On this page, the Department highlights selected electives for Fall 2018. Our electives bring cutting-edge topics to our students – it is one way that we bring our research into the classroom. For the full list of electives, go to OASIS. OASIS is always updated for the next semester by the start of registration. For questions about electives including possible substitutions, please see our Department Advisors, John Morgan or Marjorie Fontalvo.
Selected Electives For The Computer Science and Computer Engineering Programs
CAP 4034: Computer Animation Fundamentals (taught by Dr. Wang) - An introductory course to computer animation. Topics include storyboarding, camera control, hierarchical character modeling, inverse kinematics, keyframing, motion capture, dynamic simulation, and facial animation.
CAP 4662: Introduction to Robotics (taught by Dr. Sun) - This course will introduce students to the fundamental theory and practice of robotics. Kinematics theory, robot motion planning algorithms, and designs of robotic systems.
CDA 4621: Control of Mobile Robots (taught by Dr. Weitzenfeld) -Mobile robotic control system design and implementation. Includes microcontroller, sensor, and actuator control processes for localization and navigation. Team project development of software interface for robot control.
CEN 4072: Software Testing (taught by Dr. Piegl) - The course provides the fundamental principles and tools for testing and validating large-scale software systems. The course is open to majors as well as non-majors.
CIS 4930: Affective Computing (taught by Dr. Canavan) - This course studies affective computing systems that can recognize, interpret, process, and simulate human affect. Topics include physiology of emotion, lie detection, wearable devices, music, gaming, and ethical, social, and philosophical concerns.
CIS 4930: Introduction to AI (taught by Dr. Perez) - Basic concepts, tools, and techniques used to produce and study intelligent behavior. Organizing knowledge, exploiting constraints, searching spaces, understanding natural languages, and problem solving strategies.
CIS 4930: Brain-Computer Interfaces (taught by Dr. Andujar) - This course involves the exploration of new forms of Human-Computer Interaction (HCI) based on passive measurement of neurophysiological states (cognitive and affective). Explores the uses of non-invasive ubiquitous electroencephalographic (EEG) brain technologies. Students will learn the basics of other brain imaging technologies such as near-infrared spectroscopy (fNIRS) and Functional Magnetic Resonance Imaging (fMRI) and how they can be studied in the field of computing, and ways to use such measurements as a form of brain-controlled machines.
CIS 4930: Cryptographic Hardware and Embedded Systems (taught by Dr. Mozaffari Kermani) - Introduces concepts related to the engineering aspects of cryptography, especially those related to embedded hardware systems. Student build upon previous experience to understand the security concerns of cryptographic hardware and embedded systems.
CIS 4930: Introduction to Hadoop & Big Data (taught by Dr. Zhang) - An introduction to design and analysis big data storage and analysis systems. Topics include cluster architecture of Hadoop Distributed File System, big data analysis in MapReduce, Spark, and other Hadoop ecosystems, such as Hive, Pig, OoZie, and Sqoop.
CIS 4930 Prog. on Massive Parallel Systems (taught by Dr. Tu) - This course looks at basics in large-scale parallel computing, CUDA programming, advanced techniques for code optimization, and domain-specific case studies. Students will engage in hands-on experience in CUDA programming.
CIS 4930: Network Science (taught by Dr. Iamnitchi) - This course will provide an introduction to graph theory and hands-on experience with analyzing real network datasets. The graph theory component provides the rigorous platform for understanding graph properties, important graph metrics, and different types of graphs. The data analysis component aims to build familiarity with basic tools for measuring graph properties and interpreting results.
CIS 4930: Computational Modeling Reasoning (taught by Dr. Licato) - Different paradigms for computationally modeling reasoning will be covered, including formal logical reasoning, informal argumentation, analogical reasoning, and approximate inference methods. Some experience in the following is recommended, but not required: Propositional calculus or Boolean algebra; and Python programming.
CIS 4930: Biometric Authentication on Mobile Development (taught by Dr. Neal) - In this course, we will explore various biometric implementations as a more conclusive alternative to user authentication. In particular, we will carefully consider the framework for a biometric system, and how mobile device platforms offer unique challenges in regard to this framework and other biometric properties. We will discuss and implement innovative ideas which coincide with and/or extend the research literature in regard to mobile device biometrics, incorporating various elements associated with machine learning, pattern recognition, and cybersecurity.
CIS 4930: Social Media Mining (taught by Dr. Ciampaglia) - The objective of this course is to learn how to identify and mine user patterns from social media. We will cover the fundamentals tools and techniques of social media mining --- like the analysis of social networks --- and some of its applications, like news aggregation and recommendation systems. The course will include a project-based programming assignment in which students will learn how to use Python to connect to social media APIs, crawl data, and mine information from them.
