Alexander “Sasha” Rakhlin PhD ’06 has been named the next director of the MIT Statistics and Data Science Center (SDSC), placing a longtime member of the center’s community in charge of one of MIT’s key hubs for statistics, data science, machine learning, and AI.
Rakhlin is the Distinguished Professor in Data, Systems, and Society at the MIT Institute for Data, Systems, and Society (IDSS), as well as a professor of brain and cognitive sciences at MIT. His new role builds on years of work with SDSC students, faculty, and interdisciplinary research programs.
A leadership change at SDSC
Rakhlin succeeds Ankur Moitra, the Norbert Wiener Professor of Mathematics, associate director of the IDSS, and a faculty member in the MIT Department of Electrical Engineering and Computer Science (EECS). Moitra has been SDSC director since 2021.
Philippe Rigollet, the Cecil and Ida Green Distinguished Professor of Mathematics and a core faculty member in IDSS, also served as interim director in 2024-25.
The center is housed within IDSS, and its work sits across several major academic areas at MIT. That positioning matters because statistics is not treated here as a single-department specialty. It is described as a shared method for connecting fields that may otherwise approach problems from very different directions.
Fotini Christia, the Ford International Professor of the Social Sciences and director of IDSS, framed Rakhlin’s appointment around both research depth and mentorship. She called him “one of the sharpest theoretical minds working in statistics and machine learning today” and “one of the most devoted mentors I know.”
Why Rakhlin fits the moment
Rakhlin’s connection to SDSC goes back to 2016, when he was a visiting professor. He formally joined MIT in 2018 in the Department of Brain and Cognitive Sciences and IDSS.
He also served as the initial chair of the Interdisciplinary PhD in Statistics program at SDSC. In that role, he has seen the successful defense of over 75 IDPS PhD students across a variety of departments at MIT, including IDSS’ own Social and Engineering Systems program.
That background gives his appointment a practical dimension. Rakhlin is not arriving as an outside administrator. He has already worked inside the academic structure that connects SDSC to departments and research communities across MIT.
He is also the inaugural holder of the Distinguished Professorship in Data, Systems, and Society. The endowed chair was created in 2025 by the generosity and vision of IDSS professor Richard “Dick” Larson, described as an “MIT lifer” and pioneer in operations research, queueing theory, and system optimization.
AI makes statistics more central
Rakhlin’s own comments point to why SDSC’s mission is gaining importance. He said he has been fascinated by machine learning since his PhD work more than 20 years ago, especially because of its connections to statistics, probability, algorithms, optimization, and game theory.
In his view, AI is expanding those connections into the sciences. The promise is faster discovery, but the challenge is that the tools themselves need a rigorous foundation.
That puts statistical and mathematical questions at the center of AI’s future. The source identifies several areas where those questions matter:
- Quantifying uncertainty
- Providing guarantees
- Understanding failure
- Resisting manipulation
Rakhlin connected those issues directly to AI entering medicine, energy, and public life. The implication is clear: as AI systems move into consequential settings, technical performance alone is not enough. Researchers must also understand where systems can fail, how confidence should be measured, and what kinds of guarantees can be supported.
That emphasis fits SDSC’s broader identity. The center works at the intersection of statistics, machine learning, AI, and data science, but it also serves communities whose main questions may come from science, engineering, economics, political science, or other fields.
An interdisciplinary bridge across MIT
Rakhlin described statistics as “a shared language across MIT.” Through the Interdisciplinary Doctoral Program in Statistics, SDSC connects students and faculty from economics and political science to physics and engineering.
The source also points to collaborations in areas from biology to nuclear fusion as examples of how statistical thinking can accelerate science itself. That is a broad claim, but within the article it rests on SDSC’s role as a meeting point for people working on different kinds of problems with common analytical tools.
As director, Rakhlin aims to deepen these interdisciplinary connections. He hopes to help make SDSC the Institute’s home for the rigorous foundations of data science and AI, while also making it a bridge to scientific and societal questions where those foundations are most needed.
His academic path reflects that cross-field orientation. Rakhlin received his bachelor’s degrees in mathematics and computer science from Cornell University and his doctoral degree from MIT. He was a postdoc at the University of California at Berkeley in EECS before joining the University of Pennsylvania, where he was an associate professor in the Department of Statistics and co-director of the Penn Research in Machine Learning center.
The appointment therefore brings together several threads: theory, machine learning, statistics, AI, doctoral education, and cross-campus collaboration. For SDSC, the next phase appears focused on strengthening the mathematical foundations behind data science while keeping those foundations connected to real scientific and societal problems.