PromptBeaver
Published:
Created a Streamlit prompt-engineering tool that helps students build, evaluate, and refine prompts for large language models through guided prompt analysis rather than direct answer generation.
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Published:
Created a Streamlit prompt-engineering tool that helps students build, evaluate, and refine prompts for large language models through guided prompt analysis rather than direct answer generation.
Source Code
Published:
Constructed CLiFF, a natural language processing pipeline that uses a fine-tuned large language model and semantic clustering to transform recurring technical support issues into frequently asked questions.
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Published:
Built a Streamlit application that analyzes 1,000+ machine learning job postings using natural language processing and retrieval-augmented generation to identify in-demand skills and generate personalized learning roadmaps. Manuscript submitted for publication.
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Trained a MobileNetV2 transfer-learning model to classify 104 dog and cat breeds from 29,000 images, achieving an 84% F1 score.
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Published in International Journal of Sustainable Transportation, 2025
Recommended citation: Krause Moras, B. C., Joslin, C., & Gkritza, K. (2025). Used or new electric vehicles? Public preferences and market segments. International Journal of Sustainable Transportation, 1–14.
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Published in SC ’25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2025
Recommended citation: Joslin, C., Burns, D., Ashish, A., & Barezi, E. J. (2025, November). Generating Frequently Asked Questions from Technical Support Tickets using Large Language Models. Proceedings of the SC ’25 Workshops of the International Conference for High Performance Computing, Networking, Storage, and Analysis (pp. 715–726). Association for Computing Machinery.
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Undergraduate and Graduate Course, Purdue University, The Data Mine; Caterpillar Inc, 2023
Corporate Partners Teaching Assistant
Symposium Poster
Undergraduate and Graduate Course, Purdue University, The Data Mine; Caterpillar Inc, 2023
Corporate Partners Teaching Assistant
Undergraduate Course, Purdue University, Department of Computer Science, 2023
Undergraduate Teaching Assistant
Workshop, Purdue University, Rosen Center for Advanced Computing, 2025
This introductory workshop presented the core concepts and workflows of PyTorch and TensorFlow, two widely used deep learning frameworks. Topics included tensors, computation graphs, automatic differentiation, gradient-based optimization, and the architectural and programming differences between the two frameworks.
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Workshop, Purdue University, Rosen Center for Advanced Computing, 2026
This intermediate-level workshop introduced practical methods for fine-tuning and compressing large language models. Topics included full fine-tuning versus parameter-efficient fine-tuning, Low-Rank Adaptation (LoRA), QLoRA, key LoRA hyperparameters, model quantization, and GGUF conversion for local deployment.
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