Information Sciences and Technology (IST)

An interdisciplinary introduction to graduate research design for investigating how data and information technologies are created, analyzed, and evaluated. IST 501 serves as the central foundational course for graduate students who intend to conduct research in IST. Although each student may eventually focus on one or several methods discussed in the course, the College is committed to providing all of its research students an interdisciplinary mindset regarding their own and their peers' research activities. This mindset is a defining feature of IST research training. The course provides foundational information regarding three contrasting research perspectives of IST: Social Informatics, Human-Centered Design and Computational Informatics. The three perspectives are presented in an interleaved fashion, one week at a time, with gradually increasing complexity and sophistication in the methods used. The methods address requirements for, design of, and impacts of information technologies used to meet people's information needs at multiple levels of analysis, including individuals, groups, organizations, and national and global cultures. The technologies investigated are of various types, including algorithms, structured data, user interfaces, and distributed systems. Each one-week methods topic is practiced through an individual homework activity and a team project is used to provide an integrated application activity that cumulates throughout the semester. Through reading of contemporary and classic literature, demonstrations and practice with specific research techniques, and sharing and reflection on individual and team research activities, students will explore fundamental assumptions, theories and directions in contemporary research design useful to researchers in IST. The emphasis of this course is on defining and developing conceptual linkages between human behavior, the social, organizational, and cultural context of information and technology use, human experience when learning or using information and computing technologies, and the construction of information and computing technologies. The interdisciplinary research design will operate at individual, group, and other units of human, social, and organizational analysis, and across a range of information technologies.

Study of major methodological, normative, and theoretical issues in philosophy of science related to reserach in information sciences and technology. IST 503 Foundations for IST Research (3) This course is a study of major methodological, normative, and theoretical issues in the philosophy of science related to research in information science and technology. A significant part of this course will involve coordinating issues and problems customarily associated with the philosophy of science in general with current research in information science and technology (IST) in particular. In order to achieve this coordination, the study of classical texts in the philosophy of science will be interspersed at appropriate places with lectures and topics that exhibit relevant faculty research in various IST related disciplines.The course focuses on the main arguments that have been advanced in Anglo-American philosophy of the science for the period beginning about seventy years ago up to the present. The course contradicts the view of a single unitary "philosophy of science." It shows a series of positions and arguments that continue to lead on to still deeper questions. Usually the student will have adopted one of the classical positions without having examines it or defended it rigorously. Readings will progress in a historical fashion through arguments that attempt to provide a justification for the truth claims of science. The course will begin with a consideration of logical positivism in its early forms, i.e. the ideas of the Vienna Circle, and the early Wittgenstein's theory of meaning. The course will go on to the writings of Karl Popper especially as found in his Logic of Scientific Discovery. Continuing the historical development, Kuhn's "The Structure of Scientific Revolutions" will be considered. The discussion will then progress to the Popper-Kuhn debates involving the sophisticated falsificationists (Lakatos) and eclectic approaches like Feyerabend's. Finally, Richard Bernstein's book, Beyond Objectivism and Relativism is reviewed summarizing the debate. This final view strives to uncover the strong points in the opposing positions reviewed early in the course. Then it sets a hermeneutical position which he derives principally from the philosophy of Hans Georg Gadamer. This position amounts to a new and interesting view on how knowledge is attained in science and in life in general. The course relates the debates in the arguments in the philosophy of science to research issues in IST.

Provides the foundation to the research and theories of how technologies are used to meet society's, groups' and individuals' information needs. IST 504 Foundations of Theories and Methods of Information Sciences and Technology Research (3) This course provides an overview of the diverse fields that comprise the information sciences. The course has three broad objectives. First, the course serves as an overview to the theories, models, findings, research methods and research-related issues that frame the multiple fields of the information sciences. Second, the course provides students with skills of critical evaluation of literature. Finally, the course provides students a means to begin formulating researchable topics and questions. The course is designed as a fundamental course for research-oriented graduate students in the information sciences. The specific focus is a critical treatment of the research relative to the questions asked, views of a technology's affordances and potential uses, the implementation of the research, and conclusions drawn. Through reading of contemporary and classic literature, ongoing debate, reflection and synthesis, and active analyses, students will explore fundamental assumptions, theories and directions in the contemporary research in the various fields of the information sciences. The emphasis of this course is on defining and developing conceptual linkages between human and social behavior, information and the use of computing technologies. Assessments will be based on a number of short summary papers and an extensive synthesis of literature organized around a conceptual framework. Because this is an interdisciplinary subject, students should be prepared to read outside their primary research/interest area and be ready to embrace and integrate new knowledge from related fields into their primary field.

