Dissertation Defenses

Improving Application Connectivity with Network-conscious Systems

Assessment of Privacy Risks in Mobile and Web Applications

Application-Aware Scheduling in Deep Learning Software Stacks

Dynamic Connectivity, Hopsets, and Byzantine Agreement

Advancing Digital Safety for High-Risk Communities

The Value Equivalence Principle for Model-Based Reinforcement Learning

Context-Aware Detection and Resolution of Data Anomalies for Semi-Autonomous Cyber-Physical Systems

On Addressing the Problem of Discovery for Reinforcement Learning

Augmenting Structure with Text for Improved Graph Learning

Predictable Performance and Low Cost for Geo-Distributed Applications

Constructing Meaning, Piece by Piece: A Computational Cognitive Model of Human Sentence Comprehension

Towards Free, Open, and Ubiquitous Hardware Design

Incorporating Expert Interpretation and Reasoning to Guide Model Selection in Machine Learning

In-Memory Acceleration for General Data Parallel Applications

Improving Mobile Internet Performance with Cross-Device Network Transport and Cross-Layer Application Adaptation

Provably Efficient Reinforcement Learning under Linear Model Structures: From Tabular to Feature based Exploration

Graph Summarization Meets Representation Learning for Scalable Feature Summarization: Methods & Applications

Accelerated Systems for Pattern Matching

From Finite to Infinite: Scalable Automatic Verification of Hardware Designs and Distributed Protocols

Compiler Auto-tuning For Code Optimization

Data-Centric Execution Inspection

Optimizing Spare Linear Algebra on Reconfigurable Architecture

Provably Efficient Reinforcement Learning: From Single-Agent MDPs to Markov Games

Efficient Resource Management for Deep Learning Clusters

Cautiously Optimistic Program Analyses for Secure and Reliable Software

Enforcing Realism and Temporal Consistency for Large-Scale Video Inpainting