PhD Thesis Defense
PhD Thesis Defense: Jared Yeager, Machine Checked Verification of Validation Tests for Seldonian Algorithms
In this work we produce verified code for a Seldonian algorithm validation test.
PhD Thesis Defense: Lijun Zhang, Advanced Resource-Efficient Multi-Task Learning
This thesis addresses these challenges through a series of innovations in multi-task learning.
PhD Thesis Defense: Zack While, Broadening Data Visualization Design to People in Late Adulthood
This research advances methodologies for analyzing textual content from large-scale online datasets, interpreting message intent, retrieving knowledge...
PhD Thesis Defense: Dmitry Petrov, Structure-Aware Shape and Image Synthesis
This thesis proposes an alternative path toward intelligent control by drawing inspiration from biological systems and exploring the concept of time-aware...
PhD Thesis Defense: Blossom Metevier, Fair Algorithms for Sequential Learning Problems
This proposal addresses three problems in fair ML.
PhD Thesis Defense: Mashrur Rashik, Human-Centered Design of Contextually Appropriate Conversational Agents for Enhancing Public Interaction, Engagement, and Multimodal Experiences
This dissertation advances conversational AI by showing how multi-agent chatbots, thoughtful avatar design, and personalized interactions enhance engagement...
PhD Thesis Defense: Zafeiria Moumoulidou, Fair and Diverse Data Selection Schemes for Data Management and Visualization
In this thesis, we revisit the task of data selection through the lens of social-oriented metrics like diversity and fairness.
Data Driven Expert Assignment
Our algorithms, Greedy Expert Round Robin and FairSequence, assign experts in such a way that no request "envies" another request's assigned experts.
PhD Thesis Defense: Zitian Chen, Toward Unified Expertise: One Model for All Tasks
In this PhD Thesis Defense, Chen will explore neural network architectures that facilitate joint learning across varied tasks.
PhD Thesis Defense: Russell Lee, Learning-Augmented Online Algorithms for Energy Optimization
In this proposal, Lee will present optimal online algorithms for energy optimization in the competitive analysis setting.
PhD Thesis Defense: Shuwa Miura, Optimized Resource Allocation for Serving Deep Learning Models
This thesis introduces a unifying model for generating behaviors that not only achieve desired goals, but also account for how these behaviors are perceived.
PhD Thesis Defense: Walid A. Hanafy, Carbon-aware Resource Management for Cloud Computing Platforms
In this thesis, Hanafy proposes novel resource management techniques that allow cloud users and operators to reduce their operational carbon emissions.