Provides the foundations on research design and methods used in information sciences and technology. IST 505 Foundations of Research Design in Information Sciences and Technology (3) This course develops students' abilities to conduct academic research, formulate a relevant thesis proposal, present and discuss the progress of their work, and conduct a small-scale research project in an information sciences and technology-related area. It provides an overview of the major research methods used in the area of information sciences and technology, including quantitative, qualitative, computational, and design approaches. The course emphasizes developing and practicing research design, execution, evaluation, and writing skills through application of the concepts that define the course.

Foundational theories and techniques in general computational informatics.

Introducton to theoretical, computational, and practical issues involved in managing textual, spatial, temporal, and multimedia information in a computerized system. IST 511 Information Management: Information and Technology (3) The objective of IST 511 is to provide an introduction to the theoretical and computational issues involved in managing textual, spatial, temporal, and multimedia information. The course will survey the nature of information in various application contexts (digital libraries, digital government, healthcare information, environmental information, etc) and seek to understand their generic and specific requirements for information management. Students will be exposed to major principles and technologies for information management that are drawn from database systems, and information retrieval (IR) and spatial/geographical information systems literature. Special emphasis will be given to the problems of managing heterogeneous information sources with different ontology, representation, scales, and error characteristics.This course is required of all Information Sciences and Technology (IST) graduate students under both research Master and Ph.D. degrees. It is a foundation course that should be taken in the first or second year of graduate study. IST 501 is the prerequisite for this course.For hands-on practice and demonstration purposes, this course requires student access and use of a database management system (such as ORACLE or SQL server), a geographical information systems (Arc View or MapInfo), a information retrieval system, and/or a ERP (Enterprise Resource Planning) system.

Foundational theories in Human-Centered Interactions used for Human-Centered Design.

Users, models of users, developing the models, technology for creating interfaces; examples of good research and implications for Human-Computer Interface (HCI) design. IST 521 Human-Computer Interaction: The User and Technology (3) This course introduces students to the broad area of human-computer interaction and the idea of a theory driven interface, an underlying concept in HCI. To do this, the course starts by outlining relevant aspects of human behavior with respect to technology and how interfaces are developed, the two raw components. Students are then exposed to a tool for creating interfaces and a variety of theories of how users interact with technology on a variety of levels. These theories are validated and supplemented by usability studies. The course completes with a group project based on the readings and theories introduced in the first 12 weeks.

IST 525 introduces theories, empirical findings, evaluation methods, and design frameworks in computer-supported cooperative work. IST 525 Computer-Supported Cooperative Work (3) Students in the course will investigate CSCW challenges and opportunities from the dual perspectives of human-computer interaction and socio-technical systems analysis. They will analyze group interactions and concerns in collaborative activities such as written and spoken communication, design, meetings, education, decision-making, and everyday work activities. They will review and critique state-of-the-art CSCW technologies, including text-based and video communication tools, immersive meeting environments, group decision-making, workflow, and knowledge management. These technologies will provide a context for investigating and synthesizing issues related to individual use (e.g., perceptions of cost-benefit), the context of collaboration (e.g., social and cultural norms embodied in systems), and software architecture (e.g., coupling and consistency management). Students will apply their understanding of these issues in evaluation and design projects.

