Tesla OS Supply Chain

Production Assurance Solutions team

• Worked as a machine learning research assistant, under the mentorship of Dr. Judy Gichoya, in Healthcare Innovations and Translational Informatics (HITI) Lab at Emory• Used convolutional neural networks DenseNet, ResNet, and SqueezeNet to work on binary image classification tasks• Conducted model inference on deep learning-based nnU-Net model on image segmentation tasks, benchmarked several segmentation models, and presented findings with researchers from local hospitals• Conducted model inference on Meta's Segment Anything Model (SAM) on CT and MRI images

• Work as a teaching assistant for CS 253 Data Structures and Algorithms in Spring 2022 (40 students), Fall 2022 (70 students) with Dr. Liang Zhao, and Spring 2023 (40 students) with Dr. Andreas Zufle• Hold weekly office hours and review sessions to help students reviewing lectures and debugging programming assignments• Develop deep understandings of basic data structures, dynamic programming, sorting algorithms, etc.• Grade programming assignments, online quizzes, and midterms and provide constructive feedbacks to help students understand programming concepts and hone coding skills

• Work in a team of five, led by Dr. Blake Fleischer from the Department of Quantitative Theory and Methods (QTM), to study and understand the scale and scope of housing security problems due to the COVID-19 pandemic in five core counties of the Atlanta region• Identify potential factors most highly related to evictions on a census tract level in the Atlanta region by doing literature reviews and consulting with domain experts and stakeholders (ARC)• Use Python and R to clean explanatory variable data in the year of 2019 and 2020 obtained from the United States Census Bureau and Neighborhood Nexus• Use R to analyze and visualize the relationships between eviction rate and explanatory variables (e.g. employment rate, minority rate) and also the interactions (e.g. multicollinearity) between explanatory variables• Develop and research policy recommendations based on regression analysis and past government intervention (e.g. CARES Act) to help lower eviction rate in Atlanta metropolitan region

• Worked as a data science research assistant under the mentorship of Dr. Shivani A. Patel in Emory University's Rapid Acceleration of Diagnostic-Underserved Populations (RADx-UP) project funded by National Institute of Health (NIH)• Developed and implement strategies for fraud detection for online, community-facing survey through literature review, consultation with experts, and working closely with the program investigators• Wrote R scripts to generate weekly reports of the authenticated survey data and automatically update the community profile database• Used R to create maps to visualize and analyze the trend and distribution of COVID-19 death, vaccination (one dose and fully vaccinated), and hospitalization in both the state and county level in the U.S. from January to October in 2021

• Worked in an agile team to develop an internal dashboard for hundreds of users to track data import, issue reports, and service requests• Communicated with product owner to develop various dashboard components using Angular, ensuring an intuitive user experience• Built and tested 5+ web APIs and developed a backend system using ASP .Net core and Microsoft SQL server, reducing the application response time and improving system efficiency• Conducted code reviews with various scrum teams and presented projects in front of stakeholders and senior leadership

• Practiced scrum methodology to develop a web application used by 1000+ clients to pair food and wine and design a healthy diet• Utilized jQuery and Bootstrap to build a responsive web application that provides a consistent user experience across major browsersand devices, improving user satisfaction rate by 25%• Performed web scraping and browser automation using Python on 200+ websites and improved data collection efficiency by 20%• Trained and deployed linear regression models on Amazon Redshift ML to perform wine price and revenue prediction and used machine learning algorithms to detect anomalous data

• Tutored 10-15 students per week for introductory level calculus (calculus 1 and 2) and statistics (with a one-credit lab on statistical computing using RStudio)• Assisted multivariable calculus (calculus 3) students of using Mathematica to visualize and analyze complicated quadric surfaces in 3D dimension • Instructed first-year CS students on designing final projects with Java's object-oriented programming

• Led a group of 8 international students in online international student orientation and served as a sophomore representative to give advice on academic, residential life, and social life during their first semester in college• Introduced different aspects of general education program requirements (GER) and advised international students on STEM class selection and course registration• Worked with other international mentors to create videos and facilitate online orientation activities that introduce college campus and resources to 100+ incoming international students

• Planned biweekly event “Coffee, Cupcakes, and Crafts” to strengthen international student community and promote college campus inclusiveness• Designed weekly international student program newsletters and managed social medias to highlight campus resources and opportunities and introduce faculties and staff to the international student body• Interviewed two international students and one professor or staff weekly to understand and evaluate how professors and the international student program can better support the international student body in remote learning

• Tutored TOEFL listening and writing, SAT Math, AP Calculus AB & BC, and AP Statistics for 5-10 high school rising juniors and seniors per week• Instructed students with brainstorming and outlining ideas on college application essays and guided them to research colleges more effectively based on their individual interests and potential majors• Prepared mock exams and assisted teachers with grading, communicating with students' parents on a weekly basis, and evaluating students' performances holistically to help design more efficient study plans for individual student

• Learned the basics of Python and used NumPy, Pandas, and R (RStudio) to do data analysis on 100+ datasets collected and pre-processed from steel production• Studied the basics of SQL and understood the need of building reliable databases to accurately and efficiently detect, locate, and store exceptions generated from different steps of steel manufacture• Worked with the company smart manufacturing research team to understand how machine learning algorithms like linear regression and K nearest neighbor (KNN) can help predict and detect outliers in datasets