Former Members

Masters Students

• Moxie Broekhuis, Thesis Title TBD, Fall 2025
• Dylan Le, "Exploring Formal Methods for Provably Safe Autonomous Cyber-Physical Systems" (co-advised with Carlos Varela), Spring 2025
• Mason Sklar, "Exploring Image-to-Text Robustness of Foundation Models", Spring 2024
• Sean Patch, "Tree Identification and Segmentation" (Best Poster Winner), Fall 2023
• Matthew Crotty, "Determining Image Hardness using Ensemble Classifier Method", Fall 2022

Undergraduate Students

• John Wu, "Time-limited reinforcement learning for system recovery", Fall 2024-Fall 2025
• Meng Xin, "Time-limited reinforcement learning for system recovery", Fall 2024-Fall 2025
• Henry Ye, "Developing a fine-structure segmentation dataset", Fall 2023-Spring 2024
• Arvind Rathnashyam, "Building a tree classification dataset and developing a fine-structure classifier using graph-like segmentation", Fall 2022-Spring 2024
• Allan Wang, "Developing a fine-structure classifier using deep learning", Fall 2022-Spring 2023
• Scott Wofford, "Robustness of Neural ODEs", Summer 2023
• Shengzhe Sui, "Using ensemble methods to understand the generalization capabilities of neural networks", Spring 2023
• Chenyu Yu, "Collecting a dataset to explore the robustness of neural networks to natural perturbations", Summer-Fall 2022
• Luke Williams, "Using ensemble methods to understand the decision space of neural networks", Summer-Fall 2022

High-School Students

• Alyssum Wong, "Analyzing Autonomous Car Crash Data to Understand the Reasons for AI Failures", Spring 2023 -- Fall 2024