IST 526 addresses concepts and tools for developing working user interface software and prototypes to provide effective information visualizations. IST 526 Development Tools and Visualizations for Human Computer Interaction (3) This is a technical course focused on the different tools for designing and creating working software for the human-computer interface to complex systems. The course builds on the psychological and social theories, usability engineering methods, and computer programming techniques from its prerequisite courses to provide an advanced experience with user interface design and construction. Because of their importance and depth, special consideration is given to the concepts and tools used to develop sophisticated visualizations of complex information.

Foundations in social theories used in the study of the human context within which information and information technology exists.

Assists IST researchers in their efforts to learn about and employ appropriate qualitative methods in their research. IST 541 Qualitative Research in Information Sciences and Technology (3) As information and communication technologies (ICTs) have evolved, so too has our understanding of the role of the human contexts within which information technologies are situated. This has led to the need for appropriate methods of studying information systems and technologies in their context of use. There is a growing consensus that qualitative methods offer important research opportunities for this type of study. Therefore, researchers in such fields as the information sciences and technologies, communication technologies and information systems should have an understanding of the various types of qualitative methods so that they can determine ones that are most appropriate for addressing their particular research problems. The course is complementary to quantitative methods courses, in that it addresses problems that are not amenable to those approaches. For example, studies involving very small groups, individuals, societal level concepts and others often lend themselves to qualitative research techniques.This course begins by considering research topics that lend themselves to the choice of qualitative research methods. It then proceeds to examine the steps involved in conducting qualitative research. These include: developing the research question(s); choosing a particular research method (such as ethnography, case study or action research); making decisions about approaches to data collection (such as interview or focus group) and analysis (such as coding technique); and producing and publishing the results.This course explores concrete issues that researchers have encountered in their use of qualitative methods. It does this by drawing upon the collective expertise of distinguished scholars who employ qualitative methods in their own research. The course will examine published work that focuses on research findings as well as that which discusses methodological issues.

This course teaches the principles and practice of software security. The course gives an overview of the foundations of computation models and languages. It then builds on this foundation by teaching students how to address software security issues using fundamental techniques such as type systems and program analysis. The course also covers the practical side of software security, such as memory safety issues including buffer overflow, code injection, and code reuse attacks, as well as some of the latest security problems. Through this course, the students will gain a concrete understanding of principles and practices of software security and be prepared for research on software security related problems.

Essential skills and knowledge for effectively utilizing networks and Internet technologies to facilitate, manage and secure data communications and applications. IST 554 Network Management and Security (3)Information technology is an integral part of today's organizations and services. As information systems and networks continue to grow and evolve we are becoming more and more dependent, individually and socially, on them to provide support for the economy, military, education and business. Because of this dependence, network-based information and communication systems are attractive targets for those who would compromise information or disrupt services for economic, social or political purposes.

Distributed decision making theories and agent-based technologies, models and systems with applications in command and control, emergency and resource management. IST 555 Intelligent Agents and Distributed Decision Making (3)This course introduces the theory and design of intelligent agents for distributed decision making with applications in grid computing, command and control, emergency management and sensor management. Emphasis will be placed on understanding theories of decision making and using them to model and build relevant agent-based distributed systems for supporting decision making.

