Computer Science and Artificial Intelligence Laboratory (CSAIL)

By: Yuzhe Yang Supervisor: Dina Kati

A CSAIL study highlights why it is so challenging to program a quantum computer to run a quantum algorithm, and offers a conceptual model for a more user-friendly quantum computer.

A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.

By: Xiang FuSupervisor: Tommi Jaakkola

By: Tobia Marcucci Supervisors: Russ Tedrake, Pablo Parrilo

By: Samuel Sledzieski Thesis Supervisor: Bonnie Berger

By: Eric Lehman Supervisor: Peter Szolovits

By: Divya Shanmugam Supervisor: John Guttag

By: Martin Nisser Supervisors: Stefanie Mueller, Daniela Rus, John Hart

By: Lei Yang Supervisor Mohammad Alizadeh

Doctoral Thesis: Machine Learning Approaches for Healthcare Discovery, Delivery, and Equity

A blueprint for making quantum computers easier to program

To build a better AI helper, start by modeling the irrational behavior of humans

Doctoral Thesis: Learning to Model Atoms Across Scales

Doctoral Thesis: Graphs of Convex Sets with Applications to Optimal Control and Motion Planning

Doctoral Thesis: Learning the language of bimolecular interactions

Doctoral Thesis: Practical Considerations For the Deployment of Clinical NLP Systems

Doctoral Thesis: Advancing Equity & Reliability in Machine Learning

Doctoral Thesis: Programming Machines and Materials for On-Demand Assembly

Doctoral Thesis: Efficient Consensus and Synchronization for Distributed Systems