Qianqi Yan

Qianqi Yan

CS Senior @ University of Michigan

University of Michigan


Hi ! This is Qianqi Yan (严乾琪), a senior undergraduate student majoring in Computer Science and minoring in Mathematics. I expect to receive my bachelor’s degrees from University of Michigan College of Engineering and Shanghai Jiao Tong University - University of Michigan Joint Institute.

Currently, I’m working at Situated Language and Emboddied Dialogue (SLED) lab advised by Professor Joyce Chai and Jianing “Jed” Yang. I’m also advised by Professor Stella Yu and Tsung-Wei Ke.

  • Selected Courses: Natural Language Processing (A), Deep Learning for Computer Vision (A+), Machine Learning (A), Computer Organization (A), Data Structure & Algorithm (A)

Download my resumé.

  • Natural Language Processing
  • Deep Learning
  • Computer Vision
  • B.S.E. in Computer Science, 2023(expected)

    University of Michigan, Ann Arbor

  • B.S.E. in Electrical and Computer Engineering, 2023(expected)

    Shanghai Jiao Tong University


Research Assistant
Sep 2022 – Present University of Michigan

Advised by Stella Yu

Responsibilities include:

  • Create a vision model which conducts image-level recognition and segmentation concurrently.
  • Construct the hierarchy of image segmentation and language entity separately, and then match them at each level of granularity to derive hierarchical semantic segmentation.
Summer Undergraduate Research in Engineering
May 2022 – Present University of Michigan

Advised by Joyce Chai

Responsibilities include:

  • Leverage language models to resolve uncertainty in vision (disambiguating).
Research Assistant
Jan 2022 – Present University of Michigan

Advised by Joyce Chai and Jianing “Jed” Yang

Responsibilities include:

  • Design the prompting pipeline to query GPT-3 to generate actionable plans based on the goal state and environment feedback.
  • Collect 65k egocentric view - text description of goal state pairs from the FILM dataset and fine-tune CLIP model to match goal states with stored frames during inference.
ML Software Engineer Internship
May 2022 – Present

Advised by Rada Mihalcea and Spencer Vagg

Responsibilities include:

  • Suggesting and implementing methods to address people references and improve quality of summarization output
  • Deploying pipeline to transcribe recorded sales conversations and summarize them
Research Assistant
Sep 2019 – Oct 2020 Shanghai
  • Design a service robot to be applied in hospital wards which is capable of navigating itself in unknown environment based on SLAM algorithm and providing customized message to patients according to their locations in the ward.