PhD Thesis Defense
PhD Thesis Defense: William Rebelsky, Working Towards Universal Computational Literacy
This dissertation categorizes skills that fall under computational thinking and describes our work towards improving student learning and engagement.
PhD Thesis Defense: Spencer Lane, Tools for Aggregating, Filtering, Sorting, and Auditing Social Media
This dissertation argues for a different approach to sorting and filtering social media feeds.
PhD Thesis Defense: Erica Cai, From Text to Networks: Enabling and Investigating Social Measurement via Low-Resource Knowledge Graph Extraction
The thesis is motivated by the challenge of extracting structured instances of action or relationship occurrences from large amounts of unstructured text to...
PhD Thesis Defense: Bin Wang, Resource Allocation for Latency-Sensitive Applications in Edge Environments
In this thesis, Wang addresses this gap by presenting model-driven resource allocation algorithms for latency-sensitive applications...
PhD Thesis Defense: Hamza Elhamdadi, Calibrating Trust in Visualization through the Manipulation of Visual Complexity
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: Priyanka Mary Mammen, Enabling Scalable Sleep Monitoring with Mobile Sensing and Machine
This thesis focuses on addressing the challenges of sleep monitoring at the community level by developing scalable, personalizable, and robust sleep detection..
PhD Thesis Defense: Shib Dasgupta, Box Embeddings as Set-theoretic Representations for Information Retrieval and Recommender Systems
I develop a Gumbel random process-based approach that improves the optimization landscape, resulting in a more stable and expressive variant of Box Embedding.
PhD Thesis Defense: Yixiao Song, Advancing AI Factuality via Comprehensive Evaluation
This thesis develops scalable, accurate tools and benchmarks for factuality assessment that set higher standards for AI evaluation.
PhD Thesis Defense: Weiqi Feng, Practical Encrypted Databases with Oblivious and Expressive Query Processing
This dissertation addresses challenges to encrypted databases through the following contributions: obliviousness and query expressiveness.
PhD Thesis Defense: Oindrila Saha, Fine-Grained Reasoning With Limited Supervision
This thesis advances fine-grained reasoning under limited human supervision through several complementary approaches.
PhD Thesis Defense: Khoshrav Doctor, Learning Structure to Support Autonomous Control Decisions
This dissertation examines techniques for learning structure and discusses how the resulting background knowledge is used in decision making under uncertainty.
PhD Thesis Defense: Juan Altmayer Pizzorno, Efficient and Effective Test Generation and Type Inference for Python Applications
This dissertation explores how low-overhead dynamic analysis can be used to improve the reliability of Python software.