This course will introduce data mining techniques, including frequent pattern and association rule mining, some basic background on classification and clustering, and applications of data mining techniques in specific domains. The emphasis will be on applications in specific domains rather than fundamental methodologies. IST 557 Data Mining: Techniques and Applications (3) The course will begin with an introduction of data mining field, including why data mining, what is data mining, what kinds of data can be mined, what kinds of patterns can be mined, an overview of technologies, the major issues in data mining, and a brief history of data mining community. The three key lecture topics are: (1) mining frequent patterns and association rules; (2) classification: basic concepts and techniques, and (3) cluster analysis: basic concepts. For topic (1), we will introduce frequent item set mining methods including Apriori and FPGrowth. We will also teach advanced frequent pattern mining methods such as pattern mining in multi-dimensional space, constraint-based frequent pattern mining, mining high-dimensional data, sequential pattern mining, and graph pattern mining. For topic (2), we will teach how to formulate a real-world problem into a classification problem, how to apply classification models on real data and how to analyze the results. The classification models covered in our class include decision tree, random forest, boosting, support vector machine and kernels, naive bayes classifier, and KNN. Students will learn how to evaluate classification methods using different measures. We will be brief on the fundamental classification methods and will focus more on the applications of such methods on various kinds of data. For topic (3), we will cover the clustering topics including partitioning methods, hierarchical methods, density-based methods, grid-based methods and evaluation of clustering results. We will be brief on the fundamental clustering methods and will focus more on the applications of such methods on various kinds of data. Four weeks will be used for lectures on special topics such as text mining, time series mining, spatial data mining, graph mining, image mining, and emerging subjects in data mining. The purpose of the special topics is to help students learn about real-world data mining problems and applying state-of-the-art solutions to them. Instructor will select a few topics based on students' project proposals. Instructor and students will work together on the literature survey and prepare for the presentation. Potential key special topics include: Mining text data. We will introduce basic preprocessing methods such as tokenization, stemming, and stopwords filtering and basic textual features such as tf-idf. We will teach text mining topics including sentiment analysis, topic modeling, and entity extraction. Mining temporal data. We will introduce basic techniques in mining temporal data, such as measuring time series similarity, periodicity analysis, and trend prediction. Mining spatial data. We will introduce basic spatial models, clustering of spatial locations, spatial outliers, co-location patterns, and location prediction. There will be five discussion classes. Instructor will use these classes to talk with individual students and teams, help them with the problems they encounter in assignments and projects, and better personalize the learning experience.

Advanced data mining techniques: temporal pattern mining, network mining, boosting, discriminative models, generative models, data warehouse, and choosing mining algorithms. IST (STAT) 558 Data Mining II (3)This course is the second course in a two-course sequence on data mining. It emphasizes advanced concepts and techniques for data mining and their application to large-scale data warehouse. Building on the statistical foundations and underpinnings of data mining introduced in Data Mining I , this course covers advanced topics on data mining; mining association rules from large-scale data warehouse, hierarchical clustering, mining patterns from temporal data, semi-supervised learning, active learning and boosting. In addition, to computational aspects of algorithm implementation, the course will also cover architecture and implementation of data warehouse, data preprocessing (including data cleansing), and the choice of mining algorithms for applications. In addition to discriminative models such as CRF and SVM models, the course will also introduce generative models such as Bayesian Net and LDA. A term project will be developed by each student to apply an advanced data mining algorithm to a multi-dimensional data set. Classes will include lectures, paper discussions, and project presentations. Paper discussions will allow students to discuss state-of-the-art literature related to data mining. Project presentations will enable students to share and compare project ideas with each other and to receive feedback from the instructor.

The study and application of data mining/machine learning (DM/ML) techniques in multidisciplinary design. CSE 561 / EDSGN 561 / IE 561 / IST 561 Data Mining Driven Design (3) This course examines how theoretical data mining/machine learning (DM/ML) algorithms can be employed to solve large-scale, complex design problems. Knowledge Discovery in Databases (KDD) is the umbrella term used to describe the sequential steps involved in capturing and discovering hidden, previously unknown knowledge in large databases. The course begins with foundational information regarding engineering design and provides an overview of KDD and the emergence of the digital age. Students will investigate data acquisition and storage techniques where they will learn the difference between stated and revealed data as related to design. Students will construct their own databases and learn essential techniques in data base queries (SQL) and management. Data transformation techniques, such as binning and dimensionality reduction, will be examined in the data transformation section of the course. This course has a design-driven focus, which will enable students to solve real-life design challenges spanning diverse domains.Students will work on project-based exercises aimed at proposing novel data mining algorithms, or employing existing algorithms to solve design problems in fields relating to engineering, healthcare, financial markets, military systems, to name a few. Data visualization techniques will also be studied to help communicate complex data mining models in a timely and efficient manner.

This course introduces the theoretical foundations of information science, with applications in communication, signal processing, machine learning, and pattern recognition. IST 562 Theoretical Foundations of Information Science (3)This course introduces the theoretical foundations of information science, with applications in communication, signal processing, machine learning, and pattern recognition. Emphases will be placed on theories of communications and compression. Theories of probabilities and inference, learning methodologies, and graph theory.

