Week 0: Introduction and Background

Hi everyone, my name is Louis. I am passionate about data science. So I decided to analyze water qualities through multiple lakes in California. My goal is to collect various types of water quality data from multiple lakes from online databases and store them in a structured database with removing any inconsistencies or redundency. Specifically, my data will be focused on temperature, dissolved oxygen, pH, and ORP.

I was first exposed to data science and machine learning with R-studio at an online summer program in UC Berkeley. From there I learned how to create the basics of data analysis through R-studio and python. In school, I studied Java in AP Computer Science A, gaining proficiency in functions, loops, data types, arrays, and algorithms. Outside the classroom, I was able to expand my knowledge in a coding platform called Leetcode. I explored more algorithms through this platform; learning computer algorithms. As I learned more complex algorithms and problems, I also started competing in the USACO contests. There, I learned algorithms and dynamic programming, soon becoming most proficient with the Breadth-First Search (BFS) and Depth-First Search (DFS) graph algorithms. These provided a rich understanding of graph theory, enabling me to analyze and manipulate graphs in-depth.

I also had the opportunity to design a Web Security Platform project in collaboration with the South China University of Technology. My team and I developed an automated static vulnerability detection tool to identify potential errors like SQL injections and packet loss in large websites and applications. We documented all the procedures, testing, results, and future improvements in a research paper. Therefore, I am familiar with all the steps and procedures involved in writing research papers.

In the summer of my junior year, I attended the COSMOS summer program, where I worked on an autonomous surface boat project and displayed water quality on a Python dashboard. For my senior project, I aim to continue this research by collecting water quality data and using Exploratory Data Analysis (EDA) to make crucial suggestions for environmental improvements.

By deciding on the variety of water quality data in multiple lakes, my project aims to display a full research paper providing a comprehensive understanding and structure for the health of the ecosystems. Storing large data files in a database allows fast and efficient access toward a specific data set. Implementing machine learning and exploratory data analysis(EDA) can provide a scientific and a systematic approach for the environment. Through EDA, I aim to draw conclusions that ensure water safety, aiming to prevent waterborne diseases and secure clean water for drinking and agriculture.