PhD Dissertation Proposal Defense
PhD Dissertation Proposal Defense: Cooper Sigrist, The New Way Forward: A Learning-Augmented Approach to Sustainable and Cost-Effective Rooftop PV Deployment
In this thesis, we show that changing current adoption trends could increase CO2 reduction by 40%, using multi-objective evolutionary learning.
PhD Dissertation Proposal: Allison Poh, A Multimodal Dashboard for Real-Time Teacher Support During Embodied Learning Activities
This thesis explores the design of a multimodal teacher dashboard that is not tied to a single activity or embodiment type.
PhD Dissertation Proposal Defense: Juhyeon Lee, Advancing Objective Motor Severity Assessment in Cerebellar Ataxias Using Wearable Sensors and Machine Learning
Cerebellar ataxias are a group of etiologically diverse neurological diseases that cause dysfunction of the cerebellum and related pathways.
PhD Dissertation Proposal: Fabien Delattre, Diffusion Priors for Inverse Problems in Computer Vision
In this thesis, we explore how recent progress in generative modeling improves solutions to inverse problems.
PhD Dissertation Proposal Defense: Bhawana Chhaglani, Privacy-Aware Ubiquitous Sensing Systems for Healthy Indoor Environments
In this thesis proposal, Chhaglani will present novel, privacy-preserving sensing systems designed to monitor ventilation rate and aerosol emissions.
PhD Dissertation Proposal: Brett Mullins, Practical Algorithms for Differentially Private Marginal Query Answering
This thesis develops and analyzes principled, efficient, and scalable algorithms for answering marginal queries under differential privacy.
PhD Dissertation Proposal Defense: Janice Yu Zhen Chen, Toward Resource-Efficient Decision-Making for Networked Systems
This dissertation focuses on developing resource-efficient decision-making policies to address key challenges in various networked systems.
PhD Dissertation Proposal: Daniel Marew, From Optimization to Learning: Developing Controllers for Dynamic Legged Robots
This thesis investigates motion planning and learning based control methods with the goal of developing robust controllers for dynamic legged robots.
PhD Dissertation Proposal Defense: Yixiao Song, Advancing AI Factuality via Comprehensive Evaluation
This thesis addresses the urgent need for more robust evaluation methodologies by developing scalable, accurate tools and benchmarks for factuality assessment.
PhD Dissertation Proposal: Edmond Cunningham, Orthogonal Coordinates for Representing Probability Density Functions
This thesis reframes low dimensional representation as a coordinate-learning problem.
PhD Dissertation Proposal Defense: Abhinav Bhatia, Learning to Think about Thinking: Metareasoning with Deep Reinforcement Learning for Efficient and Safe Decision-Making
This thesis significantly generalizes the scope of metareasoning by treating any factor that restricts an agent's ability to optimize its core objective.
PhD Dissertation Proposal: Zhanna Kaufman, Measuring and Increasing Trust in Software Systems
This dissertation develops methods for accurately measuring user trust in software and creates automated techniques for making software more trustworthy.