Computer Science

Overview

Chair of the Department: Bruce MacLeod

Graduate Program Director: Behrooz Mansouri

Associate Professors: MacLeod; Assistant Professor: Mansouri; Lecturer: Amorelli; Professor Emeritus: Welty

The Department of Computer Science offers a two-year program leading to a M.S. in computer science and/or a M.S in data science. Computer science courses at the graduate level concern the practice, theory, and application of advanced software engineering, artificial intelligence (AI), and intersection of AI and software development to tackle different real-world problems. More specifically, computer scientists build, analyze, test, validate, and deploy tools that allow complex AI and/or software engineering problems to be solved. Data science courses have been designed by focusing on the high-level knowledge and skills expected from a graduate program in data science ranging from data collection and visualization to data analysis and results interpretation and accountability.

The focus of the software engineering track is large-scale software design and implementation, that is, how software is designed and built to serve a purpose. The focus of the AI track is to build, train, test, and validate AI-powered algorithms to cope with different real-world challenges. The focus of the data science track is to provide high quality opportunities for post-baccalaureate education in data science, enhancing knowledge, technical skills, and tools that can be applied immediately in the workforce.

Courses are available in the areas of databases, computer graphics, artificial intelligence, data mining, computer vision, computational text analytics, robotics, computing in data science, machine learning, statistical learning, deep and reinforcement learning, distributed systems, and computer networks.

The graduate degree in computer science and/or data science prepares students for careers in the computing profession, research and teaching accomplishments, and for higher-level graduate study in PhD, fostering critical thinking skills to apply advanced computational methods when analyzing real world problems and developing state-of-the art solutions. Course requirements ensure that students receive instruction in both practical and theoretical aspects of the graduate-level computer science and data science agendas.