This course examines the fundamental elements of crisis, disaster, risk and emergency management.

This course provides students with tools and techniques for processing and extracting meaning and knowledge from a large volume of text data, with a focus on applying contemporary research findings in human language technologies. The course begins with a brief overview of human language technologies (HLT), with the goal of covering the foundations of HLT to students with a diverse background. The course then covers three topics of contemporary interest in human language technologies: sentiment analysis, computational semantics, and computational discourse. Students will evaluate and compare ideas from recent research.

The ubiquity of computing systems and information technology has made security and privacy become a central issue in the "information age." More and more evidence revealed that technology alone is not sufficient to solve security and privacy problems. Humans are often thought of as "the weakest link in the chain of various security and privacy issues." Thus, it is essential for security and privacy experts to have an understanding of the human factors of security and privacy, e.g., how people will interact with the systems they develop. This course is designed to provide students an overview of the theoretical foundations and empirical findings of human factors of security and privacy and give them experience in understanding and designing studies aimed at helping evaluate usability and user-interface issues in security and privacy systems. The course is suitable for students interested in privacy and security who would like to learn more about the human aspects, and for students interested in human factors/HCI who would like to learn more about security and privacy.

Students apply theoretical skills and knowledge to critically assess solutions to "real world" Cybersecurity problems. This course combines synthesis and analysis of responses to Cybersecurity event simulations with critical thinking to resolve and extend solutions. Students conduct a series of laboratory assignment milestones. Each milestone generates a recommended literature-based resolution (i.e., tools, techniques, and methodologies) to prevent and control real world Cybersecurity attacks. Peer review exposes students to alternative exercise solutions, permitting a critical reflection. Analysis of each milestone is documented and compiled to create a final portfolio of lessons learned, along with new and emerging theoretical responses to the simulated Cybersecurity events. Each milestone in the final portfolio emphasizes literature-based research reflection, enabling the student to expand the frontiers of knowledge through creation of a final scholarly work product.

Continuing seminars that consist of a series of individual lectures by faculty, students, or outside speakers.

Supervised student activities on research projects identified on an individual or small group basis.

Creative projects, including nonthesis research, that are supervised on an individual basis and which fall outside the scope of formal courses.

Formal courses given on a topical or special interest subject which may be offered infrequently; several different topics may be taught in one year or semester.

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This graduate course builds foundational knowledge in students new to cybersecurity. This course covers operating systems, cybersecurity (OSI Model, TCP/IP suite, hardware, etc.), networking, database, and cloud concepts, as well as topics in security, risk, analysis, and cybersecurity.

This graduate course improves understanding in an organizational setting of the principles and practices of cyber forensics as well as the management of information security. Foundational Cybersecurity forensic software and hardware analyses is accompanied by information security management in an organization. Conducting basic Windows and Linux computer forensic investigative processes, discussion, analysis, and legal aspects are covered in the first part of the course. The second part of the course covers various information security functions of an organization such as laws, ethics, planning, governance, risk management, policy creation, crisis, and incidence response.

This course provides theoretical and applied foundations of information security and assurance. IST 815 Foundations of Information Security and Assurance (3) IST 815 provides theoretical and applied foundations of information security and assurance, with an emphasis on access control, information security governance and risk management, cryptography, security architecture and design, software security, business continuity and disaster recovery planning, network security, physical security, operations security, laws, regulations, investigations, and compliance.

The growth and use of the web is increasing at a remarkable rate. The web is a huge evolving system with data full of uncertainties and has become a critical part of everyday life of modern societies. This course will cover fundamental techniques used in building and maintaining the web. The focus will be on the practical aspect of the web's backbone techniques. Topics to be covered include: basic web and internet technologies, modern applications based on the web techniques, and an integrated presentation of theory, examples, exercises, and applications.

IST 820 provides theoretical and applied foundations of fundamentals of network security, data sources, data collection techniques and tools, cybersecurity analytics infrastructure, machine learning and data mining, network forensics, anomaly and malware detection, security data visualization, and security dashboard design and implementation.

