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Computer Science Summer Camps for High School Students Set for July 8-19

8:36 AM on March 21, 2013


MELBOURNE, FLA.—How does Netflix recommend movies for you to rent? How do you program in Java? These will be some of the questions answered at Florida Institute of Technology’s computer science-related summer camps in July. The university’s Department of Computer Sciences offers two computer programming summer camp experiences, each five days long,



Fall 2013: (Large) Algebraic Data Structures (with High Volume Automated Testing)

12:49 PM on March 18, 2013


Algebraic Data Types (ADT's) is the study of data structures without regard to the implementation. For instance, given a stack, S, we all know that pop(push(e,S)) == S, and this abstraction should be true for any implementation. These simple abstractions also give insight and direction to software testing; simple large scale, high volume tests may



Professor and Alumna Have Heads in Clouds with New Book

7:32 AM on December 12, 2012


MELBOURNE, FLA. –Florida Institute of Technology computer science Professor Scott Tilley and Florida Tech alumna Tauhida Parveen highlight the usefulness of cloud computing for software testing in their recently published book, Software Testing in the Cloud: Perspectives on an Emerging Discipline.

Cloud computing has gained significant attention



Spring 2013: Adv Topics in CS: Steganography and Applications CSE 5800-01

7:43 AM on December 3, 2012


Digital content surrounds us, providing opportunity to store or hide information within it. Becoming aware of these opportunities can help make applications more flexible, as well as help secure content, particularly multimedia. This course explores various ways in which information can be hidden, including encryption, watermarking, and steganog...



Spring 2013: Robotics and AI CSE 4510-E14/5694

7:42 AM on December 3, 2012


Robotics is where the computer starts to act not only on the human mind, but also on the physical world. In this course you will be introduced to the concept of robot, the basic components of robotics, and some algorithms used in robotics. We will concentrate on the Artificial Intelligence side of robotics, with modelling and planning algorithms. W



Spring 2013: CYB 5660 Secure Software Development

8:52 AM on November 14, 2012


Software vulnerabilities are far too common, but a security-oriented development process can help. This course explores the components of secure software development, including the characteristics of resilient software, best practices for development, and other topics spanning the software lifecycle. This course is acceptable as an Advanced Electiv



BioComplex Lab: Journal Paper Accepted

10:50 AM on November 2, 2012


Congratulations to Srividhya Venugopal (PhD student) and Evan Stoner (BSc student) for for having their paper entitled "Understanding Organ Transplantation in the USA using Geographical Social Networks" has been accepted for publication at the Journal of Social Network Analysis and Mining (SNAM) published by Springer Verlag.



Spring 2013: High Volume Automated Testing

8:50 AM on November 2, 2012


Many of the most maddening software errors cause intermittent failures. Do something—the program fails. Do what you think is the same thing again—no failure. These are hard to diagnose and almost impossible to provide customer support for, but they can be serious irritants or critically dangerous. For example, at least some of the flaws underlying



Spring 2013: CSE 4510/5400-E6: A Survey of Interdisciplinary CS ("CS in Action")

10:38 AM on October 31, 2012


This course provides a survey of how CS can help solve problems in other disciplines, such as Biology and Sociology. For each discipline, we first discuss a sample problem(s) and the associated background knowledge to understand the problem(s). We then discuss possible algorithmic solutions and compare them. Faculty members from other disciplines m



Spring 2013: CYB 5675: Data Mining for Cybersecurity

3:40 PM on October 25, 2012


This course explores data mining and machine learning in cybersecurity environments. The student will learn a variety of data mining and machine learning algorithms and their utility in cybersecurity tasks, such as signature, anomaly, scan, and intrusion detection. Network traffic profiling and privacy-preserving data mining will also be covered.



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