The “interdisciplinary approach” is something that has been lauded for many years for its ability to interrupt down silos and create recent integrated approaches to research.
For Munther Dahleh, founding director of the MIT Institute for Data, Systems, and Society (IDSS), showing the community that data science and statistics can transcend individual disciplines and form a recent holistic approach to addressing complex societal challenges has been crucial to the institute’s success.
“From the very starting, it was critical that we recognized the areas of knowledge science, statistics, AI, and, in a way, computing, as transdisciplinary,” says Dahleh, who’s the William A. Coolidge Professor in Electrical Engineering and Computer Science. “We made that time time and again — these are areas that embed in your field. It will not be ours; this organization is here for everybody.”
On April 14-15, researchers from across and beyond MIT joined together to rejoice the accomplishments and impact IDSS has had on research and education since its inception in 2015. Taking the place of IDSS’s annual statistics and data science conference SDSCon, the celebration also doubled as a approach to recognize Dahleh for his work creating and executing the vision of IDSS as he prepares to step down from his director position this summer.
Along with talks and panels on statistics and computation, smart systems, automation and artificial intelligence, conference participants discussed issues starting from climate change, health care, and misinformation. Nobel Prize winner and IDSS affiliate Professor Esther Duflo spoke on large scale immunization efforts, former MLK Visiting Professor Craig Watkins joined a panel on equity and justice in AI, and IDSS Associate Director Alberto Abadie discussed synthetic controls for policy evaluation. Other policy questions were explored through lightning talks, including those by students from the Technology and Policy Program (TPP) inside IDSS.
A spot to call home
The list of IDSS accomplishments over the past eight years is long and growing. From creating a house for 21st century statistics at MIT after other unsuccessful attempts, to making a recent PhD preparing the trilingual student who’s an authority in data science and social science within the context of a website, to playing a key role in determining an efficient process for Covid testing within the early days of the pandemic, IDSS has left its mark on MIT. More recently, IDSS launched an initiative using big data to assist effect structural and normative change toward racial equity, and can proceed to explore societal challenges through the lenses of statistics, social science, and science and engineering.
“I’m very pleased with what we have done and of all of the individuals who have contributed to this. The leadership team has been phenomenal of their commitment and their creativity,” Dahleh says. “I at all times say it doesn’t take one person, it takes the village to do what now we have done, and I’m very pleased with that.”
Prior to the institute’s formation, Dahleh and others at MIT were brought together to reply one key query: How would MIT prepare for the longer term of systems and data?
“Data science is a fancy area because in some ways it’s in all places and it belongs to everyone, just like statistics and AI,” Dahleh says “An important part of making a corporation to support it was making it clear that it was a corporation for everybody.” The response the team got here back with was to construct an Institute: a department that would cross all other departments and schools.
While Dahleh and others on the committee were creating this blueprint for the longer term, the events that might lead early IDSS hires like Caroline Uhler to hitch the team were also starting to take shape. Uhler, now an MIT professor of computer science and co-director of the Eric and Wendy Schmidt Center on the Broad Institute, was a panelist on the celebration discussing statistics and human health.
In 2015, Uhler was a college member on the Institute of Science and Technology in Austria trying to move back to the U.S. “I used to be on the lookout for positions in all various kinds of departments related to statistics, including electrical engineering and computer science, which were areas not related to my degree,” Uhler says. “What really got me to MIT was Munther’s vision for constructing a contemporary variety of statistics, and the unique opportunity to be a part of constructing what statistics must be moving forward.”
The breadth of the Statistics and Data Science Center has given it a novel and a sturdy character that makes for a sexy collaborative environment at MIT. “Numerous IDSS’s impact has been in giving people like me a house,” Uhler adds. “By constructing an institute for statistics that’s across all schools as a substitute of housed inside a single department, it has created a house for everybody who’s occupied with the sphere.”
Filling the gap
For Ali Jadbabaie, former IDSS associate director and one other early IDSS hire, being in the precise place at the precise time landed him in the middle of all of it. A control theory expert and network scientist by training, Jadbabaie first got here to MIT during a sabbatical from his position as a professor on the University of Pennsylvania.
“My time at MIT coincided with the early discussions around forming IDSS and given my experience they asked me to remain and help with its creation,” Jadbabaie says. He’s now head of the Department of Civil and Environmental Engineering at MIT, and he spoke on the celebration a few recent MIT major in climate system science and engineering.
A critical early accomplishment of IDSS was the creation of a doctoral program in social and engineering systems (SES), which has the goal of training and fostering the success of a recent variety of PhD student, says Jadbabaie.
“We realized we had this chance to teach a recent variety of PhD student who was conversant in the maths of data sciences and statistics along with an understanding of a website — infrastructures, climate, political polarization — wherein problems arise,” he says. “This program would supply training in statistics and data science, the maths of data sciences and a branch of social science that’s relevant to their domain.”
“SES has been filling a spot,” adds Jadbabaie. “We desired to bring quantitative reasoning to areas in social sciences, particularly as they interact with complex engineering systems.”
“My first 12 months at MIT really broadened my horizon when it comes to what was available and exciting,” says Manxi Wu, a member of the primary cohort of scholars within the SES program after starting out within the Master of Science in Transportation (MST) program. “My advisor introduced me to quite a lot of interesting topics on the intersection of game theory, economics, and engineering systems, and in my second 12 months I noticed my interest was really concerning the societal scale systems, with transportation as my go-to application area once I take into consideration the right way to make an impact in the actual world.”
Wu, now an assistant professor within the School of Operations Research and Information Engineering at Cornell, was a panelist on the Celebration’s session on smart infrastructure systems. She says that the fantastic thing about the SES program lies in its ability to create a standard ground between groups of scholars and researchers who all have different applications interests but share an eagerness to sharpen their technical skills.
“While we could also be working on very different application areas, the core methodologies, akin to mathematical tools for data science and probability optimization, create a standard language,” Wu says. “We’re all able to speaking the technical language, and our diversified interests give us much more to speak about.”
Along with the PhD program, IDSS has helped bring quality MIT programming to people across the globe with its MicroMasters Program in Statistics and Data Science (SDS), which recently celebrated the certification of over 1,000 learners. The MicroMasters is only one offering within the newly-minted IDSSx, a group of online learning opportunities for learners at different skill levels and interests.
“The impact of branding what MIT-IDSS does across the globe has been great,” Dahleh says. “As well as, we’ve created smaller online programs for continued education in data science and machine learning, which I feel can also be critical in educating the community at large.”
Hopes for the longer term
Through all of its accomplishments, the core mission of IDSS has never modified.
“The idea was at all times to create an institute focused on how data science will be used to unravel pressing societal problems,” Dahleh says. “The organizational structure of IDSS as an MIT Institute has enabled it to advertise data and systems as a transdiciplinary area that embeds in every domain to support its mission. This reverse ownership structure will proceed to strengthen the presence of IDSS in MIT and can make it a vital unit inside the Schwarzman College of Computing.”
As Dahleh prepares to step down from his role, and Professor Martin Wainwright gets able to fill his (very big) shoes as director, Dahleh’s colleagues say the actual key to the success of IDSS all began together with his passion and vision.
“Making a recent academic unit inside MIT is definitely next to unattainable,” Jadbabaie says. “It requires structural changes, in addition to someone who has a robust understanding of multiple areas, who knows the right way to get people to work together collectively, and who has a mission.”
“An important thing is that he was inclusive,” he adds. “He didn’t attempt to create a gate around it and say these persons are in and these people should not. I do not think this may have ever happened without Munther on the helm.”