Doctoral Degree

Information Systems Engineering and Management Ph.D.

This course introduces the basic principles (systems thinking and quantitative methods) of systems engineering and shows how these principles can be used to strategically plan, integrate, secure and administer the complex information systems that support and drive the current and future digital enterprises. Topics include: digital enterprises, aligning information technology strategy to business strategy, enterprise applications (customer relations management, procurement, supply chain management), ecommcerce, decision support, knowledge management, artificial intelligence (AI) applications, cost/benefit analysis and information technology infrastructure. These topics are explained through case studies and examples by using a strategic planning methodology.

A high level of end-user and client involvement is absolutely critical in creating usable and effective software and technology that attracts audiences and/or generates revenue. User-centered design (UCD) describes an approach to business analysis and technology development that demands user interaction and user feedback in all stages of the development lifecycle. The UCD process involves a collection of activities and techniques that can be used to create the more usable, intuitive, and effective technology possible. This course covers the full range of UCD methods and demonstrates the importance of these techniques in designing and building interactive technology, focusing mostly on software applications.

Interdisciplinary presentation of artificial intelligence as a coherent body of knowledge to acquaint the student with the key concepts and applications in business, science and engineering. The course covers models of intelligent behavior, including problem solving, knowledge representation, reason, planning, decision making, learning, perception, pattern recognition, action, communication and interaction. Recent developments in knowledge management, expert systems, computer-aided consulting and integrated intelligent systems are covered through a wide range of case studies, examples and hand-on experiments.

This course prepares the student to analyze business information systems in the digital age and to build models and logical designs that can be later implemented. The emphasis will be on the business processes and business requirements needed to build conceptual models that help in analysis of business requirements. This course prepares the student to design complex systems and to build applied designs and architectures.

This course emphasizes the practical aspects of the design and administration of modern Database Management Systems (DBMSs) that host enterprise data. Specific topics include the role of data in modern enterprises and the data life cycle that spans conceptual database design, database query languages such as SQL, database integrity rules, database administration, and data warehouses. This course utilizes commercially available relational DBMSs for hands-on experiments and explore how to create an entity-relationship data model, translate that model into relational schema, build and use a relational database that implements the schema, create SQL queries to retrieve and manipulate needed data, provide access to remote databases from web browsers, and experiment with DBA (Database Administration) capabilities. The student also investigates recent developments in database technologies (e.g. NoSQL). This course prepares the student for database design and administration positions and will also provide the necessary background for more specialized courses in database systems.

Modern digital enterprises are characterized by increased automation, mobile services, extended B2B operations with global business partners, and on-demand business services. The main issue in such enterprises is to architect and integrate a very wide range of services quickly and effectively. This course presents a ‘systems’ perspective based on service oriented architecture (SOA) that combines processes, people and technologies, and highlights the role of information and communication technologies, enterprise models, and emerging SOA standards in developing flexible and integrated business architectures.

This course is an introduction to web-based software engineering environments, design patterns, frameworks and key architectural aspects of robust enterprise applications. Topics for software development technologies include development languages and frameworks (e.g., .Net, Java, opensource), various tools used during the development lifecycle, and key components of an application in terms of the data, process and presentation layers. Architectural topics include prevalent design patterns such as model-view-controller (MVC), Web Services, and service-oriented architecture (SOA). The student uses computer-aided software engineering (CASE) environments and develops software architectures of real life enterprise applications.

The information technology product is central to most business systems. Quality of the product is represented by accuracy, reliability, repeatability and specific customer requirement standards. Various techniques to understand the quality control processes and quality assurance measures as demonstrated in industry standards and protocols are covered.

Smart Enterprises are the next generation of digital enterprises that heavily rely on artificial intelligence (AI) to deal with customers, suppliers/partners, government agencies and employees. This course highlights advances in research, technologies, systems, and applications as related to intelligent digital enterprises such as smart cities, smart towns, smart healthcare, smart islands, industry4.0, and automated planning environments. The emphasis is on “strategic intelligence” (SI) that refers to the intersection of Business Intelligence, Knowledge Management, and Competitive Intelligence for improving the strategic decision making in Smart Enterprises. Instead of intelligence on one sector, SI concentrates on intelligence that cuts across multiple sectors. The course will use case-based and project-based approaches for discussion and assignments but the focus is on research directions in this broad area of work. Students will be expected to produce a research paper as the final output of this course.

This course will build on the introduction to research methods provided in GRAD 509 to examine and practice advanced methods of research and study design. Topics covered will include research theorizing and model development, instrument development and validation, structural equation modeling, multivariate techniques, grounded theory, action research, multi-methods, and significant study of design science research.

This course integrates advanced systems engineering principles with AI/ML to design and analyze complex intelligent systems. The student will learn a requirements-driven approach, covering system testing, performance evaluation, and tools for managing system requirements. The student will explore the intersection of systems engineering, deep learning, and AI applications across various industries through research and hands-on exercises.