Chenchen Wang Email & Phone Number

Thousand Oaks, California, United States

Westlake Village, Ca

Westlake Village, California

Classification of Parkinson’s Disease with Big Data Analytics and Ensemble Machine learning* Build a big data analytics paradigm including data exploratory analysis, data wrangling and feature construction with spark/scala/sql, hive and pig.* Use ensemble approach including both linear and nonlinear machine learning models to predict subjects with early sign of Parkinson’s Disease and patients with diagnosed PD.* Perform feature importance analysis and identify predominant clinical features.Unsupervised learning and dimensionality reduction* Two clustering algorithms, k-means and expectation maximization, and four dimensionality reduction algorithms, principal component anaylsis (PCA), independent component analysis (ICA), randomized projections, and random forests, are compared on two data sets.* R libraries were used to apply these unsupervised learning and dimensionality reduction algorithms.Assessing supervised learning algorithms* Evaluate five algorithms: decision trees, neural networks, boosting, support vector machines, and k-nearest neighbors.* R libraries were used to apply classification algorithms to two interesting data sets from the UCI machine learning repository.Predicting disposition destination in hospitalized stroke patients* Data cleaning, preprocessing, and exploratory analysis of MIMIC-III dataset.* Feature construction for time series data.* Develop machine learning models to predict likelihood of different discharge locations.Deep learning: deep Q networks (DQN)* Implement deep Q networks (DQN) using Keras and Tensorflow.* Solve the lunar lander problem in OpenAI Gym using implemented DQN algorithm.Evaluating regression model on a movie data set using R* Data preprocessing and visualization of a movie data set gathered from IMDb.* Use linear regression to predict the movie profit based on various variables (both numeric and categorical).

Santa Barbara, California Area

compressed sensing, density functional theory

Accelerating materials property predictions using machine learning* Work in a multidisciplinary university research initiative (MURI) project. Extensive experience in team-working and collaborate with different universities and groups.* Develop a similarity-based machine learning approach that can help predict the properties of a new polymer.* Develop a genetic algorithm based method for feature selection.

Master'S Degree, Computer Science, 4.0

Courses: Big Data for Health Informatics, Introduction to Health Informatics, Database Systems Concepts and Design, Data and Visual.

Doctor Of Philosophy (Phd), Materials Science And Engineering

Major Advisor: Dr. Rampi Ramprasad. Thesis: Polymer dielectrics design using first principles computations and machine learning.

Education record