Biography
I am a Postdoc at ETH Zürich, working with Prof. Menna El-Assady and other amazing 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 Decision Making
- Visual Analytics
Featured Projects
Polyphony facilitates interactions between biologists and single-cell omics data annotation ML models with the integration of visualization and anchor-based interactive transfer learning.
VBridge incorporates ML explanations into clinicians’ decision-making workflow by connecting the dots between ML features, data and explanations in healthcare models.
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.
Publications
(2024).
RELIC: Investigating Large Language Model Responses using Self-Consistency.
Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI'24).
(2022).
Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.
IEEE Transactions on Visualization and Computer Graphics (VIS'22). Best Abstract Award at BioVis@ISMB.
(2022).
In Defence of Visual Analytics Systems: Replies to Critics.
IEEE Transactions on Visualization and Computer Graphics (VIS'22).
(2021).
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models.
IEEE Transactions on Visualization and Computer Graphics (VIS'21). Best Paper Honorable Mention Award.
(2020).
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models.
IEEE Transactions on Visualization and Computer Graphics (VIS'20).
Contact
- furui.cheng@inf.ethz.ch
- (+41) 076 451 2072
- Stampfenbachstrasse 114, Zürich, 8092