CIS 4930: Digital Circuit Synthesis (taught by Dr. Katkoori) - Digital circuit modeling and abstractions, hardware description languages, behavioral and logic synthesis algorithms, automatic circuit optimization, datapath and control synthesis, algorithmic transformations, and design space exploration.
CIS 4930: Privacy-Preserving Infrastructure (taught by Dr. Yavuz) - This course will explore emerging cyber-security technologies addressing security issues of cyber-infrastructures. It will cover privacy-enhancing and trustworthy techniques for cloud computing and internet of thing systems. It will also capture cryptographic techniques that are used to secure critical cyber-systems such as blockchains, vehicular networks and aerial drone systems.
CIS 4930 Capture the Flag (taught by Dr. Lewis) - This is a new course and we are very excited to be offering it. At its heart, this course is being offered to help students interested in computer security compete in Capture the Flag competitions. This course will help you to understand computer security fundamentals, as well as prepare you to for the computer security profession. This course covers fundamental problems, principles, and practical problem-solving techniques employed in various subfields of computer security; many of the techniques will be demonstrated and practiced using commonly used and customized tools and reinforced through CTF challenges.
CIS 4930 Cyber-Physical Systems (taught by Dr. Zheng) - This course considers cyber-physical systems and their design principles. Issues of cyber-physical systems at design/run time and possible approaches to addressing those issues will be discussed.
CIS 4930 Natural Language Processing (taught by Dr. Licato) - Provides an introduction to the field of Natural Language Processing (NLP), the study of how to use artificial intelligence to understand text written by people in natural settings. We will cover vector embeddings, calculating text similarity, and various language models, primarily using Python (prior experience is recommended, but not required).
CIS 4930 Augmented Virtual Reality (taught by Dr. Rosen) - This course will introduce students to the variety of computer graphics and computer vision techniques that make modern augmented and virtual reality systems immersive. Students will engage in a semester's-long group project from concept-to-demo, targeting their choice of application in augmented, mixed, or virtual reality.
CIS 4930 IoT System Design (taught by Dr. Katkoori) - In this course, we will learn what an IoT system is, different layered IoT architecture models, edge and fog computing concepts, design IoT systems for applications in various domains, such as, smart home, smart transportation, smart health, etc. We will also into security aspects of IoT Hands-on design exercises will be completed using IoT design kits.
COP 4365: Software System Development (taught by Dr. Jeanty) - Analysis, design, and development of software systems using objective methodology with object oriented programming and advanced software development tools (such as integrated development environments).
COT 4521: Computational Geometry (taught by Dr. Rosen) - Computational geometry is the study of efficient algorithms to solve geometric problems. Topics covered include Polygonal Triangulations, Polygon Partitioning, Convex Hulls, Voronoi Diagrams, Arrangements, Search and Intersection, and Motion Planning.
SELECTED ELECTIVES FOR THE INFORMATION TECHNOLOGY AND CYBERSECURITy programs
CNT 4403: Network Security and Firewalls (taught by Dr. Gauvin Jr.) - This course surveys network security standards and emphasizes applications that are widely used on the Internet and for corporate networks. This course also examines Firewalls and related tools used to provide both network and perimeter security. This is a core class for Cybersecurity majors, but it can be requested as an elective for Information Technology.
COP 4200: Penetration Testing (taught by Dr. Ventura) - Penetration testing and related software tools are presented. Legalities and various cyber-attacks such distributed denial of service, man-in-the-middle, and password attacks are covered. Methods to correct security flaws are given. This is a core class for Cybersecurity majors, but it can be requested as an elective for Information Technology.
COP 4883 Java Programming for IT (taught by Dr. Gaspar) - This course explores advanced programming techniques, using the Java language. Topics include generic programming applied to the Java collection framework, meta-programming allowing the code to inspect and interact with itself at runtime, and functional programming with the new stream API.
COP 4931: Information Privacy Trust Systems (taught by Dr. Yavuz) - This course covers foundational concepts, algorithms, protocols and tools to enhance information privacy for trustworthy computing systems, with a clear emphasis on both theoretical concepts and practical applications, and impact.
COP 4931 Capture the Flag (taught by Dr. Lewis) - This is a new course and we are very excited to be offering it. At its heart,
this course is being offered to help students interested in computer security compete
in Capture the Flag competitions. This course will help you to understand computer
security fundamentals, as well as prepare you to for the computer security profession.
This course covers fundamental problems, principles, and practical problem-solving
techniques employed in various subfields of computer security; many of the techniques will be demonstrated and practiced using commonly used and customized tools and reinforced through CTF challenges.
COP 4931 IT Systems Security (taught by Dr. Chellappan) - This course covers foundations of systems security, including availability, authentication, access control, network penetration/ defense, reverse engineering, cyber physical systems, forensics, supply chain management, and secure systems design. Please note this course is for Cybersecurity majors only.