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najmulhasan-code/README.md

Najmul Hasan

BS in Computer Science with minors in Mathematics and Physics, Honors Student University of North Carolina at Pembroke

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I am an undergraduate researcher advised by Dr. Prashanth BusiReddyGari at UNC Pembroke. Previously, I worked with Dr. Shaohu Zhang (UNC Pembroke / NC A&T).

My research focuses on Natural Language Processing, specifically on understanding how large language models behave under distribution shifts, adversarial inputs, and real-world deployment constraints. I am interested in building robust NLP systems that can generalize across languages and domains.

Currently, I am working on multi-agent reinforcement learning for decentralized resource coordination, investigating emergent communication patterns and fairness in cooperative AI agents.

I have first-authored papers accepted to the NeurIPS 2025 LAW Workshop and IEEE CCWC 2026.

I'm applying to PhD programs for Fall 2026. Feel free to reach out!

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  1. sage sage Public

    SAGE: Synchronized Agents for Generalized Expertise - A multi-agent framework where AI agents research, debate, and synthesize answers together

    Python 1

  2. SummaryOne SummaryOne Public

    Modern AI-powered text processing platform with customizable summarization, translation, grammar checking, content expansion, and tone adjustment features.

    TypeScript 4

  3. text-sentiment-analyzer text-sentiment-analyzer Public

    A web application for analyzing the sentiment of text using a trained machine learning model. Tech Stack: Sentiment140 dataset with 1.6 million tweets, Naive Bayes classifier, Python, Skit-learn, N…

    Jupyter Notebook

  4. using-gemma-to-answer-common-python-questions using-gemma-to-answer-common-python-questions Public

    Using Gemma to Answer Common Python Questions | Python, Gemma-2b-it Independent Project/Kaggle Competition Entry

    Jupyter Notebook

  5. -Concrete-Strength-Prediction-using-Neural-Networks -Concrete-Strength-Prediction-using-Neural-Networks Public

    Developed a Keras-based neural network model to estimate concrete strength. Implemented data normalization and rigorous model evaluation. Executed 50 training iterations to assess model stability, …

    Jupyter Notebook