IDSS News November 2018
Munther Dahleh photo by Lillie Paquette MIT School of Engineering

The announcement of the new Schwarzman College of Computing is a milestone for IDSS as it is for all of MIT. Cross-disciplinary collaboration is as central to the mission of the new college as it is to us. Data science is at the core of the development of computational models that can advance research across disciplines -- and those disciplines provide insights and challenges that will advance research in data science and computing.

IDSS already serves as a bridge spanning all five schools at MIT, enabling unique research collaborations, hiring joint faculty, and launching interdisciplinary academic programs. Meanwhile, a core competency of IDSS is at the heart of computing and AI: making real-time decisions under uncertainty with real-time data. 

We look forward to expanding our role as a part of the college, and to connecting with a broader community through new collaborations. In the meantime, it is my pleasure to share these stories with you about the community we are continuing to build.

Munther Dahleh, Director
William A. Coolidge Professor, Electrical Engineering and Computer Science
The cross-disciplinary "bridge" role that IDSS plays at MIT will prove useful to the new Schwarzman College of Computing.
Learners from around the globe now have enhanced access to “blended” master’s programs at MIT and elsewhere.
Citizens and data scientists produced actionable recommendations for high-priority Boston-area issues at an IDSS student-run event during Boston's annual ideas festival.
Industry and academic leaders discussed how retailers are personalizing sales and delivering unique customer experiences with the help of machine learning, predictive analytics, and artificial intelligence.
Three Social and Engineering Systems students carry on the legacy of Michael Hammer with innovative research applying data analytics to complex societal challenges.
Schneider (SES, TPP '16) is one of 16 MIT grad students honored for their academic achievement, leadership, and commitment to addressing crucial global challenges.
Teppei Yamamoto has helped introduce conjoint analysis to the study of political cause and effect.
Rigollet uses the theory of optimal transport to address data that are whole geometric objects, with applications in medical imaging, LiDAR for self-driving cars, and more.
Sra's cross-disciplinary research explores how machine learning can improve medical imaging.
Master the skills needed to solve complex challenges with data with an MIT MicroMasters.
Turn your big data into even bigger results in this 7-week online course.
Jessika Trancik and her team uncover the factors that have caused photovoltaic module costs to drop by 99 percent.
TPP director Noelle Selin and Hélène Angot, a former IDSS postdoc, find that delays render mercury emissions-reducing policies less effective.
Media Lab professor and IDSS affiliate Iyad Rahwan explores the ethics of programming autonomous vehicles.
A look at recent insights about fake news from IDSS affiliates Adam Berinksy, Sinan Aral, David Rand, and Teppei Yamamoto.
System designed by researchers including Jonathan How of LIDS allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.
The Women in Data Science Conference (WiDS) on March 4 will feature all women speakers on data science research & applications.
SDSCon 2019, our third annual gathering of the statistics and data science community at MIT and beyond, will be held on April 5.