Qianwen Wang

According to our database, Qianwen Wang authored at least 31 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

GNN101: Visual Learning of Graph Neural Networks in Your Web Browser.

Yilin Lu, Chongwei Chen, Yuxin Chen, Kexin Huang, Marinka Zitnik, Qianwen Wang

IEEE Trans. Vis. Comput. Graph., February, 2026

Can LLMs Bridge Domain and Visualization? A Case Study on High-Dimension Data Visualization in Single-Cell Transcriptomics.

Qianwen Wang, Xinyi Liu, Nils Gehlenborg

IEEE Trans. Vis. Comput. Graph., January, 2026

FlowForge: Guiding the Creation of Multi-Agent Workflows with Design Space Visualization as a Thinking Scaffold.

Pan Hao, Dongyeop Kang, Nicholas Hinds, Qianwen Wang

IEEE Trans. Vis. Comput. Graph., January, 2026

Not All Uncertainty Is Equal: How Uncertainty Granularity Shapes Human Verification in LLM-Assisted Decision Making.

Mauricio Villavicencio, Sitong Pan, Qianwen Wang

Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency, 2026

2025

A Critical Analysis of the Usage of Dimensionality Reduction in Four Domains.

Dylan Cashman, Mark S. Keller, Hyeon Jeon, Bum Chul Kwon, Qianwen Wang

IEEE Trans. Vis. Comput. Graph., October, 2025

KNowNEt:Guided Health Information Seeking from LLMs via Knowledge Graph Integration.

Youfu Yan, Yu Hou, Yongkang Xiao, Rui Zhang, Qianwen Wang

IEEE Trans. Vis. Comput. Graph., January, 2025

The State of Single-Cell Atlas Data Visualization in the Biological Literature.

Mark S. Keller, Eric Mörth, Thomas C. Smits, Simon Warchol, Grace Guo, Qianwen Wang, Robert Krüger, Hanspeter Pfister, Nils Gehlenborg

IEEE Computer Graphics and Applications, 2025

2024

GNN 101: Visual Learning of Graph Neural Networks in Your Web Browser.

Yilin Lu, Chongwei Chen, Kexin Huang, Marinka Zitnik, Qianwen Wang

CoRR, 2024

2023

GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks.

Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

IEEE Trans. Vis. Comput. Graph., June, 2023

Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing.

Qianwen Wang, Kexin Huang, Payal Chandak, Marinka Zitnik, Nils Gehlenborg

IEEE Trans. Vis. Comput. Graph., 2023

GenoREC: A Recommendation System for Interactive Genomics Data Visualization.

Aditeya Pandey, Sehi L'Yi, Qianwen Wang, Michelle A. Borkin, Nils Gehlenborg

IEEE Trans. Vis. Comput. Graph., 2023

Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

Furui Cheng, Mark S. Keller, Huamin Qu, Nils Gehlenborg, Qianwen Wang

IEEE Trans. Vis. Comput. Graph., 2023

Beyond Generating Code: Evaluating GPT on a Data Visualization Course.

Chen Zhu-Tian, Chenyang Zhang, Qianwen Wang, Jakob Troidl, Simon Warchol, Johanna Beyer, Nils Gehlenborg, Hanspeter Pfister

CoRR, 2023

Enabling Multimodal User Interactions for Genomics Visualization Creation.

Qianwen Wang, Xiao Liu, Man Qing Liang, Sehi L'Yi, Nils Gehlenborg

Proceedings of the 2023 IEEE Visualization and Visual Analytics (VIS), 2023

The Role of Visualization in Genomics Data Analysis Workflows: The Interviews.

Sehi L'Yi, Qianwen Wang, Nils Gehlenborg

Proceedings of the 2023 IEEE Visualization and Visual Analytics (VIS), 2023

DRAVA: Aligning Human Concepts with Machine Learning Latent Dimensions for the Visual Exploration of Small Multiples.

Qianwen Wang, Sehi L'Yi, Nils Gehlenborg

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

2022

ThreadStates: State-based Visual Analysis of Disease Progression.

Qianwen Wang, Tali Mazor, Theresa Anisja Harbig, Ethan Cerami, Nils Gehlenborg

IEEE Trans. Vis. Comput. Graph., 2022

A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization.

Qianwen Wang, Chen Zhu-Tian, Yong Wang, Huamin Qu

IEEE Trans. Vis. Comput. Graph., 2022

Gosling: A Grammar-based Toolkit for Scalable and Interactive Genomics Data Visualization.

Sehi L'Yi, Qianwen Wang, Fritz Lekschas, Nils Gehlenborg

IEEE Trans. Vis. Comput. Graph., 2022

2021

Visual Analysis of Discrimination in Machine Learning.

Qianwen Wang, Zhenhua Xu, Chen Zhu-Tian, Yong Wang, Shixia Liu, Huamin Qu

IEEE Trans. Vis. Comput. Graph., 2021

HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models.

Qianwen Wang, William Alexander, Jack Pegg, Huamin Qu, Min Chen

IEEE Trans. Vis. Comput. Graph., 2021

2020

Visual Genealogy of Deep Neural Networks.

Qianwen Wang, Jun Yuan, Shuxin Chen, Hang Su, Huamin Qu, Shixia Liu

IEEE Trans. Vis. Comput. Graph., 2020

DeepDrawing: A Deep Learning Approach to Graph Drawing.

Yong Wang, Zhihua Jin, Qianwen Wang, Weiwei Cui, Tengfei Ma, Huamin Qu

IEEE Trans. Vis. Comput. Graph., 2020

Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timeline.

Chen Zhu-Tian, Yun Wang, Qianwen Wang, Yong Wang, Huamin Qu

IEEE Trans. Vis. Comput. Graph., 2020

MARVisT: Authoring Glyph-Based Visualization in Mobile Augmented Reality.

Chen Zhu-Tian, Yijia Su, Yifang Wang, Qianwen Wang, Huamin Qu, Yingcai Wu

IEEE Trans. Vis. Comput. Graph., 2020

Applying Machine Learning Advances to Data Visualization: A Survey on ML4VIS.

Qianwen Wang, Chen Zhu-Tian, Yong Wang, Huamin Qu

CoRR, 2020

GNNVis: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks.

Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

CoRR, 2020

Augmenting Static Visualizations with PapARVis Designer.

Chen Zhu-Tian, Wai Tong, Qianwen Wang, Benjamin Bach, Huamin Qu

Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

2019

Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs.

Qianwen Wang, Zhen Li, Siwei Fu, Weiwei Cui, Huamin Qu

IEEE Trans. Vis. Comput. Graph., 2019

Narvis: Authoring Narrative Slideshows forIntroducing Data Visualization Designs.

Qianwen Wang, Zhen Li, Siwei Fu, Weiwei Cui, Huamin Qu

CoRR, 2019

ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning.

Qianwen Wang, Yao Ming, Zhihua Jin, Qiaomu Shen, Dongyu Liu, Micah J. Smith, Kalyan Veeramachaneni, Huamin Qu

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 2019