Dissertation Defenses

Rescuing Data Center Processors

Automating the Detection and Correction of Failures in Modern Persistent Memory Systems

Cognitive Modeling of Aggregate and Individual Performance on the Remote Associates Test

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

Architectural Enhancements for Data Transport in Datacenter Systems

Towards Closing the Programmability-Efficiency Gap using Software-Defined Hardware

Towards Learning the Foundations of Manipulation Actions with Unguided Exploration

Enabling Hyperscale Web Services

Understanding User Cognition: from Spatial Ability to Code Writing and Review

Ride-Sharing Optimization Algorithms for Urban Commuting

A Comprehensive Computational Model of PRIMs Theory for Task-Independent Procedural Learning

Multi-task Hierarchical Reinforcement Learning for Compositional Tasks

Developing Trustworthy Hardware with Security-Driven Design & Verification

Sample efficient learning and generalization with text representations

On Learning Neural End-to-End Goal-Oriented Dialog Systems

Datacenter Architectures for the Microservices Era

Evaluating and Improving Internet Load Balancing with Large-Scale Latency Measurements

Improving the Generalization Performance of Deep Learning Models Applied to Clinical Time Series by Addressing Task Specific Structure

Expanding Task Diversity in Explanation-Based Interactive Task Learning