Resume
Contact
- Leander, TX
- +1-346-332-6294
- nancie151@gmail.com
- linkedin.com/in/nancyluongg
- github.com/nancie151
Education
UNIVERSITY OF COLORADO BOULDER
Master of Science in Data Science
UNIVERSITY OF TEXAS AT AUSTIN
Bachelor of Science in Biochemistry, Minor in Forensic Science
Skills
Technical Skills: Data analysis, data modeling, statistics, data visualization, machine learning, deep learning, and data mining
Languages: Python (NumPy, Pandas, Keras, TensorFlow, Scikit-Learn, Matplotlib, Altair, Seaborn), R, MySQL
Visualization: PowerBI
Relevant Project
Phishing Website Detection using Deep Learning Neural Network Models
- Leveraged Deep Learning models including CNN, GRU, and LSTM for detection of phishing URLs.
- Developed and fine-tuned the neural network architectures to optimize the model.
- Achieved an accuracy score of 95.49% on an unseen dataset.
Cancer Detection Using Pathology Scans
- Utilized image processing techniques and neural network model, specifically CNN to effectively identify cancer biomarkers, contributing to early and reliable cancer detection.
- Achieved an accuracy score of 88.14% on an unseen dataset.
BBC News Classification
- Utilized TF-IDF vectorization to transform the text data into numerical feature representation.
- Employed Non-negative Matrix Factorization algorithm to extract latent topics from TF-IDF matrix.
- Achieved an accuracy score of 95.646% on an unseen dataset.
Country Categorization Based on Development
- Utilized k-means clustering and hierarchical clustering algorithms to categorize countries based on their level of development.
- Achieved a silhouette score of 0.569 for hierarchical clustering model.
Diabetes Prediction Model
- Utilized machine learning models such as Logistic Regression, KNN, Random Forest, and SVC learn to predict whether a female of at least 21 years old of Pima Indian heritage have diabetes.
- Achieved an AUC score of 85.28% through feature selection, hyperparameter tuning, and model evaluation.
Interest Rate Prediction Hackathon
- Participated in a Hackathon competition and led a team of 4 colleagues to build predictive models for interest rate.
- Leveraged a variety of algorithms including Linear Regression, Decision Trees, AdaBoost, and Gradient Boost to develop accurate models.
Work Experience
UNIVERSITY OF TEXAS AT AUSTIN
Undergraduate Student Researcher
- Employed data analytics techniques and computational screening to research infectious disease and drug discovery.
- Visualized 3D structures of protein-ligand interactions using Python and PyMOL to predict drug potency.
- Extracted and pre-processed over 40,000 chemical structures from various databases using Microsoft Excel to identify potential drug targets.
- Collaborated with lab members to analyze and interpret data.
LONE STAR COLLEGE
Mathematics Tutor
- Tutored 10 students every week with Calculus homework and assignments.
- Guided students through practice problems and high-level mathematical concepts.
- Provided students with useful learning techniques and online resources, helping students further understand the materials.