Furui Cheng

Furui Cheng

Postdoc

ETH Zürich

Biography

I am a Postdoc at ETH Zürich, working with Prof. Menna El-Assady and other people in the recently established IVIA Lab.

My research focuses on Human-Centered AI with data visualization approaches. My research goal is to support people in understanding and interacting with machine learning models by developing scalable visual interfaces and explainable machine learning techniques. Recently, I have focused more on 1) facilitating interpretable and trustworthy AI-informed decision-making in high-stakes scenarios and 2) supporting users in steering machine learning models to align with their knowledge.

I received my Ph.D. at the Hong Kong University of Science and Technology in 2022, advised by Prof. Huamin Qu.

Download my resumé .

Interests
  • LLM Transparency
  • Explainable and Interactive ML
  • Human-AI Teaming in High-stakes Decision-making
  • Visual Analytics

Projects

Polyphony: incorporate experts’ knowledge into ML models
Polyphony facilitates interactions between biologists and single-cell omics data annotation ML models with the integration of visualization and anchor-based interactive transfer learning.
PDF Code
Polyphony: incorporate experts' knowledge into ML models
VBridge: AI-informed clinical decision-making
VBridge incorporates ML explanations into clinicians’ decision-making workflow by connecting the dots between ML features, data and explanations in healthcare models.
PDF Code
VBridge: AI-informed clinical decision-making
DECE: explore ML models with counterfactual explanations
DECE supports exploratory visual analysis on ML models with counterfactual explanations. The system helps non-expert users propose, verify, and refine their hypotheses on ML predictions.
PDF Code
DECE: explore ML models with counterfactual explanations

Publications

Furui Cheng, Mark S Keller, Huamin Qu, Nils Gehlenborg, Qianwen Wang (2022). Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis. IEEE Transactions on Visualization and Computer Graphics (To Appear). Best Abstract Award at BioVis@ISMB.

PDF Cite Code Project

Aoyu Wu, Dazhen Deng, Furui Cheng, Yingcai Wu, Shixia Liu, Huamin Qu (2022). In Defence of Visual Analytics Systems: Replies to Critics. IEEE Transactions on Visualization and Computer Graphics (To Appear).

PDF Cite Project

Furui Cheng, Dongyu Liu, Fan Du, Yanna Lin, Alexandra Zytek, Haomin Li, Huamin Qu, Kalyan Veeramachaneni (2021). VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models. IEEE Transactions on Visualization and Computer Graphics. Best Paper Honorable Mention Award.

PDF Cite Code Project Video

Furui Cheng, Yao Ming, Huamin Qu (2020). DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models. IEEE Transactions on Visualization and Computer Graphics.

PDF Cite Code Project

Yao Ming, Panpan Xu, Furui Cheng, Huamin Qu, Liu Ren (2019). ProtoSteer: Steering deep sequence model with prototypes. IEEE Transactions on Visualization and Computer Graphics.

PDF Cite

See all publications

Contact