Research Spotlight

    Thanks to Vans Warped Tour

    Prof. Mike Buckley would like to thank Kevin Lyman, Kate Truscott, and the entire Vans Warped Tour 2014 for their generous donation to The Center for Socially Relevant Computing. More »

  • Chess Life Ken Regan Cover Image

    Research Spotlight

    Catching Chess Cheaters

    CSE associate professor, theoretician and International Master chessplayer Kenneth W. Regan is the subject of a technical and biographical profile in the June 2014 issue of Chess Life.

  • UBHacking 2013 Image

    Research Spotlight

    UBHacking 2014

    Students competed 'round the clock in UB Hacking 2014 over the weekend of April 5-6. Winners, projects, prizes, and sponsors are announced here.

  • Tech Savvy 9 image

    Research Spotlight

    Tech Savvy 9

    CSE students presented a session at UB's Tech Savvy 9. Pictured are Victoria Minorczyk, Bich Vu, Dr. Alphonce, Kayla Weixlmann, Christine Baxter, Amie Vuong (l-r).

  • Steve Ko NSF CAREER image

    Research Spotlight

    Congratulations, Dr. Ko!

    CSE Assistant Professor Steve Ko won the prestigious NSF CAREER Award for his research program titled, 'Systems for Transparency in Personal Devices and Services'.

  • Shambhu Upadhyaya CEISARE WGRZ Image

    Research Spotlight

    CEISARE in the News

    In two Buffalo NBC affiliate WGRZ Channel 2 News features, Shambhu Upadhyaya explains CEISARE's work training cyberwarriors and developing countermeasures to power facility cyberattacks.

  • Chunming Qiao Chancellor's Award Image

    Research Spotlight

    Congratulations, Dr. Qiao!

    Chunming Qiao receives 2013 SUNY Chancellor's Award for Excellence in Scholarship and Creative Activities. Dr. Qiao is joined onstage by President Satish Tripathi, Provost Charles Zukoski, and SEAS Dean Liesl Folks.

  • UBHacking 2013 Competition Winners Image

    Research Spotlight

    UBHacking 2013 Winners

    GamePute won first prize in a field of 30 teams at UBHacking 2013. Joe Peacock and Nick DiRienzo pose with GamePute team Scott Florentino, Andrew Wantuch, Jen Cordaro, and Andrew Kopanon.

  • SEAS Poster Competition Winners 2013 Image

    Research Spotlight

    CSE students win SEAS Grad Student Poster Competition

    Ankur Upadhyay, Daniel Bellinger, and Sumit Agarwal's work on Laasie won first prize in the 2013 SEAS Grad Poster Competition. They are advised by Luke Ziarek and Oliver Kennedy.

  • CSE Open House Image

    Research Spotlight

    Open House

    CSE undergrads demonstrate technology from the Center for Socially Relevant Computing (CSRC) to newly-accepted students and their parents at the CSE Open House on Saturday, March 23.

  • CSE Research Posters Image

    Research Spotlight

    Student Research Poster Session

    CSE graduate students and their faculty advisors present research posters in the Davis Atrium on March 7, 2013.

  • UB NCCC Image

    Research Spotlight

    Cyberdefenders

    CSE and Management students compete in the Northeast Collegiate Cyberdefense Competition (NCCC) on Saturday, January 19. UB advanced to the next round of competition, to be held at the University of Maine in March.

  • Cybersecurity Image

    Research Spotlight

    Cybersecurity

    UB's Center of Excellence in Information Systems, Assurance, Research, and Education (CEISARE) received a $1.6 million NSF grant to train students to protect the United States from cyberattacks. »

  • UB PhoneLab Image

    Research Spotlight

    UB PhoneLab

    Geoffrey Challen and Steven Ko are enlisting hundreds of students to build an unprecedented smartphone network to help scientists improve mobile computers and better understand how they're changing the world. »

  • UB CSE Research Image

    Research Spotlight

    Davis Hall dedication

    UB hosted Davis Hall's ribbon-cutting ceremony on May 12, 2012. Pictured (l to r) are: Kamlesh Tripathi, Margaret Jacobs, Jeremy Jacobs, Barbara Davis, Jack Davis, Rajan Batta, George Maziarz, and Harvey Stenger.

  • UB CSE Research Image

    Research Spotlight

    Davis Hall southwest elevation

    Davis Hall, CSE's new $75M headquarters, is designed to meet LEED "Gold" standards. The building is named for Barbara and Jack Davis. Davis is the founder of Akron-based I Squared R Element Co.

  • Ken Regan Image

    Research Spotlight

    Exposing chess cheats

    Theoretician and International Master chessplayer Kenneth W. Regan devises algorithms to detect chess cheating. The New York Times recently profiled his work .

  • UB CSE Research Image

    Research Spotlight

    Crystal clear

    Nobel Laureate Herbert Hauptman, a CSE affiliated professor, developed an algorithm for determining crystal structure. Computing in Science and Engineering Magazine named it one of the top 10 algorithms of the 20th century.

  • UB CSE Research Image

    Research Spotlight

    Handwriting recognition

    Pursuing work on document verification and identification, CSE researchers use machine-learning algorithms to study handwriting variability.

  • UB CSE Research Image

    Research Spotlight

    Structural determination

    CSE professor Russ Miller is one of the authors of a program that can determine the structure of molecules as large as 2,000 atoms from X-ray diffraction patterns.

  • UB CSE Research Image

    Research Spotlight

    Image analysis

    CSE professor Aidong Zhang is developing intelligent content-analysis programs to automatically analyze images, replacing human coding of semantic content.

  • UB CSE Research Image

    Research Spotlight

    Davis Hall northwest elevation

    This concept scheme shows Davis Hall, CSE's new $75M headquarters, viewed from the northwest. The edge of Ketter Hall is visible on the right, just east of Davis. UB held the ribbon-cutting ceremony on May 12, 2012.

  • UB CSE Research Image

    Research Spotlight

    Algorithm therapy

    A geometric algorithm developed by CSE professor Jinhui Xu configures a set of radiation beams to destroy brain tumors in a form of computer-aided surgery.

  • UB CSE Research Image

    Research Spotlight

    Award-winning faculty

    The CSE faculty includes NSF CAREER award holders; ACM, IEEE, and AAAI fellows; and editors of noteworthy journals.

  • UB CSE Research Image

    Research Spotlight

    Working together

    CSE faculty work with researchers in chemistry, the life sciences, the pharmaceutical sciences, media study, geography, and many other disciplines.

  • UB CSE Research Image

    Research Spotlight

    Davis Hall northeast elevation

    This concept scheme shows Davis Hall, CSE's new $75M headquarters, viewed from the northeast. Ketter and Furnas Halls can be seen on the left, just south of the new building. We broke ground in April 2009.

  • UB CSE Research Image

    Research Spotlight

    Automated mail

    CEDAR, a CSE-affiliated research center, developed the systems that postal agencies around the world use to automatically sort hand-addressed mail.

  • UB CSE Research Image

    Research Spotlight

    High-performance

    CSE's MultiStore Research Group is funded by a $1 million NSF grant for the development of high-performance online data-storage systems.

  • UB CSE Research Image

    Research Spotlight

    Cutting-edge research facilities

    CSE faculty are major participants in the new $200 million Buffalo Center of Excellence in Bioinformatics.

  • UB CSE Research Image

    Research Spotlight

    Grants for research

    CSE faculty average some $4.5 million annually in research grants. Our research areas range from high-performance computing to data mining.

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Calendar

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Click on the calendar image to view the schedule of planned events.

See a list of current and past events.