Doctor of Philosophy in Digital Transformation

1503770

Foundations and Frontiers of Digital Transformation

3

Prerequisite:

Grad Standing.

This course explores how digital technologies shape our social, political, and ethical worlds. Focusing on artificial intelligence, data infrastructures, and digital platformsbyexamininghow power, values, and rules are embedded in everyday digital systems. Students are encouraged to think critically about technologies not just as tools, but as socio-technical systems with real consequences for people, institutions, and communities. Through interdisciplinary readings, guided discussions, and hands-on research activities, the course develops the analytical tools needed to examine questions of accountability, equity, responsibility, and public trust.

1503771

Advanced Data Analytics Tools with Applications

3

Prerequisite:

Grad Standing.

This course covers the theoretical foundations and practical applications of cutting-edge data analytics tools, Generative AI platforms, and workflow automation technologies used in contemporary data-driven environments. It introduces students to a range of coding-free and platform-based analytics solutions, including large language models such as ChatGPT and Claude, AI-native analytics tools such as Julius, and automation platforms such as n8n, with a strong emphasis on advanced prompting strategies, agentic AI systems, and autonomous analytics workflows. The course further explores the application of these tools across key analytics domains, including exploratory data analysis, predictive modeling, data visualization, and data storytelling. Upon completion, students will be equipped to critically evaluate, select, and apply advanced analytics tools to address complex, real-world research and organizational challenges in a responsible and ethical manner.

1503772

Change Management & Leadership in Digital Transformation

3

Prerequisite:

Grad Standing.

This doctoral-level course critically examines the theoretical foundations and advanced practices of change management and leadership in the context of digital transformation. Moving beyond operational frameworks, the course explores how senior leaders shape strategic direction, institutional resilience, and long-term value creation amid technological disruption within the context of digital transformation. Doctoral students will engage with contemporary research on transformational, adaptive, and distributed leadership, digital ecosystems, and governance in complex socio-technical systems in digital space.

Emphasis is placed on developing rigorous analytical perspectives to evaluate and design large-scale transformation initiatives, including culture change, digital capability building, stakeholder orchestration, and ethical leadership in data-driven environments. Students will interrogate emerging debates on power, resistance, digital maturity, sustainability, and AI-enabled decision-making, drawing on interdisciplinary literature from management, information systems, innovation studies, and organizational theory.

Through critical analysis of global case studies, research papers, and real-world transformation programs, doctoral candidates will refine their ability to construct theoretical models, design empirical research, and contribute original scholarship to the field. By the end of the course, doctoral candidates will be equipped to advance research and practice at the nexus of change management, leadership, and digital transformation in complex organizational and geopolitical contexts, which is also expected to help the candidates be prepared for PhD thesis.

1503773

Digital Governance, Ethics & Societal Impacts

3

Prerequisite:

Grad Standing.

This course explores how digital technologies shape our social, political, and ethical worlds. Focusing on artificial intelligence, data infrastructures, and digital platforms by examining how power, values, and rules are embedded in everyday digital systems. Students are encouraged to think critically about technologies not just as tools, but as socio-technical systems with real consequences for people, institutions, and communities. Through interdisciplinary readings, guided discussions, and hands-on research activities, the course develops the analytical tools needed to examine questions of accountability, equity, responsibility, and public trust.

1503774

Emerging Research Topics in Digital Transformation

3

Prerequisite:

Grad Standing.

This course examines advanced and emerging research topics at the forefront of Digital Transformation. Students critically explore contemporary theories, socio-technical systems, and disruptive technologies, including AI, digital governance, platform ecosystems, cybersecurity, sustainability, and responsible innovation.

Through engagement with high-impact research and interdisciplinary debates, candidates identify research gaps, develop advanced conceptual frameworks, and position their work within global scholarly discourse. The course strengthens intellectual independence, methodological rigour, and strategic thinking, culminating in a publishable-quality research paper or a refined doctoral research proposal aligned with the student’s dissertation trajectory.

1503775

Directed Study in Digital Transformation

3

Prerequisite:

Grad Standing.

This course offers an individualized and in-depth exploration of a specialized topic within the field of digital transformation, allowing students to investigate emerging theories, technologies, and research methodologies under the guidance of a faculty supervisor. Emphasizing scholarly independence and critical inquiry, the course enables students to define a research focus aligned with their doctoral interests and to examine digital transformation phenomena across organizational, societal, or technological dimensions.

Students will engage with advanced academic literature, develop conceptual or theoretical models, and apply appropriate qualitative, quantitative, or mixed methods approaches. The course encourages the integration of ethical considerations, inclusive innovation practices, and data governance principles within the research process.

By the end of the course, students will have developed a research output that demonstrates intellectual rigor, original thinking, and a comprehensive understanding of a complex issue in digital transformation.

1503778

Research Methods

3

Prerequisite:

Grad Standing.

