Panpan Xu (徐盼盼), I am currently a Senior Applied Scientist at Amazon AWS AI (Santa Clara, CA). I am working on research and development of Machine Learning and Explainable AI (XAI) techniques for high-impact customer applications in a variety of industrial verticals, which includes but are not limited to Manufacturing, Health Care and Life Sciences, Automotive, Retail and etc.
I am broadly interested in multidisciplinary research that combines techniques in machine learning, data visualization, and human-computer interaction to help people better understand large and complex data, develop and apply machine learning models to address important real-world use cases, and distill and communicate their findings in an intuitive manner.
   Before joining Amazon, I was a Research Scientist at Bosch Research North America. I hold PhD and Bachelor's in Computer Science from Hong Kong University of Science and Technology and Zhejiang University, respectively.

Human-in-the-loop Extraction of Interpretable Concepts in Deep Learning Models
IEEE VIS 2021 (to appear)
Zhenge Zhao (intern), Panpan Xu, Carlos Scheidegger, Liu Ren
paper (coming soon)
(TL;DR: an active learning approach to visual concept extraction for generic vision model (image classification and semantic segmentaion) diagnostics and performance improvement)

Interactive Visual Pattern Search on Graph Data via Graph Representation Learning
IEEE VIS 2021 (to appear)
Huan Song, Zeng Dai, Panpan Xu, Liu Ren
paper (coming soon)
(TL;DR: enable interactive subgraph isomorphism search with GNNs)

ProtoSteer: Steering Deep Sequence Model with Prototypes
IEEE Transactions on Visualization and Computer Graphics (VAST 2019)
Yao Ming (Intern), Panpan Xu, Furui Cheng, Huamin Qu, Liu Ren
paper (with supplementary materials) video (Dropbox link) bib
(TL;DR: interactive interface to train DNNs with domain knowledge input)

Interpretable and Steerable Sequence Learning via Prototypes
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 19), Research Track, Oral
Yao Ming (intern), Panpan Xu, Huamin Qu, Liu Ren
paper (with supplementary materials) video (30MB download) bib
(TL;DR: DNN with built-in interpretability for time-series and event sequence classification)

TPFlow: Progressive Partition and Multidimensional Pattern Extraction for Large-Scale Spatio-Temporal Data Analysis IEEE Transactions on Visualization and Computer Graphics (VAST 2018)
Best Paper Award
Dongyu Liu (intern), Panpan Xu, Liu Ren
paper video (50MB download) bib

ViBR: Visualizing Bipartite Relations at Scale with the Minimum Description Length Principle
IEEE Transactions on Visualization and Computer Graphics (VAST 2018)
Gromit Yeuk-Yin Chan (intern), Panpan Xu, Zeng Dai, Liu Ren
paper supplementary material video (78MB download) bib

Sequence Synopsis: Optimize Visual Summary of Temporal Event Data
IEEE Transactions on Visualization and Computer Graphics (VAST 2017)
Yuanzhe Chen (intern), Panpan Xu, Liu Ren
paper supplementary material video(82MB download) bib

VisPubData.org: A Metadata Collection about IEEE Visualization (VIS) Publications
IEEE Transactions on Visualization and Computer Graphics 2017
Petra Isenberg, Florian Heimerl, Steffen Koch, Tobias Isenberg, Panpan Xu, Chad Stolper, Michael Sedlmair, Jian Chen, Torsten Möller, John Stasko
paper data visualization demo site

ViDX: Visual Diagnostics of Assembly Line Performance in Smart Factories
IEEE Transactions on Visualization and Computer Graphics (VAST 2016)
Best Paper Honorable Mention Award
Panpan Xu, Honghui Mei (intern) , Liu Ren, Wei Chen
paper video (vimeo) video (download) bib

Interactive Visual Co-cluster Analysis of Bipartite Graphs
IEEE Pacific Visualization Symposium (PacificVis)}, 2016
Panpan Xu, Nan Cao, Huamin Qu, John Stasko
paper bib

Visual Analysis of Topic Competition on Social Media
IEEE Transactions on Visualization and Computer Graphics (VAST 2013)
Panpan Xu, Yingcai Wu, Enxun Wei, Tai-Quan Peng, Shixia Liu, Jonathan J.H. Zhu, Huamin Qu
paper bib slides (large)

Edge Bundling in Information Visualization
Tsinghua Science and Technology, 2013
Hong Zhou, Panpan Xu, Xiaoru Yuan and Huamin Qu
paper bib

PhD, Computer Science

• Vis Lab, Hong Kong University of Science and Technology

Visiting Student

• Information Interfaces Research Group, Georgia Institute of Technology

Research Intern

• Microsoft Research Asia, Internet Graphics Group

B.S., Computer Science

• State Key Lab of Computer Aided Design and Computer Graphics, Zhejiang University

Program Committee

• IEEE VIS (VAST) Papers, 2017 - 2019
• ACM Intelligent User Interface (IUI) Papers, 2019
• IEEE Pacific Visualization Symposium (PacificVis) Papers, 2017 - 2019
• IEEE Pacific Visualization Symposium (PacificVis) Workshop on Visualization meets AI, 2019
• IEEE Pacific Visualization Symposium (PacificVis) Notes, 2016
• International Symposium on Visual Computing (ISVC), 2018
• ChinaVis, 2017 - 2019

Reviewer

• ACM SIGCHI
• IEEE VIS (InfoVis and VAST)
• IEEE Transactions on Visualization and Computer Graphics
• The EG/VGTC Conference on Visualization (EuroVis)
• IEEE Pacific Visualization Symposium (PacificVis)
• IEEE Computer Graphics and Applications Magazine
• Very Large Data Bases (VLDB)

Organizing Committee

• IEEE Visualization in Data Science (VDS) Web Chair (colocated with IEEE VIS), 2019
• Area Chair, Visualization, International Symposium on Visual Computing (ISVC), 2019

Quotes:

"A problem clearly stated is a problem half solved." - Dorothea Brande

"The fundamental principles of designing for people: (1) provide a good conceptual model and (2) make things visible." - The Design of Everyday Things, Don Norman

"The writers who have most to give us often do most violence to our prejudices, particularly if they are our own contemporaries." - Virginia Woolf