Machine Learning Research Assistant

Lucas Zhu

*****@**********.*** 352-***-**** ***0 S Eads St Arlington, VA

Education

Georgetown University Washington, DC

Master of Science in Data Science &Analytics(GPA:3.67) 2023 - 2025 University of Florida Gainesville, FL

Bachelor of Science in Statistics (GPA: 3.73) 2019 - 2023 Work Experience

Georgetown University McDonough School of Business Washington, D.C Research Assistant June 2024 – August 2024

• Cleaned and retrieved data on a healthcare dataset containing over 100,000 records using SQL queries

• Conducted exploratory data analysis (EDA) on cleaned data using Python [Pandas, Matplotlib, Seaborn] to identify patterns and detect anomalies in patient clinical data.

• Applied machine learning algorithms [Random Forest, Support Vector Machines, Convolutional Neural Network] to evaluate treatment efficacy across more than 10,000 blood cancer cases.

• Assessed model performance AUC and ROC curves, identifying statistically significant differences in treatment approaches correlated with biological indicators (e.g., tumor markers)

• Transformed complex healthcare data into three interactive dashboards using Tableau. Generated 20+ visualizations and communicated findings to non-technical colleagues, enabling healthcare professionals to quickly identify key trends University of Florida Herbarium Gainesville, FL

Research Assistant August 2022 – December 2022

• Performed comprehensive data cleaning on a plant specimen database using Python (Pandas, NumPy), which improved data accuracy by 30% and enhanced the database’s reliability for research applications.

• Used K-means clustering to group plant specimens based on key variables, providing actionable insights for research teams

• Applied advanced Excel functions to organize and analyze plant specimen data, streamlining data exploration and facilitating more efficient decision-making.

• Created visualizations with python to present clustering results, generating over 10 charts that enabled the research team to interpret patterns more effectively and design experiments more precisely. Larry Hartfield Insurance group Gainesville, FL

Data Analysis Intern May 2022-August 2022

• Actively collaborated with managers to brainstorm and identify critical analytics needs, leveraging problem-solving skills to address complex challenges and provide data-driven insights.

• Retrieved and analyzed over 50,000 data records using Python, identified anomalies, and reported findings to the company, enhancing data quality and supporting timely corrective actions.

• Developed detailed monthly reports in Excel for data aggregation and presentation, performed in-depth trend analysis, and researched emerging insurance products to inform strategic decision-making and product development. Project Experience

Machine learning and Neural Style Transfer with WikiArt

• Implemented deep learning models (AlexNet, Xception, ResNet, GoogLeNet) to classify paintings into three genres: Abstract Expressionism, Minimalism, and Contemporary Realism.

• Achieved 88.78% classification accuracy using the Xception model, leveraging depthwise separable convolutions for efficient feature extraction.

• Enhanced model generalization through data augmentation techniques, including rotation, flipping, scaling, and color adjustments.

• Applied Neural Style Transfer (NST) with VGG19 to generate AI-driven artistic transformations, blending artistic styles with existing artworks.

Skills

Programming Languages: Python (NumPy, Pandas, Scikit-learn, Matplotlib, TensorFlow, PySpark, Seaborn, PyTorch, NLTK, Keras) R (ggplot2, dplyr, purrr, tidyr, tidymodels, leaflet, timetk) SQL Data Tools & Frameworks: Jupyter, Azure Notebook, Tableau, Power BI, Git MySQL, MongoDB

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