Hi! I’m Jody. I'm a rising junior at Rensselaer Polytechnic Institute pursuing a dual major in Computer Science and Information Technology and Web Science.
I decided to go into computer science because I enjoy problem solving, working through unique challenges, and being creative. As an avid learner, I like that there is always the opportunity for growth within computer science. Not only do I find coding fun, but I can have an impact at the same time.
Outside of school, I enjoy hiking, swimming, skiing, and spending time with family and friends.
To excel in a challenging and impactful software engineering internship
Bachelor of Science in Computer Science and Information Technology and Web Science, GPA 3.96/4.00
High School Diploma, GPA 4.95/5.00
During this course, I learned various programming concepts and how to apply mathematical tools like order notation to evaluate the efficiency of a program. I was also introduced to several data structures, including binary search trees, heaps, maps, hash tables, and linked lists. I was able to apply these structures and principles to challenging homework and lab assignments using C++.
This course was my first taste of a college computer science course. I learned how to design basic computer programming algorithms as well as how to use a top-down approach to tackle complex problems. I applied these concepts to homework and lab assignments using Python.
This course introduced me to the growing and interdisciplinary field of cognitive science. I learned how unique fields like philosophy, psychology, computer science, neuroscience, and linquistics intersect. This course confirmed my interest in pursuing a minor in Cognitive Science. As a student who is curious about artificial intelligence and machine learning, I believe that supplementing my computer science degree with courses related to cognitive science will enable me to explore these interests.
I am currently a Software Development Engineer intern within Amazon Web Services.
I have been an undergraduate researcher at the Cognitive and Immersive Systems Lab (CISL) since September 2020. CISL is a collaboration program between RPI and IBM Research that advances research and development across a variety of disciplines.
As a sales associate, I greeted shoppers, attended to customer needs, and organized displays. I exhibited responsibility, punctuality, and effective communication skills. I found my time at Kohl's to be a valuable experience.
I worked in the kitchen as a volunteer at my local senior center. My responsibilities included setting the tables, preparing and serving meals, and cleaning up in the kitchen. I made connections with my co-volunteers and enjoyed interacting with guests.
ACM-W supports and celebrates the participation of women in all aspects of the computing field. The RPI chapter provides students with programs and services to educate them about opportunities in computer science and aid their professional growth.
The RPI chapter of the Food Recovery Network fights food waste and hunger by recovering food from dining halls and delivering it to local shelters. As a volunteer, I participate in food recoveries. I am also developing a website for our chapter to facilite weekly sign ups and recruit new members.
RCOS enables students to participate in open-source projects that solve real-world problems. As a member, I have gained experience in the code review process and have learned how to discuss the technical and non-technical aspects of a project. I participate in RCOS for course credit.
Coding&&Community is a student-run organization that aims to close the disparities in computer science education, especially relating to race, ethnicity, gender, and socio-economic status. As an instructor, I teach weekly Python lessons to middle and high school students through RPI STEP (Science Technology Entry Program).
Over the course of a few months, I utilized the Alteryx community learning academy to familiarize myself with the fundamentals of Alteryx Designer, which is a data analytics tool that enables data preparation, blending, and analysis. I learned about the functionality of various tools, how to configure them, and much more. This experience gave me a newfound understanding of the power of data transformation.
I took an online Java course to further diversify my knowledge of programming languages. I acquired core Java skills, including polymorphism and inheritance, object-oriented programming, generics, concurrency, and lambda expressions. In this course I was also introduced to JavaFX, unit testing using JUnit, Java Database Connectivity (JDBC), and networking.
During a Cloud Study Jam hosted by Developer Student Clubs RPI, I had free access to Google's online cloud labs and was introduced to Google Cloud Essentials through a hands-on introductory-level quest. I learned key concepts, such as how to write Cloud Shell commands and create virtual machines.
This summer I volunteered for and was selected to co-develop a website with six other students that will help RPI students explore their humanities curriculum options. I am currently working on the user interface for our website using Vue.js, a framework with which I had no previous experience or knowledge. My teammates and I utilized routing, state management, and local storage to ease and improve the user experience. Through participating in this project, I have learned the importance of effective communication and time management as well as how to work with students of varying levels of experience. As an entirely virtual endeavor, this experience has been both challenging and fulfilling, and I am excited to take on similar opportunities in the future.View on Github
The Machine Common Sense program broadly aims to address the absence or presence of common-sense knowledge in AI machines. The more specific objective is to identify and explore knowledge sources, including Web Data Commons (WDC). These sources provide information and relationships that describe how language is actually used in the world. As an undergraduate researcher, I analyzed these sources, writing Python scripts to extract data from them. More specifically, I parsed out spatial data from a corpus of WDC product information. My work contributed to a large-scale common-sense knowledge graph, or network of semantic relationships. I also participated in a virtual research project symposium by submitting a presentation of my work.View on Github View presentation