AI and Data Science: Leveraging Responsible AI, Data and Statistics for Practical Impact
Uncover data’s true value and make data-driven business decisions with data science techniques and AI tools. Learn from MIT faculty with mentorship from industry practitioners. READ MORE
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More: IDSS brings together research and expertise
Institute for Data, Systems, and Society (IDSS) is committed to addressing complex societal challenges by advancing education and research at the intersection of statistics, data science, information and decision systems, and social sciences.
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Computational tools for society’s most complex challenges
IDSS faculty Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
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MIT Transit Lab to develop an AI platform for public transit agencies
IDSS faculty Jinhua Zhao joins project to unify public transportation agencies’ real-time monitoring, operations control, and passenger communication systems to improve information speed and accuracy.
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From Autonomous Cars to Autonomous Agents: The Five Levels of AI Agent Autonomy
Researchers including IDSS faculty Ramesh Raskar examine the autonomous-vehicle industry’s framework for AI agent autonomy, and how a similar structure could help develop policies on supervision and accountability for AI agents in the future.
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MIT researchers are mapping extreme weather risks — and building tools to act on them
A research team including IDSS faculty Jessika Trancik examines impacts of extreme weather on the electrical power system and ways to optimize decisions on the placement and sizing of new energy infrastructure.
SES10: Tenth Anniversary Symposium of the SES Doctoral Program
SES alums, students, and advisors are invited to celebrate SES’s 10th anniversary.
Deep Kernel Aalen-Johansen Estimator: An Interpretable and Flexible Neural Net Framework for Competing Risks
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George Chen, Carnegie Mellon University – Heinz College