This graduate level course provides students with a foundation in Cloud Computing including its supporting network infrastructure. Key parts of this type of infrastructure are examined with respect to their vulnerabilities. The focus of the class addresses inherent cyber vulnerabilities in cloud computing. Approaches and techniques for securing data, hardware and software in the cloud are then discussed. Finally, topics such as disaster recovery and deployment models are explored.

This course provides an overview of techniques to assess and ensure the security of web applications and services that drive modern e-commerce transactions. The course first presents foundational knowledge of security technologies, web servers, web applications, and web services. Building on this foundational knowledge, various code review and testing techniques to identify and evaluate vulnerabilities in web applications, web services, and databases are covered through comprehensive hands-on exercises. Besides, the best practices to prevent common flaws, misconfigurations, and vulnerabilities in web applications and services are discussed. The course emphasizes threat modeling as a critical security evaluation approach of web applications and services.

This course provides students with the principles of project management and knowledge of the project management skills and processes needed to select, initiate, and plan a project. Students will employ various elements of the project management process, software, tools and techniques in a complex cybersecurity environment. In addition to learning basic project management topics, including creating the project charter, developing project scope statements, creating the project schedule and budget, assigning project resources, and risk planning, students will explore more advanced topics in the area of cybersecurity project management, including cybersecurity risk management and assessment and agile project management. Students will learn the sophisticated techniques and management designs used to effectively manage risk and uncertainty, financial exposure and human constraints.

This course provides a foundation in information systems and technology for improvement of healthcare.

Introductory course on search engines and information retrieval. Search, indexing, ranking, and search evaluation are formally defined, explained, and used. IST 841 Search Engines & Information Retrieval (3) This is introductory course on the principles of information storage and retrieval systems and databases. Students will learn how effective information search and retrieval is interrelated with the organization and description of information to be retrieved. Students will also learn to use a set of open source tools and procedures for organizing information, will become familiar with the techniques involved in conducting effective searches of print and online information resources and will build a vertical/specialty search engine. Search, indexing, ranking, and search evaluation are formally defined, explained and used.

This course provides a foundation in knowledge management concepts and paradigms, emphasizing computational methodologies and tools for supporting data and knowledge management practices.

This course focuses both on monitoring systems and networks for real-time threats and on "ethical" hacking tools and techniques. Both topics allow students to recognize the need for the constant collection and analysis of Cybersecurity data and provide the insight on how to accomplish such. Students in the first part of the course practice techniques, and put into use various tools, for identifying Cybersecurity threats. Students in the second part of the course test systems, networks, and policies for vulnerabilities and exploit them while recognizing how to prevent such real attacks from hackers.

This course covers the fundamental principles, methods, and tools of visual analytics that enable data and security analysts to synthesize information and derive insight from data. When dealing with complex decisions, analysts are faced with a continuously growing set of data originating from a wide range of sources and in a wide variety of formats. Such data needs to be analyzed to characterize a situation and to take actions promptly. Visual Analytics (VA) represents a human-centered approach in designing interactive data visualizations and dashboards that enables full cycles of data analysis, from making sense of data, assessing situations, detecting unexpected patterns, as well as communicating findings and informing actions. The objective of this course is to introduce a set of data visualization and interaction methods that enhance the analytical skills of students in solving problems. Students will gain skills and knowledge in designing interactive visual dashboards that support analytical reasoning with data. Upon completion of this course, students should develop skills in (1) choosing proper data visualization methods (e.g., bar charts, line charts, tree maps, scatter plots, histograms, bullet charts) to reveal patterns in quantitative and categorical data; (2) designing visualization of spatial and temporal data for exploring geo-temporal patterns; (3) creating customizable and dynamic visualizations for exploratory data analysis; (4) creating interactive dashboards for investigative analysis; (5) applying visual analytic skills in applications such as detecting risk or threats in security investigation or monitoring pandemic spreads.

