Teaching

“I am not a teacher; only a fellow traveler of whom you asked the way. I pointed ahead –– ahead of myself as well as of you.” – George Bernard Shaw (1908)

I enjoy teaching variety of information technology/data science/analytics courses both at undergraduate and graduate (master and doctoral) levels. I teach both online and on campus. Additionally, I advise and supervise students on independent research projects and doctoral dissertations. Scroll the page down to learn more about my teaching and impact.

Courses

Systems Analysis & Design – Undergrad and Grad Course

This course introduces the software development life cycle with a specific focus on the analysis and logical design of information systems that support organizations’ business and data-processing needs. The course covers object-oriented methods and contemporary software development approaches such as Agile methodology. Particular emphasis is on system feasibility, requirement gathering, and data modeling. Hands-on projects focusing on Unified Modeling Language (UML) and Computer Aided Software Engineering (CASE) tools to design systems solving real-world problems are an integral part of the course.

Information Storage Management – Grad Course

This course provides a comprehensive review of the processes, technologies, and tools used to manage the performance, capacity, and availability of storage resources in an IT environment. The emphasis is on the fundamentals of storage technology, including the types of storage and storage media. Challenges and opportunities in traditional and cloud-based storage management are discussed. Other topics include storage protocols, virtualization, performance monitoring, disaster recovery, green storage, and security. Hands-on labs focusing on storage management using vendor-specific and open-source storage management tools are an integral part of the course.

Advanced Data Mining and Predictive Modeling- PhD Course

This course provides a comprehensive understanding of the theoretical foundations, methodological approaches, and real-world applications of Artificial Intelligence (AI) in business and societal contexts. The course will equip students with knowledge of theoretical frameworks that guide the study and development of AI. Novel computational techniques and approaches will be explored to inform research design. Students will conduct exploratory research on AI in their areas of interest and develop a research proposal.

Student Advising

Dissertation and Thesis

Dissertation Chair

Moumita Saha, 2027 Artificial Intelligence and Disinformation

Hyein Jeong, Graduated in 2024 Assistant Professor at Rhode Island College

Master’s Thesis Chair

Archana Shinde, 2021 Machine Learning Approach to Detecting Misinformation

Dissertation Committe Member

Oyebisi Oladeji, Graduated in 2024 Assistant Professor at Kennesaw State University

Romilla Syed, Ph.D.