Ph.D. Dissertations - Joseph Gonzalez
Building Agentic Systems in an Era of Large Language Models
Charles Packer [2024]
Ensuring Data Freshness Across Clouds for Model Serving
Sarah Wooders [2024]
Scalable and Efficient Systems for Large Deep Learning Models
Lianmin Zheng [2024]
Structured Contexts For Large Language Models
Kevin Lin [2024]
Teaching Large Language Models to Use Tools at Scale
Shishir Patil [2024]
Accelerating Electronic Structure Calculations with Machine Learning
Daniel Rothchild [2023]
Towards Robust and Scalable Large Language Models
Paras Jain [2023]
Efficiently Designing Efficient Deep Neural Networks
Alvin Wan [2022]
Safe Reinforcement Learning Using Learned Safe Sets
Brijen Thananjeyan [2022]
The Serverless Datacenter: Hardware and Software Techniques for Resource Disaggregation
Nathan Pemberton [2022]
The Design of Dynamic Neural Networks for Efficient Learning and Inference
Xin Wang [2020]
The Design and Implementation of Low-Latency Prediction Serving Systems
Daniel Crankshaw [2019]
Machine Learning for Automatic Resource Management in the Datacenter and the Cloud
Neeraja Yadwadkar [2018]
Alternate Representations for Scalable Analysis and Control of Heterogeneous Time Series
Francois Belletti [2017]