Computer Science and Artificial Intelligence Laboratory (CSAIL)

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The headshots of all six MIT-related Fellows for ACM 2022.
January 27, 2023

Six With Ties to MIT Honored as ACM Fellows

Six distinguished scientists with ties to MIT were recognized “for significant contributions in areas including cybersecurity, human-computer interaction, mobile computing, and recommender systems among many other areas.”

Doctoral Thesis: Context and Participation in ML

Harini Suresh Abstract: ML systems are shaped by human choices and norms, from problem conceptualization to deployment.  They are then used in complex socio-technical contexts, where they interact

Christina Delimitrou

Assistant Professor, [CS]

delimitrou@csail.mit.edu

Office: 32-G738

​Doctoral Thesis: Towards Scalable Structured Data from Clinical Text

Monica Agrawal Abstract: The data in electronic health records have immense potential to transform medicine both at the point-of-care and through retrospective research. However, structured data alone can only

Doctoral Thesis: Specification and verification of sequential machines in rule-based hardware languages

Thomas Bourgeat Abstract: The design of correct hardware is an important concern in the age of information, where more and more companies are designing chips tailored to their workloads.

Doctoral Thesis: The Lottery Ticket Hypothesis: On Sparse, Trainable Neural Networks

Jonathan Frankle In this thesis defense, I will present my work on the “Lottery Ticket Hypothesis,” which provides a new perspective on understanding how neural networks learn in

Doctoral Thesis: Volumetric Mapping for Medical Imaging and Geometry Processing

Mazdak Abulnaga Abstract:Mapping is a central problem in medical imaging and computer graphics. Most methods for this task apply only to two-dimensional (2D) surfaces. The neglected task of

Doctoral Thesis: Untangling the complexity of nature: Machine-learning for accelerated life-sciences

Adam U. Yaari Abstract:  Biological mechanisms are convoluted and stochastic systems that remain largely misunderstood despite centuries of rigorous scientific work. Machine-learning (ML) is a powerful framework to

Doctoral Thesis: Risk Aware Planning and Probabilistic Prediction for Autonomous Systems under Uncertain Environments

Weiqiao Han Abstract: This thesis considers risk aware planning and probabilistic prediction for autonomous systems under uncertain environments. Motion planning under uncertainty looks for trajectories with bounded probability

November 14, 2022

Three from MIT named 2023 Rhodes Scholars

Jack Cook, Matthew Kearney, and Jupneet Singh will begin postgraduate studies at Oxford University next fall.