Understanding the concepts, techniques, and issues surrounding the fusion of information from multiple sensors and sources of data. IST 885 Introduction to Multisensor Data Fusion (3)Rapid advances in nano and micro-scale sensors, ubiquitous wide-band wireless communications and improvements in computing provide the opportunity to collect and disseminate huge amounts of data and information from sensors, humans acting as observers, and emerging data available on the web. Applications for this data are widespread and include areas such as geospatial intelligence, emergency management, environmental monitoring, epidemiology, and others. This course introduces methods and process models for fusion of the information from diverse sources to achieve inferences that cannot be obtained by using a single source or sensor. Course Objectives: IST 885 provides an introduction to multisensor information fusion. Multisensor information fusion seeks to combine information from multiple sensors and sources to achieve inferences that are not feasible from a single sensor or source. the proliferation of micro and nano-scale sensors, wireless communication, and ubiquitous computing enables the assembly of information from sensors, models, and human input for a wide variety of applications such as environmental monitoring, crisis management, medical diagnosis, monitoring and control of manufacturing processes. Techniques for fusing multisensor and multi-source information are drawn from a variety of disciplines including statistics, data mining, artificial intelligence, estimation and control theory, pattern recognition, and signal and image processing. While this course is non-mathemathical it will help students understand the concepts, techniques and issues associated with developing and using multisensor data fusion systems. At the end of this course students should be able to: * Explain different models of multisensor data fusion and describe the advantages and limitations of data fusion * Explain the five levels of data fusion in the Joint Directors of Laboratories (JDL) data fusion process model * Assess and characterize a sample information fusion application * Identify various techniques used in multisensor data fusion and indicate the applicability and limitations of the techniques for a selected application * Design a data fusion system including specifying the required functions, applicable techniques, selection/assessment of sensors and information sources, and design of a sample user interface * Discuss current technology trends that affect the implementation of a fusion system. Student activities: The course consists of ten lessons and one capstone group project that will span either the 15-week semester or the combined 12-week summer session. Each lesson will require approximately 8 hours of student activity. Student activities will include reading lesson text, online quizzes, and discussions about the way in which multisensor information fusion is applied to selected applications such as geospatial intelligence, environmental monitoring, monitoring of complex systems, crisis management or related areas.

design and development of mobile computing-based applications and services utilizing current and emerging mobile computing technologies. The purpose of this course is to provide students with an advanced and hands-on exploration of mobile computing paradigms. Mobile computing addresses the mobility needs of business operations and management in organizations, with the increasing trend of leveraging a variety of deployed enterprise information systems. Hence, well-designed and developed mobile applications can meet the needs of business mobility on both the service provider and the customer sides. This course is designed to explore and discuss approaches to the design and development of mobile applications. It builds an awareness of the business need for operational agility and mobility, and the value of existing IT investments in organizations. Specifically, this course investigates the fundamental design and development of mobile applications and services using platform technologies; area topics include mobile application and services design patterns, user interface, animation, location & mapping, and integration. Through working on exercises, labs, and projects, students will be able to identify and apply appropriate mobile platform technologies in their assignments and will gain skills and coding experience in the development of adaptable and sustainable mobile application solutions. Consequently, with this course, students will learn mobile development environments, application and service design and development, device emulators, data and mobility management, and enterprise solution-based integration. Cross Listings: IST 888 will be added as a cross-listed course.

This course is a laboratory-based course that requires students to apply skills and knowledge from previous coursework to "real world" cybersecurity scenarios and problems. The course combines analyses of cybersecurity issues with the critical thinking required to resolve them. Students will be faced with a variety of laboratory assignments spanning a wide range of cybersecurity vulnerabilities and scenarios they must deal with. Each module's laboratory assignment requires a thorough analysis in order to apply the proper tools and techniques for a successful resolution. Peer reviews of work ensure that students grow in their understanding of the skills involved for a given exercise and in their ability to judge alternate approaches to resolution.

Creative projects with a professional orientation, including nonthesis research, that are supervised on an individual basis and which fall outside the scope of formal course.

Forman courses given on a topical or special interest subject with a professional orientation that may be offered infrequently.