Lizhen CHEN
Jersey City,USA
Overview
3
3
years of professional experience
Work History
Research Assistant
GPH Center For Anti-Racism Social Justice
06.2022 - 08.2022
- Extract relevant data from public use data sources
- Clean and analyze data to compare over time
- Create tables, graphs, maps, figures and data visualizations that show key findings
- Complete a Tableau class at NYU’s data studio or online and using these skills, construct appropriate data visualization and create a data dashboard for project data
Research Assistant
UCSB Hayes Lab
10.2019 - 03.2020
- Introduced mutations/truncations in toxic effectors through restriction cloning, then assessed their in vivo activity through co-culture competition assays.
- Shouldered tasks of running PCRs, plasmid minipreps, making various buffers and growth media, setting up bacterial cultures and co-culture experiments
- Cloned several constructs and helped demonstrate that certain domains were critical for effector activity.
Education
Master of Public Health, Biostatistics Concentration -
New York University
New York, NY05.2023
B.A. in Economics -
The University of California Santa Barbara
Santa Barbara, CA08.2020
B.S. in Biological Science -
The University of California Santa Barbara
Santa Barbara08.2020
Skills
- R
- SAS
- Tableau
- Microsoft Office
- Problem-Solving
- Time Management
- Data Analysis
- Multitasking and Organization
- Data Entry
- Statistical Analysis
Standardizedtest
GRE, 328, 159, 169, 11/13/2020
Projects
Quantitative Analysis of Education Investment and Economic Growth, 10/2019, 12/2019, Embraced co-integration model and error correction model to analyze the relationship between education investment and economic growth in the short-term and long term. Found a mutual relationship with the lag phase between education investment and economic growth through the Granger Causal Relation Test. Proposed government increase in education investment and encourage private enterprises to invest education industry, widening the channels of education investment. Characterizing Type VI Secretion System Effectors in Enterobacter Cloacae, 10/2019, 03/2020, Dr. Hayes, UCSB Hayes Lab, USA, Introduced mutations/truncations in toxic effectors through restriction cloning, then assessed their in vivo activity through co-culture competition assays. Shouldered tasks of running PCRs, plasmid minipreps, making various buffers and growth media, setting up bacterial cultures and co-culture experiments. Cloned several constructs and helped demonstrate that certain domains were critical for effector activity. Applying Machine Learning to Business Analytics, 11/2020, 12/2020, Prof. Stephen Coggeshall, University of Southern California (online), Built ML models including overfitting, measures of goodness, feature selection, data cleaning, and feature engineering. Completed a hands-on machine learning project on a practical real-world data set to solve an applied problem. Learned Jupyter Notebooks with Python. Modified and executed Python notebooks for a wide range of modern machine-learning algorithms on practical and real-world data sets. Interpreted the data and the graph and compared ML algorithms on the data set. Analyzed the Python notebook and interpreted the conclusion and findings with a written paper. Machine Learning Project, 01/2022, 05/2022, Prof. Feng Yang, New York University, USA, Applied machine learning methods to predict customer behavior in an audiobook app, aiming to minimize churn rate and maximize company profit. Through exploratory data analysis and feature selection, I built and compared various classification models including logistic regression, linear discriminant analysis, quadratic discriminant analysis, K-nearest neighbors classification, decision tree, bagging, random forest, and boosting. Interpreted the data and the graph and compared ML algorithms on the data set. Used evaluation metrics such as classification accuracy, area under ROC curve, confusion matrix, and classification report to assess model performance, ensuring avoidance of overfitting. Thesis Research Project, 09/2022, 05/2023, Adolfo G. Cuevas, PhD., New York University, USA, Extracted data from the Midlife in the United States (MIDUS Refresher) Study. Conducted a comprehensive analysis of the biological data of 863 respondents who completed the MIDUS Refresher Survey. Using regression analysis on a subset of 318 female participants, I examined the association between depressive symptoms (measured using the Center for Epidemiologic Studies Depression Scale) and diabetes (assessed through hemoglobin A1c levels). Drafted report to interpret the data and elaborate on the implications of the study.
Languages
English
Full Professional
Chinese (Mandarin)
Native or Bilingual
Timeline
Research Assistant
GPH Center For Anti-Racism Social Justice
06.2022 - 08.2022
Research Assistant
UCSB Hayes Lab
10.2019 - 03.2020
Master of Public Health, Biostatistics Concentration -
New York University
B.A. in Economics -
The University of California Santa Barbara
B.S. in Biological Science -
The University of California Santa Barbara
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