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Quynh Quang Ngo

Dr.

Research Associate
Visualization Research Center (VISUS)
Sedlmair Group

Contact

+49 711 685 88623
Email

Allmandring 19
70569 Stuttgart
Germany
Room: 01.031

Publications

2023
1. Chen, Kun-Ting ; Ngo, Quynh Quang ; Kurzhals, Kuno ; Marriott, Kim ; Dwyer, Tim ; Sedlmair, Michael ; Weiskopf, Daniel: Reading Strategies for Graph Visualizations That Wrap Around in Torus Topology. In: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications, Proceedings of the 2023 Symposium on Eye Tracking Research and Applications. Tubingen, Germany : Association for Computing Machinery, 2023 — ISBN 9798400701504
  - BibTeX
  - Link
  BibTeX
  @inproceedings{10.1145/3588015.3589841, abstract = {We investigate reading strategies for node-link diagrams that wrap around the boundaries in a flattened torus topology by examining eye tracking data recorded in a previous controlled study. Prior work showed that torus drawing affords greater flexibility in clutter reduction than traditional node-link representations, but impedes link-and-path exploration tasks, while repeating tiles around boundaries aids comprehension. However, it remains unclear what strategies users apply in different wrapping settings. This is important for design implications for future work on more effective wrapped visualizations for network applications, and cyclic data that could benefit from wrapping. We perform visual-exploratory data analysis of gaze data, and conduct statistical tests derived from the patterns identified. Results show distinguishable gaze behaviors, with more visual glances and transitions between areas of interest in the non-replicated layout. Full-context has more successful visual searches than partial-context, but the gaze allocation indicates that the layout could be more space-efficient.}, address = {New York, NY, USA}, articleno = {67}, author = {Chen, Kun-Ting and Ngo, Quynh Quang and Kurzhals, Kuno and Marriott, Kim and Dwyer, Tim and Sedlmair, Michael and Weiskopf, Daniel}, booktitle = {Proceedings of the 2023 Symposium on Eye Tracking Research and Applications}, doi = {10.1145/3588015.3589841}, isbn = {9798400701504}, location = {Tubingen, Germany}, numpages = {7}, publisher = {Association for Computing Machinery}, series = {ETRA '23}, title = {Reading Strategies for Graph Visualizations That Wrap Around in Torus Topology}, url = {https://doi.org/10.1145/3588015.3589841}, year = 2023 }
  Link
  https://doi.org/10.1145/3588015.3589841
2022
1. Heyen, Frank ; Ngo, Quynh Quang ; Kurzhals, Kuno ; Sedlmair, Michael: Data-Driven Visual Reflection on Music Instrument Practice. In: ACM CHI Workshop on Intelligent Music Interfaces (IMI), ACM CHI Workshop on Intelligent Music Interfaces (IMI) : ACM, 2022
  - BibTeX
  - Link
  BibTeX
  @inproceedings{heyen2022datadriven, abstract = {We propose a data-driven approach to music instrument practice that allows studying patterns and long-term trends through visualization. Inspired by life logging and fitness tracking, we imagine musicians to record their practice sessions over the span of months or years. The resulting data in the form of MIDI or audio recordings can then be analyzed sporadically to track progress and guide decisions. Toward this vision, we started exploring various visualization designs together with a group of nine guitarists, who provided us with data and feedback over the course of three months.}, author = {Heyen, Frank and Ngo, Quynh Quang and Kurzhals, Kuno and Sedlmair, Michael}, booktitle = {ACM CHI Workshop on Intelligent Music Interfaces (IMI)}, doi = {10.48550/arxiv.2203.13320}, publisher = {ACM}, title = {Data-Driven Visual Reflection on Music Instrument Practice}, url = {https://doi.org/10.48550/arxiv.2203.13320}, year = 2022 }
  Link
  https://doi.org/10.48550/arxiv.2203.13320
2. Ngo, Quynh Quang ; Dennig, Frederik L. ; Keim, Daniel A. ; Sedlmair, Michael: Machine Learning Meets Visualization – Experiences and Lessons Learned. In: it - Information Technology, it - Information Technology. Bd. 64 (2022), Nr. 4–5, S. 169–180
  - BibTeX
  - Link
  BibTeX
  @article{NgoDennigKeimSedlmair+2022+169+180, abstract = {In this article, we discuss how Visualization (VIS) with Machine Learning (ML) could mutually benefit from each other. We do so through the lens of our own experience working at this intersection for the last decade. Particularly we focus on describing how VIS supports explaining ML models and aids ML-based Dimensionality Reduction techniques in solving tasks such as parameter space analysis. In the other direction, we discuss approaches showing how ML helps improve VIS, such as applying ML-based automation to improve visualization design. Based on the examples and our own perspective, we describe a number of open research challenges that we frequently encountered in our endeavors to combine ML and VIS.}, author = {Ngo, Quynh Quang and Dennig, Frederik L. and Keim, Daniel A. and Sedlmair, Michael}, doi = {doi:10.1515/itit-2022-0034}, journal = {it - Information Technology}, lastchecked = {2022-09-20}, number = {4-5}, pages = {169–180}, title = {Machine Learning Meets Visualization – Experiences and Lessons Learned}, url = {https://doi.org/10.1515/itit-2022-0034}, volume = 64, year = 2022 }
  Link
  https://doi.org/10.1515/itit-2022-0034

Quynh Quang Ngo

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Publications

2023

BibTeX

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2022

BibTeX

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BibTeX

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Quynh Quang Ngo

Contact

Publications

2023

BibTeX

Link

2022

BibTeX

Link

BibTeX

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