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PHONE NUMBER AVAILABLEOrlando, FL Neda Ghafourilinkedin.nedaghafourigithub/nedaghafouriEMAIL AVAILABLEEducationGraduate University of Central Florida Aug 2023  Dec 2024 Master of Science (M.Sc.) in Data Analytics. Researcher : Leveraging Large Language Models to Enhance Clinical Trial Matching for Breast Cancer Pa- tients. Takeaways : Data Preprocessing, Model Evaluation, Data Cleaning, Model Implementation, Reasoning. Undergraduate Pooyesh Inst. of Higher Edu. 2014  2017 Bachelor of Science (B.Sc.) in Civil Engineering. Payame Noor University 2007  2012 Bachelor of Science (B.Sc.) in Theoretical Physics. Technical Skills Languages: Python, Julia, R, SAS, SQL, MATLAB Tools: PySpark, Power BI, Tableau, Gephi, Microsoft Office, ETABS, SAP Machine Learning and Data Analysis: PyTorch, TensorFlow, Keras, Jax, Scikit-learn, NumPy, Pandas Technical Experience Vision and Voice-Enabled AI Assistant: Developed an AI assistant capable of responding to user queries using both voice and vision capabilities. The project integrates multiple APIs, including LiveKit API, Deep- gram API, and OpenAI API, to provide an interactive and engaging user experience. The assistant is designed to process video content, transcribe speech (voice-enabled), and generate responses using advanced language models. Video Answering and Questioning: Developed a Retrieval-Augmented Generation (RAG) application us- ing Python, LangChain, and the OpenAI API. The project involves creating an interactive system capable of answering questions based on the content of given video. Tumor Detection with Deep Learning: Conducted a tumor detection project in medical imaging, focusing on the use of pre-trained deep learning models including Large Language Models (LLMs) and Transformers, Convolutional Neural Networks (CNNs) from PyTorch and TensorFlow model zoos. Utilized The Cancer Imaging Archive (TCIA) for data acquisition aimed at identifying the most effective model for accurate tumor diagnosis, contributing to advancements in diagnostic precision and treatment strategies. Market Basket Analysis: Analysis of K-means Clustering Algorithm in E-commerce Data Segmentation. Heart Attack Risk Prediction: Analyzed and predicted heart attack risk using the Heart Attack Risk Predic- tion Dataset with 8K global patient records and employed various predictive models such as Random Forest, Logistic Regression, and SVM to optimize accuracy, focusing on health data, lifestyle choices, and socioeco- nomic factors. Data Scientists Salary Analysis: Conducted a data analytics visualization project using a Kaggle dataset of data scientists salaries, analyzing key factors influencing higher salaries from 2000 to 2024. Utilized Tableau and Power BI for in-depth analysis and visual representation. Financial Forecasting Model Comparison: Implemented and compared Linear Regression and Random Forest models for financial forecasting, focusing on accuracy evaluation through Mean Squared Error (MSE) analysis. K-Medoids Clustering Analysis: Conducted k-medoids clustering on a food dataset, involving data prepro- cessing, determining optimal clusters, and visualizing results with annotated scatter plots. Analyzed cluster distances and patterns to highlight key findings and outliers. K-Means Image Compression: Implemented the K-means clustering algorithm and applied it to compress an image, using principal component analysis (PCA) to find a low-dimensional representation of face images. PCA and Visualization: Fitted a PCA model to a normalized dataset and visualized the data through scatter plots. Book Ratings Correlation Analysis: Generated plots to analyze book data, correlating average ratings with ratings count, and using page numbers and publication years as color indicators, in both original and log- transformed formats.Professional Development Data Pipelines(ETL), DataCamp, Online Present Relational Databases and SQL, Stanford University, Online Fall 2022 Python in Machine Learning, Interdisciplinary Schools, Tehran Fall 2021 Matlab Programming, Sharif University of Technology, Tehran Spring 2021 The Health Effects of Climate Change, Harvard University, Online Spring 2021 Machine Learning, Stanford University, Online 2019 Data Structures, University of California San Diego, Online Spring 2019 Linear Algebra (3-Course Specialization), Johns Hopkins University, Online Fall 2018 Python for Everybody (5-Course Specialization), University of Michigan, Online 2017-2018 Teaching Experience Teaching Assistant, General Mathematics 1, preparing and grading homework, holding TA sessions, de- signing and grading projects, Pooyesh Inst. of Higher Edu., Qom, Iran, 2016. Teaching Assistant, General Mathematics 2, preparing and grading homework and projects, Pooyesh Inst. of Higher Edu., Qom, Iran, 2016. Teaching Mathematics to students preparing for Irans university entrance exam, Tehran, Iran, 2017  2018.