About

I am a Ph.D. student at Interactive Intelligent Systems Lab (IIS-Lab), The University of Tokyo, supervised by Koji Yatani. I received my master's degree in the same lab at The University of Tokyo in 2020, and B.S. at Shanghai Jiao Tong University, supervised by Xinyi Le.

My research interest is Human-computer Interaction (HCI), Computer Vision (CV), and Machine Learning (ML). I primarily study Interactive Machine Teaching, creating technologies to empower human intelligence during the creation of their customized ML models. I also conduct research related to human pose/gesture detection, low-level CV, and foundational models.

Be free to email me if you want to collaborate or discuss with me about those research!

News

Publication

Papers

DIPA2: An Image Dataset with Cross-cultural Privacy Perception Annotations
SoundTraveller: Exploring Abstraction and Entanglement in Timbre Creation Interfaces for Synthesizers
Gesture-aware Interactive Machine Teaching with In-situ Object Annotations
Bringing Rolling Shutter Images Alive with Dual Reversed Distortion
SyncUp: Vision-based Practice Support for Synchronized Dancing
Zhongyi Zhou, Anran Xu, Koji Yatani
In IMWUT/Ubicomp 2021
Best Presentation Award at Ubicomp '21
Distinguished Paper Award in IMWUT '21
PDF, ArXiv, Preview (30 secs), Demo (~2 mins) Talk (~6 mins)
An Image-based Approach for Defect Detection on Decorative Sheets

Workshop Papers (posters, demos, etc.)

DIPA: An Image Dataset with Cross-cultural Privacy Concern Annotations
Exploiting and Guiding User Interaction in Interactive Machine Teaching
Enhancing Model Assessment in Vision-based Interactive Machine Teaching through Real-time Saliency Map Visualization
Visualizing Out-of-synchronization in Group Dancing