Computer Science and Artificial Intelligence Laboratory (CSAIL)

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Doctoral Thesis: Format Abstractions for Compilation of Sparse Tensor Algebra

Stephen Chou Abstract:Multidimensional arrays (tensors) are commonly used to represent data in many domains, including data analytics, machine learning, engineering, and the physical sciences. Many highly-optimized libraries and

Doctoral Thesis: Systems to Democratize and Standardize Access to Web APIs

Tarfah Alrashed Abstract: Today, many websites offer third-party access to their data through web APIs. However, manually encoding URLs with arbitrary endpoints, parameters, authentication handshakes, and pagination, among other

Doctoral Thesis: Compositional Robot Learning for Generalizable Interactions

Yen-Ling Kuo Abstract: To understand environments effectively and to interact safely with humans, robots must generalize their learned models to scenarios they have never been trained on before,

Doctoral Thesis: Controlling Neural Language Generation

Tianxiao Shen Abstract: Language models have achieved success in a wide range of applications such as machine translation, dialogue generation, and writing autocompletion. However, typical models operate in

Doctoral Thesis: Interactive Touch for Manipulation

Shaoxiong (Shawn) Wang Abstract:Towards helping people in daily life, robots need to better interact with our physical world and inevitably make contact with various objects. Touch provides contact

Doctoral Thesis: Enriching Digital Maps with Aerial Imagery and GPS Data

Songtao He Abstract: Digital street maps with rich features are the foundation of many applications. However, creating and maintaining up-to-date digital maps often involve many labor-intensive tasks, making

Doctoral Thesis: A Practical Approach to Federated Learning

Vaikkunth Mugunthan Abstract:Machine learning models benefit from large and diverse training datasets. However, the sensitivity of the data and government regulations such as GDPR, HIPPA, and CCPA restrict

Doctoral Thesis: Optimistic Active Learning of Action Models for Robotic Manipulation

Caris Moses Abstract: Manipulation tasks such as construction and assembly require reasoning over complex object interactions. In order for a robot to successfully plan for, execute, and achieve

Doctoral Thesis: End-to-end Learning for Robust Decision Making

Alexander Amini Abstract:Because the physical world is complex, ambiguous, and unpredictable, autonomous agents must be engineered to exhibit a human-level degree of flexibility and generality — far beyond

Doctoral Thesis: Learning State and Action Abstractions for Effective and Efficient Planning

Rohan Chitnis Abstract: An autonomous agent should make good decisions quickly. These two considerations — effectiveness and efficiency — are especially important, and often competing, when an agent