Professional Experience

Quality Assurance, Reserach, and Social Work

Quality Assurance internship

Background: I worked as an intern in an AI startup using the Agile Software Development model

Task: Work with the Quality Assurance team to ensure that the firm's products meet industry standards and provide a good user experience

Actions:

  1. Conducted daily regression tests to identify User Interface (UI) and User Experience (UX) issues
  2. Used Project-Management Software (ClickUp) to create, maintain, and re-test a backlog of bugs and feature requests
  3. Reviewed live user session recordings (LogRocket) to discover UX pain-points
  4. Discussed ideas and prototypes for possible improvements with Project Managers and Development Leads
  5. Investigated the use of Contrastive Loss functions and in Large Language Model (LLM) development with the Natural Language Processing (NLP) research team

Results:

  1. Reported and re-tested more than 100 bugs!
  2. My UI & UX suggestions made it into the final product!
  3. I used Figma created prototypes for my design ideas and shared them with the developers
  4. I took responsibility and filled in when members of my team are unavailable
  5. I participated in daily standup meetings to receive project updates and raise UI/UX concerns

Legal Lingo

Background: My team and I were tasked to address a social problem using deep learning methods. We drew on our shared experience of translating English documents to our parents, who were not as familiar with the English language as us

Research Task: (1) Create a translation tool tailored to the high-stakes nature of legal documents (2) Pitch and present our idea to a audience of judges, educators, and industry leaders

Actions:

  1. Created Legal Lingo, a web-based translation tool
  2. Developed the OCR module to scan images of legal documents users uploaded
  3. Interviewed members of my community who face similar challenges to understanding legal documents in a foreign language to identify pain-points
  4. Discussed with project mentors to identify and address limitations and problems in our project
  5. Met weekly to design and troubleshoot our product
  6. Created and practiced our presentation pitch with professional communicators

Results:

  1. We developed Legal Lingo, a high-impact tool to advance social justice and inequalities brought by language barriers
  2. Our project won the 2022's FutureMakers Create-a-thon
  3. We presented at the 2023 ASU-GSV summit to educators, investors, and industry leaders

Teaching Assitant for Natural Language Processing class

Background: I joined the Natural Language Processing class as a teaching assistant

Task: (1) Grade homework and exams (2) Hold officer hours

Actions:

  1. Held officer hours to answer questions and provide guidance
  2. Graded homework and exams using GradeScope
  3. Created a PyTorch tutorial based on pain-points I observed from grading and from office hour conversations

Results:

  1. Every student I helped made significant progress in their homework problems!
  2. Students made much more progress in their coding tasks and implemented more complex neural network models Previously, they struggle with the process and structure of training neural networks in PyTorch and spend much more time than they would like