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Home > Academic Units > CSAM > School of Computing > Theses

School of Computing Theses

 

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Theses/Dissertations from 2026 2026

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Ordered Mini-batch Training for Differentially Private and Encrypted Logistic Regression, Ryan Leone (2026)

Theses/Dissertations from 2025 2025

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A Multimodal AI Framework for Energy Analysis: Integrating GIS, CNNs, ViTs, and LLMs, Blessing Austin-Gabriel (2025)

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Quantitative Preventive Approaches to Diabetes: Mathematical Modeling and Analysis, Rushi P. Bhatt (2025)

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Predicting Lung Cancer Severity Using Machine Learning Algorithms: Enhanced by Statistical Analysis, Esin Bilgin (2025)

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Enhancement of Offshore Wind Farms Using Geospatial Wind Data and Machine Learning in the Northeastern United States, Cristian Camilo Noriega Monsalve (2025)

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Human-AI-Collaboration-For-Coding, Siddhardha Ravi (2025)

Theses/Dissertations from 2024 2024

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Bridging NLP with Environmental Management by Sentiment Analysis and Topic Modeling on Offshore Wind Energy, Isabele Mansur Costa Bittencourt (2024)

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Feature Matching Methods Comparison with Limited Computing Power, Xu Du (2024)

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Deterministic and Stochastic Dynamics of Marine Food Webs, Julian A. Hernandez S. (2024)

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Infusing Commonsense via Knowledge Bases in Multipurpose Robotic Task Organization, Rafael Omar Hidalgo (2024)

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Predictive modeling of PM₂.₅ pollution in New Jersey, Katerina Knyazeva (2024)

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Trust in Human-Robot Collaborative Tasks, Jesse Parron (2024)

 
 
 

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