Jenna Kang

About Me

I’m a first-year Computer Science Ph.D. student at New York University (NYU), advised by Dr. Qi Sun. My research interests center on improving immersive experiences in 3-D and AR/VR applications, with a focus on accelerating and enhancing graphics systems using machine learning techniques. I am particularly interested in studying and exploiting human perception through cognitive, perceptual, and vision sciences to enhance the experience and draw inspiration from.

I am also interested in using HCI strategies for AR/VR 3-D displays, focusing on how users navigate and react within virtual spaces, investigating unique behavioral quirks to enhance immersion and interaction in these environments.

I achieved my B.S. in Computer Science at the Georgia Institute of Technology in 2024, where I was advised by Dr. Thad Starner.

Publications

• Towards Improving Real-Time Head-Worn Display Caption Mediated Conversations with Speaker Feedback for Hearing Conversation Partners
  Jenna Kang, Emily Layton, David Martin, Thad Starner
  CHI Late-Breaking CHI 2024.
  [paper]

• Evaluating Visual Perception of Object Motion in Dynamic Environments
  Budmonde Duinkharjav, Jenna Kang, Gavin S.P. Miller, Chang Xiao, Qi Sun
  SIGGRAPH ASIA Journal Paper SIGGRAPH ASIA 2024.
  [paper]

• Stepping into AR: Exploring Optimal Positioning for Monocular Head-Worn Displays for Reading on the Go
  Priyanka V Mosur, Ethan I Kimmel, Parth Arora, Rajandeep Singh, Jenna Kang, Atharva R Madiwale, Thad Starner
  UbiComp/ISWC Workshop UbiComp/ISWC 2024.
  

Research

• New York University, Advisor: Qi Sun
• Georgia Institute of Technology, Advisor: Thad Starner
  • Prototyped medical applications of head-worn displays, projecting camera output for surgical zoom with a variety of sensors
  • Quantitatively and qualitatively analyze benefits for the speaker to see their captions along with the deaf and hard of hearing user with captioning on glasses
• Emory University School of Medicine, Advisor: Anthony Law
  • Developed/trained machine learning models for vocal fold segmentation, computer vision for vocal fold paralysis detection

Work Experience

• Amazon Robotics, Software Engineer Intern (May 2024 - Aug 2024)
  Applied Machine Learning
• Amazon Robotics, Software Engineer Intern (May 2023 - Aug 2023)
  AWS: Lambda, Step Functions, CDK, DynamoDB, Cloudformation, Cloudwatch, Opensearch, API Gateway, S3, IAM
• Amazon Robotics, Software Engineer Co-op(Jan 2022 - Aug 2022)
  Kotlin, Docker, Typescript, Java, React
• CyberCrucible, Frontend Engineer Part-time (Dec 2021 - Feb 2023)
  Javascript, CSS, HTML, React, ReactJS

Teaching

• CS3001 Computing and Society Spring 2024, Teaching Assistant
• CS3001 Computing and Society Fall 2023, Teaching Assistant