Theresearch methodscourse provides a comprehensive foundation of designing and developing research projects. It covers topics such as introduction to research in digital transformation, design thinking, project lifecycle, data collection and analysis techniques, proposal development, dissemination of research findings, emerging trends in digital transformation. In also provides knowledge and skills required to develop a well-structured research proposal. Students will collaborate closely with industry mentors who propose live, real-world projects. By the end of the course, students are expected to produce a detailed project/thesis proposal, demonstrating a clear understanding of the problem, its significance, and a roadmap for execution. This proposal lays the groundwork for the thesis or dissertation to be developed in subsequent stages of their academic journey.

1503779

PhD Qualification Exam

0

Prerequisite:

Grad Standing.

Every PhD student must pass a Comprehensive Examination designed to evaluate the breadth and depth of the student's knowledge of his or her discipline, as well as the student's scholarly potential. The comprehensive exam consists of a written exam that will be prepared, administered, and evaluated by an examination committee from the computer science department. Students taking the comprehensive exam must be in good academic standing and complete the required coursework.

1503780

PhD Dissertation

3

Prerequisite:

Grad Standing.

Students must undertake and complete independent theoretical and/or practical research under the supervision of a faculty member. Students are required to submit a dissertation documenting their research and defend it in an oral examination before a committee. The dissertation work should provide the student with advanced knowledge in digital transformation with an in-depth research experience. Students are required to produce at least two refereed publication of their work before defending the dissertation

1503665

Entrepreneurship and Business Development

3

Prerequisite:

Grad Standing.

This course examines entrepreneurship and business development in the context of digital transformation, focusing on innovation-driven ventures, scalable data-enabled business models, and sustainable value creation. It explores how emerging digital technologies reshape opportunity recognition, value proposition design, and competitive strategies in new and established organizations. The course equips PhD candidates with advanced strategic and research frameworks to design, evaluate, and manage digitally enabled ventures, drawing on contemporary theory, empirical research, and real-world case studies. Key topics include digital business model innovation, scaling strategies, venture financing, governance, and ecosystem development. The course also emphasizes responsible entrepreneurship by addressing the societal, ethical, and policy implications of digital transformation and prepares students to conduct rigorous scholarly research that informs practice and policy.

1501830

Topics in Artificial Intelligence

3

Prerequisite:

Grad Standing.

This advanced graduate course, which is similar to Topics in AI 1, explores in depth several important topics in modern AI. The course will emphasize both practical and theoretical aspects of AI such as machine learning. Appropriate areas include artificial neural network; natural language processing; machine translation; speech processing; pattern recognition, computer vision, artificial life, intelligent agents, robotics, and expert systems. We will supplement the lectures with paper discussions and there will be a significant research project component to the class to learn current research issues.

1501861

Topics in Data Analytics and Cloud Computing

3

Prerequisite:

Grad Standing.

This course involves special topics in data analysis and cloud computing. The course explores advanced/specialized topics in data analysis and cloud computing that are not currently offered as regular courses in the PhD in Computer Science curricula. The topics depend on the interest of the instructor and contents may vary at each offering. The following course description followed by the weekly topics are a specific sample for this topic course. Areas covered include cloud systems, data processing frameworks, networking, cloud data centres, state-of-the-art data processing frameworks, cloud workload characteristics, and resource management and scheduling. We will supplement the lectures with paper discussions and there will be a research project component to the class to learn current research issues.

0309725

Doctoral Management Seminar in Entrepreneurship I

3

Prerequisite:

Grad Standing.

This seminar based course appreciates the multidisciplinary nature of the field of entrepreneurship and presents an overall view of the domain of entrepreneurship and provides opportunity to students to explore major themes in the literature. The seminar critically reviews the seminal theory and research in the field of entrepreneurship addressing the fundamental issues. A selection of seminal articles, from the top ranked journals in the field by influential researchers, are included in each session for critique, discussion, and presentations. Some of the major topics covered in this seminar include the domain of entrepreneurship as a field of study, typology of entrepreneurs, institutional, resource based, behavioral, and social capital perspectives of entrepreneurship, entrepreneurial opportunities and learning, corporate entrepreneurship, entrepreneurial failure, and entrepreneurship in the global context.

0309731

Doctoral MIS Seminar in Business Analytics I

3

Prerequisite:

Grad Standing.

This seminar addresses the foundation of Business Analytics. The aim is to review and critically analyze the theoretical developments in Business analytics. In addition, it examines the most influential and innovative works that apply a range of theories and theoretical approaches in the discipline. The students are expected to participate in the theoretical discourse and debates about the relevance of Business Analytics to competitive advantage.

0309705

Behavioral Decision Making for Leaders

3

Prerequisite:

Grad Standing.

The purpose of this course is to provide students with deep understanding of how decision makers think about complex problems and what are the imperfections that limit the effectiveness of decision making. It also aims to offer guidelines and techniques for overcoming these limitations and improving the quality of decision making. The topics covered include human decision-making systems, judgmental heuristics, common biases, behavioral marketing, behavioral finance, behavioral strategy, behavioral ethics, behavioral leadership, and debiasing and improving decision making.