Master of Public Informatics

About the Program

The Bloustein School’s Master of Public Informatics STEM-designated program provides a globally competitive state-of-the-art education in public informatics for students pursuing careers in leading advanced data analytics, machine learning, information science, and cutting-edge data-driven value creation. The MPI program provides the thought leadership and the skills needed for informatics professionals to succeed in highly demanding domain analytics and data science environments with artificially intelligent technologies. Graduates of the program bring a deep understanding of contexts, methods, and technologies into their work, with an enhanced understanding of diverse dimensions of informatics.

The MPI program imparts high-quality research and thought leadership-based education in advanced topics for better public policy analytics, urban and regional planning, and healthcare analytics. These include topics in global data analytics, machine learning, geographic information science, artificial intelligence, textual analytics and natural language processing, statistics, programming, data management, visualization, spatial analysis, domain applications, and the integration of these skills for domain-specific value creation.  

The MPI program will be tremendously valuable for both public service and corporate/business careers. Public informatics is critical for local and national policy-making, even as it is vital for corporations and businesses to leverage public informatics to guide their long-term strategy and day to day operations in sustainability, corporate governance, compliance, civic trends and insights, and public perceptions of products, services, and brands.  A high level of employment demand is anticipated for Informatics professionals based on their advanced domain-specific information and intelligence management capabilities. 


Why a Master of Public Informatics from Rutgers?

The Rutgers MPI program is suitable for students with undergraduate degrees in any field.  Applicants must demonstrate competency in one or more programming languages and skills in data management (with coursework, work experience, or by examination).  Students with appropriate backgrounds may substitute more advanced courses* for topics already mastered.

It is anticipated that full-time students may complete the 36 credit hours required for the degree in three (3) semesters (18 months).

The Bloustein School values exceptional performance and student accomplishments and regularly provides financial awards and scholarships to deserving students. Numerous competitive awards and work opportunities, such as teaching, grading and research assistantships, are also available during the academic year. All students are encouraged to apply for these.


How to Apply

Prospective students apply online and submit all application materials before the Bloustein School will review your credentials for admission.

• The deadline to apply to the Master of Public Informatics program is July 1 for fall admission.

  • Online application form
  • Application fee
  • Baccalaureate degree from a nationally/internationally accredited program
  • Official transcripts from all institutions
  • Resume/CV
  • Three letters of recommendation
  • GRE general, GMAT or LSAT test — CURRENTLY WAIVED
  • TOEFL/IELTS required for non-U.S. applicants. Scores will be accepted up to five years from their issuance.
  • Personal statement (approximately 750 words)
    Why do you want to study public informatics and what are your professional goals? Why are you particularly interested in the public informatics program at Rutgers Bloustein School? Describe your professional/user experience and background in following areas: graphics, statistics and computer science?

Courses and Topics

Core Courses

  • Theory and Practice of Public Informatics
  • Machine Learning for Public Informatics
  • Data Visualization
  • Intro to GIS – Informatics / Planning and Public Policy
  • Applied Multivariate Methods

Electives and Concentrations

Students can choose for MPI concentrations in public policy, urban planning, and healthcare, or design custom configurations in areas such as energy analytics or artificial intelligence, with appropriate permissions. A broad range of additional electives within the Bloustein School and other Rutgers University schools and colleges will be offered; some topics will be covered under future seminar, studio, and special topics courses.

  • Global Data Analytics
  • Artificial Intelligence – Practice, Principles & Strategy
  • Graphical Communication for Planners
  • Informatics Studio – Textual Analytics & Natural Language Processing
  • Informatics Studio – Independent Research & Projects
  • Urban Planning Studio
  • Public Policy Studio
  • Seminar: Special topics, cyber informatics, GIS, energy, transportation, NLU, smart cities, financial informatics, public opinion informatics
  • Public Policy Practicum I
  • Public Policy Practicum II
  • GIS – Special Topics
  • Basic Quantitative Methods
  • Additional one-credit courses: Intro to R, Intro to Python and Intro to HPC (Supercomputing)


Recent Projects in Data Analytics and Informatics

Bikeshare use in New York City dropped substantially during the initial months of the COVID-19 pandemic, but by summer of 2020 had largely recovered to pre-pandemic levels. The patterns of usage, however, have changed. In “Changes in the Pattern of Bikeshare Usage Due to the COVID-19 Pandemic,” published in the January 2021 issue of Transport Findings, research associate Haoyun Wang MCRP ’20, MPI ’20 and Robert Noland, Distinguished Professor and director of the Alan M. Voorhees Transportation Center, examined bikeshare usage in New York City during the COVID-19 outbreak.

