CRC creates a few different robots each year and competes in the Rage in the Cage competition. The firmware subteam most recently worked on a sportsman bot in collaboration with one of the mechanical engineering subteams. This is a fully autonomous robot that attacks a robot opponent with the goal of destroying it and pushing it out of the arena. In the past, we've also worked on a sumobot with the primary goal of pushing its opponent out of the ring.
CUSail is an engineering project team that designs and manufactures an autonomous sailboat to compete in the SailBot International Robotic Sailboat Regatta. The boat competes in five events: Fleet Race, Endurance, Station Keeping, Precision Navigation, and Search. I worked on the boat's buoy detection, location, and navigation algorithms.
This program automates the enrollment process for Cornell's Student Center with Selenium in Python. It continually checks the student center webpage until enrollment opens, loops through the confirmation screens until the user is enrolled in all the chosen classes, then notifies the user when the process is complete. I undertook this project to learn about automation with Selenium in Python and to avoid the commotion of class enrollment periods.
I collaborated with six others on a team to make a fitness app which can be used to share workouts. I webscraped fitness exercises in Python and used Firebase to manage this data. I also contributed to a recommendation system with TensorFlow Lite in Python. This project was a learning experience for the early stages of app development and interacting with a database.
I worked on a team of four people to recreate the game UNO in OCaml. We designed a pass and play style game with both single player (against the computer) and multiplayer options. Notable features inlude an intermission screen when switching between players in a multiplayer game, which displayed the most recently played cards to the next player, and a keyboard navigation operated GUI.
"What is the value of honey production for each state?"
I built a linear regression model which aims to clarify a relationship between environmental factors
(location, honey producing colonies, yield per colony, production,
year) and financial factors (stocks on December 15th, average price per pound).
"How does honey production vary by each state?"
I built a classification model (kNN classifier) that was used to determine from what location each of the
aforementioned factors was taken. I continued with a futher analysis of how effective this model was compared to
a baseline of randomly generated predicitons.