CLASIC Capstone Projects Showcase

CLASIC students investigate a wide variety of questions for their CAPSTONE projects, developed through internships or faculty-supervised research.

 

Mitchell Allen (2023) "DLT2: Dating Latin Texts with Deep Learning Techniques"

Sean von Bayern (2025) "Golden Retrievers: Fetching Expert Curriculum Knowledge to Enhance Pedagogical Agents"

Paul Bontempo (2026) "GraphSpect: Automating Aspect Prediction for Structured Meaning Representations"

Alvin Chen (2025) "Effects of Collaboration on the Performance of Interactive Theme Discovery Systems"

Alexis Cooper (2025) "Tree-Planted Translation for Free-Order, Case-Marking Languages"

Nicholas Derby (2026) "AutoPrompt: An Automated Prompt-Tuning Tool"

Ray Groshan (2025) "Is linguistically-motivated data augmentation worthwhile?"

Shiyue Hu (2026) "Tracing the Latent Threads: A Mechanistic Study of How LLMs Encode and Operationalize Race & Ethnicity"

Zilong Li (2025) "Modeling Native Chinese Speakers’ Acquisition of Japanese Kanji Pronunciation"

August Milliken (2026) "An Investigation of Improving Data Classification with Natural Language: Predicting Baseball Plate Appearance Outcomes"

Luna Peck (2025) "ConEm: Learning Embedded Concept Representations from LLMs"

Kushal Sai Ravindra(2026) "UtteranceIQ: A voice driven, evidence-based interview evaluator with auditable scoring"

Federico Ortega Riba (2026) "Pushing on LLMs’ Knowledge of the Caused Motion Construction"

Reece Suchocki (2023) "SCI 3.0: A Web-based Graphical Interface for Schematic Event Curation"

Mike Wang (2025) "MAMORX: Multi-agent Multi-Modal Scientific Review Generation with External Knowledge"

Jasper Wilkerson (2026) "Audio Deepfake Detection using Reflection Coefficient Vocal Track Modeling"