This update focuses on the PhD program in Social & Engineering Systems (SES), which is the beating heart of IDSS. A unique interdisciplinary program, SES students address concrete and societally significant problems by combining the analytical tools and methods of statistics and information sciences with social science tools and methods. Using data to unify the multi-facets of every societal challenge, SES students are addressing a wide range of problems including smart infrastructures, misinformation propagation, social behavior impact on the spread of pandemics, and the effects of social media on political polarization. 

This fall, IDSS welcomed our 5th cohort of SES students, bringing our total to 36 (including two graduates). These remarkable individuals have helped the IDSS community take shape, and they continue to improve it through participation in efforts like our Task Force on Structural Racism, the IDSS Student Council, and the MIT dREFS program, which offers confidential, peer-to-peer support for IDSS graduate students.

Below we are highlighting some SES students not only to showcase their compelling research, but to show how SES students crossover with statistics at MIT and with LIDS, how they are supported by the Hammer Fellowship, and how they enrich our online MicroMasters program.

Admissions are now open for this competitive MIT PhD program. We are looking for excellent students who have genuine interest in our mission. If you know someone who would be a good fit, please encourage them to apply by December 15th.

I hope you enjoy reading about our students. As always, stay in touch and stay safe.

Munther Dahleh, Director

William A. Coolidge Professor, Electrical Engineering and Computer Science

The doctoral program in Social and Engineering Systems (SES) addresses societally significant problems by combining the analytical tools and methods of statistics and data science with engineering and social science tools and methods.

SES students study challenges in areas like energy systems, social networks, autonomous systems, financial networks, and urban systems. This includes analytical research that can be used to inform policy making.

Because SES student research addresses complex societal challenges in a diverse set of areas, SES faculty advisors come from departments across every MIT school and the Schwarzman College of Computing.

SES students can add the Interdisciplinary PhD in Statistics (IDPS) to their program. The IDPS requires additional classes in probability, statistics, and data analysis, along with a substantial focus on statistics in their dissertation.

Minghao Qiu is interested in environmental and energy policies with a global focus on issues involving air pollution and climate change. His research uses causal inference, statistical modeling, and atmospheric chemistry modeling to study the sustainability challenges at the intersection of energy, pollution and climate using real-world data. He is looking for postdoc and faculty positions in environmental and energy policy, sustainability, atmospheric sciences, or related fields.

Yuan Yuan researches social interactions and social networks for social good. He is especially interested in how to utilize social preference and social contagion to promote positive social interactions, and how social networks have shaped human behavior and can be reshaped by digital technologies. His research also aims to advance the methodology in Computational Social Science, and he is broadly interested in machine learning, causal inference, experimental design, and network science.

Jinglong Zhao works at the interface between optimization and econometrics, with applications in digital markets and urban logistics. His research leveraging discrete optimization techniques to develop data analytics methods has created value for his industry collaborators. He has brought both research and industry experiences into his classroom to meet students’ growing educational needs in the big-data era. Jinglong is on the academic job market this year.

SES students can work with the IDSS online MicroMasters Program in Statistics and Data Science through Teaching Assistantships (TAs). TAs gain valuable teaching experience by answering discussion forum questions from learners around the world, developing course material (e.g., data analysis projects, lecture notes, exercises), and conducting live recitation sessions.

Meet the SES TAs who are contributing to the success of the MicroMasters program, as well as providing hands-on support to our educational partners.

The Michael Hammer Fellowship program supports SES students and IDSS postdoctoral researchers in the early stages of their research careers. This initiative is made possible by a generous gift from Phyllis Thurm Hammer in memory of her late husband Michael Hammer ’68, SM ’70, PhD ’73.