Resume

Contact

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.