COMP 510 ADVANCED IMAGE ANALYSIS TECHNIQUES

Image processing course in the fundamentals of 2-D digital signal processing with emphasis in image processing techniques, image filtering design and applications. Programming exercises in Matlab (or Octave) will be used to implement the various processes, and their performance on synthetic and real images will be studied. Applications in medicine, robotics, consumer electronics and communications.

COMP 520 ADVANCED DATABASE SYSTEM

Three hours lecture in the lab per week Prerequisite: Admission to the Computer Science or Mathematics Graduate Program This graduate course covers advanced analysis of Relational Database Management Systems including their design and implementation. Topics include relational algebras, Entity Relation Diagrams, first, second, and third Normal Forms, data integrity constraints, triggers, query optimization, indexing, stored procedures, distributed databases, database administration issues, transaction processing and scheduling, object oriented database modeling, and data security.

COMP 529 CLOUD COMPUTING

Design and programming of distributed systems that use telecommunication networks as their computing platform.

COMP 524 SECURITY

A survey of security issues and techniques for stand-alone and networked computer systems including databases. Techniques such as auditing, risk analysis, cost-benefit analysis. Security standards. Application in various fields.

COMP 546 PATTERN RECOGNITION

New and emerging applications of pattern recognition (PR) such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition - require robust and efficient techniques. Statistical decision making and estimation are fundamental to the study of PR. Pattern content is analyzed using feature extraction and classification. The principles and concepts underpinning PR, and the evolution, utility and limitations of various techniques (including neural networks) will be studied. Programming exercises will be used to implement examples and applications of PR processes, and their performance on a variety of diverse examples will be studied.

COMP 550 ADVANCED SOFTWARE ENGINEERING

The design, development and analysis of effective interfaces to computer systems. Trends in graphical user interfaces.

COMP 549 HUMAN-COMPUTER INTERACTION

The design, development and analysis of effective interfaces to computer systems. Trends in graphical user interfaces.

COMP 554 ALGORITHMS

Design strategies for algorithms and data structures. Theoretical limitsto space and time requirements. Time/space trade-offs. Categories of problems and algorithms. Applications to business, bioinformatics, engineering, telecommunications and other disciplines. Open problems in the field.

COMP 566 GEOMETRY AND COMPUTER GRAPHIC

Algorithms for geometric analysis and retrieval of 3D shapes from large 3D databases common in severalfields, including computer graphics, computer-aided design, molecular biology, paleontology, and medicine. The focus of study will be recent methods for matching, registering, recognizing, classifying, clustering, segmenting, and understanding 3D data.

COMP 569 ARTIFICIAL INTELLIGENCE

The course covers the many aspects of how human intelligence might be encoded in computer programs and mechanisms such as robots. This includes topics in Natural Language Processing, Computer Vision, Expert Systems, and Automated Problem Solving.

COMP 571 BIOLOGICALLY INSPIRED COMPUTING

Study of computing paradigms that have roots in Biology including Neuromorphic Systems, Evolutionary Systems, Genetic Programming, Swarm Intelligence and Artificial Immune Systems.

COMP 572 NEURAL NETWORKS

Covers the basic ideas of distributed computation with many simple processing units, similar to the neurons of the brain. Topics include: Hopfield style networks applied to optimization problems, and the backpropagation method applied to pattern classification problems. Additional topics include associate memory, binary vs. analog networks, simulated annealing.

COMP 575 MULTI-AGENT SYSTEMS

Analysis of design issues that currently confront software engineers as they define the electronic ecosystem that will be housed in the computer networksof the future. The course focuses on state-of-the-art agent technology. Inthis course the student will build an agent development framework and then implement several intelligent agents.

COMP 578 DATA MINING

This graduate course covers the fundamentals of Data Mining. Topics include: the analysis of patterns of data in large databases and data warehouses, the application of statistical pattern recognition, and data modeling and knowledge representation. Applications in large databases and gene hunting.

COMP 581 MATHEMATICAL METHODS IN ARTIFICIAL INTELLIGENCE

This course presents several branches of mathematics that provide computational basis for Artificial Intelligence. The course covers Trees and Search, The Concepts of Predicate Logic, The Theory of Resolution, Nonmonotonic Reasoning, Probability Theory, Bayesian Networks, Fuzziness and Belief Theory, Classifier Systems, Math for Neural Networks, Elements of Statistics, Decision Trees and Optimization.

COMP 590 ADVANCEDTOPICS IN COMPUTER SCIENCE

Selected advanced topics in Computer Science.

COMP 597 MASTER THESIS

Supervised research in the field of computer science or its applications. Required to present their research at Graduate Seminar.

COMP 599 GRADUATE SEMINAR

Oral presentations of current advancements in the field, reports on students’ research, master thesis, and projects.