Master of Professional Studies in Geospatial Artificial Intelligence and Healthcare

The Master of Professional Studies in Geospatial Artificial Intelligence and Healthcare, Online is a multidisciplinary program offered jointly through the Department of Health Policy and Management in the School of Public Health (SPHL) and the Department of Geographical Sciences in the College of Behavioral and Social Sciences (BSOS) . Bringing together students to address healthcare challenges through data-driven, spatially informed decisions, the program integrates geospatial technologies, health systems, and artificial intelligence applications.

Mentoring and advising are an essential part of the program. Students meet with faculty and the academic program director to ensure that educational goals and career learning and development goals are met. Students with specific academic questions may contact Dr. Negin Fouladi via email: fouladi@umd.edu.

Overview

The Master of Professional Studies in Geospatial Artificial Intelligence and Healthcare is a 30-credit, 10-course, multidisciplinary curriculum that integrates artificial intelligence, geospatial analytics, and health science to address pressing healthcare challenges through data-driven informed solutions.

• Prepares graduates to become impactful leaders and global citizens in creating solutions while integrating artificial intelligence with geospatial intelligence to address healthcare disparities and implement data-driven solutions to improve healthcare delivery and population health.
• Addresses the growing national demand for professionals who understand and can implement spatial analysis and big data analysis in the healthcare setting.
• Successful graduates enter the field of work or service ready to address healthcare disparities, improve provision of care, and identify innovative solutions.

Program Features

Students participate in both academic and applied training.

• 30 credits (ten courses) in evidence-based approaches to addressing health systems, geospatial technologies and artificial intelligence in public health and healthcare administration.
• 15 credits (five courses) in the public health related courses; and
• 15 credits (five courses) in geospatial science and artificial intelligence.

Registration Overview

• See the sample plan of study below. Students should use this as a guide to develop a plan with the academic program director.
• Actual course offerings are determined by the program and may vary. Students should note if a course has a prerequisite or corequisite.
• Specific class meeting information (days and times) is posted on the University of Maryland’s (UMD) interactive web service, Testudo. Once on the site, select “Schedule of Classes,” then choose the term/year. Courses are listed by academic unit.
• The program uses specific section codes for registration that are listed on the sample plan of study.

Sample Plan, Full-time, Fall

Sample Plan, Full-time, Spring

For a listing of program courses, see the Graduate School Catalog program requirements for MPGH. For course descriptions that include prerequisites or corequisites, see HLSA, SPHL, and GEOG.

Overview

• Instruction is provided by UMD faculty and professionals in the field.
• Uses the semester academic calendar with classes held during the fall and spring semesters (16 weeks each) and Summer Session (two 6-week sessions).

Online Learning

• Features 100% online instruction with engaging and interactive learning.
• Using advanced audio and video technology, UMD’s online learning environment delivers dynamic and interactive content.
• Featuring convenience and flexibility, online instruction permits asynchronous or synchronous participation.
• Lectures are video archived. Students who are unable to attend in real time can review the session through asynchronous participation.

Upon successful completion, graduates will have mastered a combination of foundational public health, geospatial sciences and artificial intelligence specific competencies appropriate to their educational and professional goals.

• Evaluate the organization and delivery of healthcare systems in the U.S. and globally, and assess their impacts on population health using geospatial and AI-based approaches.
• Understand the connection among healthcare systems, public health data, GIS, remote sensing, computing, and emerging technologies such as drones, artificial intelligence, and machine learning, with a comprehensive view of their history, current application and future trends.
• Apply principles of strategic planning, program development, marketing, budgeting, management, and evaluation in healthcare and community health initiatives supported by geospatial and AI technologies. 
• Analyze health and geospatial data in diverse formats and models using advanced analytical and computational methods to identify patterns, trends, and relationships.
• Create geospatial-AI-enabled data products, tools, applications, and decision-support systems for healthcare and population management.