Julian Fletcher

This is an ongoing project where I am implementing various data structures and some common algorithms in C++. I started this project in June 2024 to learn C++ and prepare for my research this fall and internship this spring. Programming data structures allowed me to get familiar with the syntax and standard libraries in C++ while giving me a deeper understanding of the data structures that make the world go round. I've implemented basic structures like linked lists, and more advanced structures like graphs and common search algorithms like Depth First Search and Dijkstra's Algorithm. In the future I plan to dive into tree data structures like the k-d tree, red-black tree, and more.

A practice game to convert 8-bit numbers between binary, hexadecimal, and base 10. This was originally made as a python program in for 4-bit numbers (0-15), I decided to expand it to 8-bit numbers and make it a website for easier use. It can be played here.

This is an ongoing research project I'm conducting with Dr. Jeffrey Uhlmann as a part of my involvement with the McNair Scholars Program. We're investigating an algorithm to compute least-cost paths with turn constraints.

This was a class project for Geography 3040; Intro to Geographic Information Systems. In this project I explored the relationship between homeownership rates and proximity to public transportation in Hennepin and Dakota County in Minnesota. After collecting and processing data I created a gradient to display both transit stops and the percentage of homes owned by their occupants in both counties using cencus tracts. You can view the full project poster here.

This was a class project for Geography 4940: Advanced Geographic Information Systems. In this project I gathered crash data from Huston Texas and created an atlas of maps broken down by police districts in the city. Each district map in the atlas has a “dashboard” of crash data from each district. This dashboard includes information like the average number of crashes on each road, the number of fatalities or injuries in crashes, and a graph showing the number of crashes recorded on each road within the district. The atlas includes a larger map showing the entire city, and on this map roads with more recorded crashes appear larger than those with smaller amounts—giving a great visual on where hotspots of crashes are in the city.

This was a class project for Geography 3380: Intro to Remote Sensing. In this project I utilized Sentinel-1 SAR data to detect and map flooding near Mankato, Minnesota along the Minnesota River in 2024. My workflow included the Sentinal Application Platform (SNAP) and ArcGIS Pro to process and display the SAR data from both 2023, and 2024. After classifying water pixels in ArcGIS, I overlayed the 2023 and 2024 imagery to effectively map the extent of the flooding along the river. You can view the full project poster here.