About Me

Welcome! My name is Rama Naboulsi. I am an Ohio State University graduate with a Bachelors in Computer Science and Engineering. I currently attend Northwestern University and am pursuing my Masters in Computer Science with a specialization in Artifical Intelligence. My hobbies include coding, reading, and travelling. I am interested in finding ways to create an impact using software engineering, data science, and machine learning. I am currently in search of a full time opportunity to help leverage my skills and grow as scientist and engineer. Check out my resume and projects below!

Rama Naboulsi

Projects

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    Optimizing Portfolio Allocation with Algorithmic Trading Strategies and Machine Learning

    SageMaker Lambda API Gateway S3 RDS SQL Docker Yahoo Finance API

    Developing a serverless application that analyzes stock trends using technical indicators, leverages machine learning and NLP for stock behavior prediction, and implements portfolio optimization techniques to maximize returns and manage risk.

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    Cooking Companion Chatbot

    NLP LLMs API Gateway RAG PineCone Prompt Engineering User-Aided Design

    Built an AI-powered chatbot that generates personalized recipes based on user preferences, and provides step-by-step cooking guidance, ingredient substitutions, and real-time adjustments based on user feedback.

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    Leveraging AI to Accelerate 911 Lifesaving Care

    Python Scikit-learn Hugging Face Fuzzy Matcher Word2Vec Whisper

    Used natural language processing and machine learning strategies to develop a real-time pipeline that classifies 911 calls into appropriate emergency types, enabling more efficient and accurate dispatch services.

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    Equity in Post-HCT Survival Predictions

    Python Scikit-survival Scikit-learn Pandas Numpy Seaborn Matplotlib

    Created a random survival forest model to predict a patient's probability of surivial over varying timeframes following Hematopoietic Cell Transplantion. Focused on promoting equity by equally weighing outcomes across all racial groups during model evaluation.

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    Chicago Car Crash Data

    Python Pandas Numpy Scikit-learn Seaborn Matplotlib

    Used exploratory data analysis as well and machine learning models to identify patterns in Chicago city traffic. Provided recommendatios to the City of Chicago based on the findings.

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    Loan Approval Prediction

    Python Pandas Numpy Scikit-learn PyTorch Seaborn Matplotlib

    Developed a machine learning model to predict whether a loan is approved using a Random Forest and Neural Network.

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    Legends of Zelda Game

    C# Monogame

    Used game design patterns and coding best practices to recreate the popular video game The Legends of Zelda

Contact

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