Shanshan Gao

Durham,USA

Summary

Driven Duke University Biomedical Engineering graduate student with a strong foundation in AI and healthcare. Skilled in diverse STEM fields, particularly in machine learning and database management. Eager to apply a fast-learning approach to contribute to various STEM opportunities in a multicultural, innovative environment.

Overview

year of professional experience

Work History

Part-time Research Assistant

Benfey's Lab, Biology Department, Duke University

Durham

06.2023 - Current

Proposed and assisted in establishing detailed performance values, leading to an improvement in team efficiency and the successful early completion of the project by 2 months
Contributed to laboratory operations by developing and refining SOPs, significantly enhancing workflow efficiency through process optimization.
Facilitated onboarding and training of new team members, ensuring a smooth integration into laboratory operations.

Student Research Assistant

Prof. Jessilyn Dunn's Lab

Durham

11.2022 - 05.2023

Collaborated in the design and implementation of the preprocessing module handling digital biomarker data from 4 types of wearable digital health devices.
Streamlined data organization by developing efficient spreadsheets and databases for easy access and analysis.
Enhanced research quality by conducting thorough literature reviews on relevant topics.

Education

Master candidates: Biomedical Engineering, Data Science Concentration -

Duke University

Durham, NC

05.2024

Bachelor of Science - Chemical Engineering

Technion-Israel Institute of Technology

Haifa, Israel

06.2021

Skills

Functional: Data Analytics, Database Management, Machine learning, Data Visualization, Data modeling, Statistics Analysis
Language and Tools: Python, Matlab, SQL, MongoDB, Microsoft Office Suite

Soft Skills: Critical thinking, Time management, Organization, Attention to detail, Adaptability, Research
Others: Business Analysis, QLab (Cardiovascular ultrasound quantification software)

ACDAMIC PROJECTS

Coronary Blood Flow Estimation via 4D Ultrasound Data

Led the project on estimating myocardial volume change, involving intricate anatomical studies and advanced imaging analysis with QLAB software; pioneered a novel method for coronary blood volume computation.
Employed MATLAB for the precise reconstruction of cardiac anatomy and volumetric analysis, successfully correlating computational findings with empirical medical data.

Exploration of Machine Learning Approaches to Drug Response Prediction in Breast Cancer Cell line

Led a comprehensive study on drug response in breast cancer cell lines, overseeing data preprocessing and the application of PCA and t-SNE for feature reduction and data visualization.
Directed the development and training of multiple machine-learning models, including Lasso, SVMs, Random Forest, and Extra Trees, enhancing predictive accuracy by 10% through hyperparameter tuning.
Presented findings and methodological approaches, including the use of ROC curves and multidimensional metrics, to academic peers, demonstrating leadership in collaborative research environments.

Development of a Sleep Lab Monitoring GUI

Orchestrated the creation of an analytical module for patient's continuous positive airway pressure data analysis, integrating Fast Fourier Transform for detailed respiratory event detection and a user-friendly GUI for data input.
Engineered a secure, cloud-based data management system using MongoDB, ensuring the confidential and efficient handling of sensitive patient information

ACTIVITIES

Asia Science Camp, Organized check-in and reporting procedures for a prestigious international scientific conference. Coordinated the arrangement of meeting places for 300 scientists, including Nobel Prize winners and Wolf Prize in Mathematics winners, and students from 28 countries.

Timeline