PhD Program in Social & Engineering Systems
The Doctoral Program in Social and Engineering Systems (SES) is a unique research program focused on addressing concrete and societally significant problems by combining the analytical tools and methods of statistics and information sciences with engineering and social science tools and methods.
SES students study problems that correspond to significant societal challenges, with an emphasis on areas such as social networks, autonomous systems, energy systems, financial networks, and urban systems. This includes analytical research that can be used to inform policy making. Graduates will go on to roles in academic departments in various fields (engineering, management, operations research, and others), serve in the public sector (from research labs to regulatory agencies), as well as pursue careers in the private sector (from industry to consulting).
The first part of a student’s program consists of advanced, rigorous, and challenging classes (more details below). The lists of acceptable classes approved by the SES Graduate Program Committee (SES-GPC) will evolve as the SES program is offered, often originating from petitions by students and their advisors.
However, classes are just the first part of the doctoral program. After passing both the written and oral portion of the qualifying exam, the balance of a student’s academic activity will shift from classes to research. This immersion in research is the centerpiece of the SES program.
To get a sense of the style and variety of research that is carried out within IDSS please visit the web pages that describe some of IDSS’s domains of expertise as well as the web pages of individual IDSS faculty, senior research staff members, and students. You may also find the videos from the IDSS Launch Symposium to be quite informative about the broader vision.
Applications are due December 15. The application opens around September 15.
MIT Graduate Admissions Statement
In response to the challenges of teaching, learning, and assessing academic performance during the global COVID-19 pandemic, MIT has adopted the following principle: MIT’s admissions committees and offices for graduate and professional schools will take the significant disruptions of the COVID-19 outbreak in 2020 into account when reviewing students’ transcripts and other admissions materials as part of their regular practice of performing individualized, holistic reviews of each applicant.
In particular, as we review applications now and in the future, we will respect decisions regarding the adoption of Pass/No Record (or Credit/No Credit or Pass/Fail) and other grading options during the unprecedented period of COVID-19 disruptions, whether those decisions were made by institutions or by individual students. We also expect that the individual experiences of applicants will richly inform applications and, as such, they will be considered with the entirety of a student’s record.
Ultimately, even in these challenging times, our goal remains to form graduate student cohorts that are collectively excellent and composed of outstanding individuals who will challenge and support one another.
Questions or concerns about this statement should be directed to the academic department or program to which the prospective student has applied.
March 26, 2020
The Character of the Program
- It is driven by problems of societal interest. The focus of the program is the study of problems that correspond to significant societal challenges, with emphasis on areas such as sociotechnical systems, autonomous systems, energy systems, finance, social networks, and urban systems. This includes analytical research that can be used to inform policy making. An example of work that falls under this program would be studying systemic risk in the banking system and its impact on the overall financial system. In contrast, profit-maximizing portfolio management does not.
- It involves quantitative methods. Societal problems or policy questions can be addressed from many different angles. However, this program focuses on problems that can be addressed through tools of computing and information sciences, including mathematical modeling and analysis, data science and statistics, and other quantitative methods.
- It relies on real-world data. Research is expected to analyze data from the application domain of interest, and thus training in statistics is part of the program.
- It engages societal aspects of the problem. The research is expected to examine the societal aspects of a problem (e.g., regulations, institutions, human behavior, or economic aspects), using theories and tools from the social sciences.
The class requirements for the doctoral program follow. In some cases classes will be selected from pre-approved class lists and in other cases classes will be subject to approval by the SES-GPC.
Take 3 of the 4 following classes. With academic advisor approval, substitutions may be possible for 6.436.
- 6.436 Fundamentals of Probability
- 18.6501 Fundamentals of Statistics or
18.655 Mathematical Statistics or
IDS.160 Mathematical Statistics (for students with previous background in statistics)
- 14.121 & 14.122 Microeconomic Theory I & II
- 21A.809 Designing Empirical Research in the Social Sciences
Information, Systems, and Decision Science
5 classes. These will be rigorous classes in the areas of probabilistic modeling, statistics, optimization, and systems/control theory. Classes used to satisfy the core can be counted toward this requirement. However, the remaining classes should be at a more-advanced level. One subject must involve the statistical processing of data. One subject must have substantial mathematical content (as defined by the IDSS-GPC). Two classes must belong to a sequence that provides increasing depth on a particular topic.
4 classes. A student proposes a coherent and rigorous program-of-study in the social sciences that provides the background necessary for the student’s research. Classes used to satisfy the core can be counted toward this requirement. However, the remaining courses should be at a more-advanced level. Three classes must form a coherent collection that builds depth in a particular social science focus area.
2 classes. A student takes a total of two classes in the application domain of their research. One class may also be counted toward the social science requirement. Another class may be satisfied by an internship or independent study in which the student is graded on their performance of hands-on work in a particular domain.
Written Qualifying Exams
A student takes the written qualifying exams in December of their second year (the end of their third semester in the program). The student is examined on three of the core classes, and passes the written qualifying exams by passing each of these three core areas. Students may retake core area exams that they may have failed in May of their second year (the end of their fourth semester in the program) for a total of two attempts. In specific circumstances it may be possible to waive a core area exam if the student’s performance in the corresponding core class was strong.
Oral Qualifying Exam
Between the student’s fourth and sixth semester in the program, and after the student passes the written qualifying exams, they take the oral qualifying exam. The oral qualifying exam includes a research presentation by the student. To pass the oral qualifying exam a student must demonstrate the ability to undertake doctoral-level research and to handle questions about that research, including extensions to related problems.