Ride-hailing is frequently used for social, leisure, and recreational trips to destinations such as retail stores, restaurants, and sports and entertainment facilities.  This is more likely in the evening when users are dropped off at these locations and then late at night they also return home. A paper by Bloustein School doctoral candidate Sicheng Wang and Distinguished Professor Robert B. Noland looks at the elasticities of demand for ride-hailing service provider DiDi in Chengdu, China. 

In an effort to understand how changes in mobility are associated with the spread of the coronavirus, distinguished professor Robert Noland used mobility data from Google correlated with estimates of the effective reproduction rate, a measure of viral infectiousness, in “Mobility and the Effective Reproduction Rate of COVID-19,” published in the Journal of Transport and Health. The Google mobility data provides estimates of reductions in mobility for six types of types of activities and is available for all states and the District of Columbia.

As bikesharing systems have proliferated, few studies have examined the trips made on these systems. Researchers examine trips between origin-destination pairs during three months in 2015 on New York City’s Citi Bike system. Findings suggest considerable variation across user types, across months, and across times of day. Principal findings indicate that bikesharing is used for transit access and egress during rush hours, and that stations located along the same high-quality bicycle route see far more trips than do other station pairs. 

Cities around the world and in the U.S. are implementing bikesharing systems, which allow users to access shared bicycles for short trips, typically in the urban core. Yet few scholars have examined the determinants of bikeshare station usage using a fine-grained approach. Researchers examine the of effects bicycle infrastructure, population and employment, land use mix, and transit access separately by season of the year, weekday/weekend, and user type (subscriber versus casual). We find that bikeshare stations located near busy subway stations and bicycle infrastructure see greater utilization, and that greater population and employment generally predict greater usage.

Using data from anonymized mobile devices and building footprints, we examined how mobility patterns changed in NJ for the period of March 1, 2020, to May 17, 2020. This two and half month span includes the period with the maximum restrictions on individuals and businesses.

This cyberinfrastructure captures real-time or close-to real-time data on social and economic effects of COVID-19, and brings data streams on different sectors together to support decision-making by local and regional governments and private companies in a holistic fashion for a robust recovery.


Careers for Data Scientists and Data Analysts

The U.S. Department of Labor’s Bureau of Labor Statistics reports that the 2014-24 job outlook for data analysts is expected to grow by 30% (much faster than the average), with almost 28,000 new jobs needing to be filled in this area. Management analysts will add an additional 103,400 jobs (a 14% increase). A report by the National Science and Technology Council of the Executive Office of the President stated “…a national Big Data innovation ecosystem needs a strong community of practitioners across Federal agencies to facilitate rapid innovation, ensure long-term propagation of ideas, and provide maximal return on research investments.”

In addition, prospective employers routinely express interest in students to fill positions related to public informatics. The following organizations have recently posted job openings with the Bloustein School’s Student and Academic Services Office and Rutgers University that require a public informatics background:

  • AARP
  • Applied Energy Group
  • Deloitte
  • Delaware Valley Regional Planning Commission
  • Eurostat
  • Federal Transit Administration
  • Johnson and Johnson
  • Mathematica Policy Research
  • MDRC
  • Port Authority of New York New Jersey
  • United Nations
  • United Nations Development Programme
  • UN Office of the High Commissioner for Human Rights
  • U.S. Department of Health & Human Services
  • World Bank
  • World Economic Forum
  • WSP USA

Bloustein School MPI graduates will also be able to pursue career opportunities in informatics, analytics, and AI, all of which are expanding rapidly with above-average salaries in a wide range of government institutions, businesses, companies, NGOs, social organizations, entrepreneurial initiatives and startups, and multinational corporations.