Investigated the peripherals and capabilities of the MSP430 microcontroller that will be used for motor and valve control for the temperature and humidity regulation of a spacecraft.

Validated sensor performance of a motor position sensor by utilizing SPI communication, and reporting the angle position and angular velocity.

Worked on automated flight software testing of the Dream Chaser spacecraft using Jenkins pipelines and custom testing frameworks that simulate flight hardware.

As a robotics researcher, it was my objective to get a working Lidar and SLAM demo using iRobot Education's Create3 Roomba. These demos would set the path to future mobile robot research at the robotics lab. My role required heavy collaboration with the people at iRobot, and I helped to improve the initial setup documentation for connecting the Create3 Roomba with a Raspberry Pi.

As an undergraduate student assistant (UGSA), I worked with 3 professors to help run productive and efficient lectures with 100+ students. On a weekly basis, I helped 30+ students with in-class worksheets and activities and made sure students had a clear understanding of Machine Learning, Data Science, and programming concepts.

Classes I helped with:

ECE 204 (Introduction to Data Science with Python) - Work with large datasets (Pandas, NumPy), data analysis (Clustering, Principal Component Analysis, Classification, Regression), data visualization (Matplotlib), ethics in data science.

ECE/CS 532 (Matrix Methods in Machine Learning) - Math topics: Linear equations, Regression, Regularization, Singular Value Decomposition (SVD), etc. Machine Learning (ML) topics: Lasso, Support Vector Machines (SVMs), Kernel Methods, Clustering, Neural Networks, and Deep Learning.

Conducted weekly drop-in tutoring sessions for various CS courses. I helped 5-10 students a week with their programming projects, and strived to solidify their understand of programming, Object Oriented Programming (OOP), Algorithms, Data Structures, version control (Git), and more.

Classes tutored:

CS 200 - Basic Java, edit-compile-run cycle, data types, control structures, basic testing and debugging, and good programming practices.

CS 300 - Intermediate Java (Interfaces, Generics, Exceptions, etc.), Object-Oriented Programming (OOP), Data Structures (Arrays, Linked Lists, Stacks, Queues, Heaps, etc.), Algorithms (Sorting and Searching), complexity analysis (Big O), recursion

CS 400 - Advanced Java (Polymorphism, Anonymous Classes, Lambda Functions), Advanced Data Structures (Hash tables, self-balancing trees, skip lists), Advanced Algorithms (Dijkstra's algorithm , DFS/BFS), version control (Git, GitHub), creating GUIs (JavaFX)

CS 220 - Basic Python, dataset processing, evaluating large datasets

CS 320 - Intermediate Python, Data Structures (graphs), A/B testing, data plotting, basic classification, clustering, optimization, and simulation techniques.