- Provided support to organization leadership, such as providing member feedback, project ideas, and organizing events to improve member satisfaction and build community- Advised members on various computer science topics, academic paths, and recruiting guidelines to assist in their future careers

- Engaged over 200 club members through the organization of weekly Hack Nights, social events, and company outreach events- Coordinated a team of 20 leads to assist in developing meaningful projects for members- Collected feedback from various members and leads to establish new initiatives and improve the experience for all members

- Taught others about how to use Android Studio to create mobile applications, as well as general software development strategies.- Directed a team of 10 students to create an app, “Hungr,” which uses object oriented programming to connect people with local restaurants.- Responsible for managing the development of the app, assigning roles, teaching members, and helping wherever needed.

- Organized a team of 10 students to develop a mobile application using React Native for the Michigan Daily, a student-run newspaper on campus- Distributed tasks and managed the timeline for releasing new features- Coordinated and collaborated with product design managers to enhance user experience

- Collaborated with a team of students to develop a mobile application using React Native- Enhanced the user experience by adding customizable themes for the application- Conducted user testing and improved the application based on user feedback

- Developed a modernized version of MCommunity (mcommunity.umich.edu), the University of Michigan’s online directory, in Angular to improve user experience, accessibility, and mobile device friendliness- Upgraded and documented the MCommunity API in Django to allow university members to interact programmatically with the directory- Improved user experience by implementing a trash feature to avoid accidental deletions of groups, reducing service calls to the help desks- Assisted other interns with frontend and backend development, UI design, and presentations to enhance their learning experiences

- Conducted research under Prof. Carol Flannagan and Kathleen Klinich on the Data Elements from Video using Impartial Algorithm Tools for Extraction (DEVIATE) to analyze motion sickness in autonomous vehicles- Maintained and enhanced an internal data labeling tool used to provide data to machine learning algorithms- Developed a computer vision script to track head gaze in passengers to gauge motion sickness

- Execute advanced computer science lesson plans ranging from basic data structures to applied programming over Zoom for students ages 8-18, adapting to student needs and interests.- Regularly communicate with parents, providing updates on student progress and results from learning assessments.- Maintain thorough records for each student, covering multiple courses and skill level progression.

Graded homework and projects for MATH 214: Applied Linear Algebra

- Worked as a developer for the Identity and Access Management team- Enhanced the university password recovery web application by collaborating with team members using Python with Django, which improved security and user experience for university sponsored affiliates, and saw 334 users after three weeks in production.- Analyzed a database of 100,000 entries to discover potential conflicts to address during the university’s transition to a new directory group management system.- Developed and presented open-source Python programs for perfSONAR, a network measurement toolkit used by researchers worldwide.

Member of the Philadelphia Young Artists Organization as a violinist from 2016-2019, and a member of the Philadelphia Youth Orchestra from 2019-2020.

- Completed rigorous courses in stem cell biology, cybersecurity, discrete mathematics, organic chemistry, and special relativity- Took elective courses in laser technology, projective geometry, and the science of music- Took a lab course in machine learning, covering topics such as supervised and unsupervised learning algorithms (including support vector machines, naive Bayes classifiers, and K-means clustering), reinforcement learning methods (including genetic algorithms and Q-learning), ensemble methods, neural networks, and deep learning structures (including convolutional and recurrent neural networks)- Led a team project to research the mathematics of the card game “Cheat” and implemented unsupervised learning algorithms to create an artificial intelligence to play the card game, and published a research paper about the topic in the 2019 PGSS journal, Volume 34