TAKANORI
FUJIWARA
Takanori Fujiwara is a postdoctoral researcher at the Department of Science and Technology (ITN), Linköping University. He is currently working for the division for Media and Information Technology (MIT, led by Dr. Anders Ynnerman) and the Information Visualization group (iVis, chaired by Dr. Andreas Kerren). His research interest lies in intersctions of network science, machine learning, and visual analytics. He received his B.E. (2009) and Master's degree in environmental studies (2011) from University of Tokyo; Ph.D. in computer science from University of California, Davis (2021) where he was with VIDI Labs. During 2011-2015, he worked for Kajima Corporation in Japan.
E-mail: tfujiwara at ucdavis.edu (preferred) or takanori.fujiwara at liu.se
CV,  GitHub,  Google Scholar,  ResearchGate
NEWS
[2022.12] I am co-charing the Workshop on Visualization Meets AI. The paper due is Dec-30, 2022.
[2022.06] Implementation of D3 Gallery's examples without using Observable is available here (over 150 examples).
[2022.04] I am willing to provide research mentorship and support for students/researchers in underrepresented countries in terms of visualization research. Please read here.
SOFTWARE

- D3 Gallery - JavaScript Implementation.

- Most of visual analytics algorithms and UI used in the published papers are available on GitHub.

PUBLICATIONS
Submitted for Publication/Preprint
Feature Learning for Dimensionality Reduction toward Maximal Extraction of Hidden Patterns
Takanori Fujiwara, Yun-Hsin Kuo, Anders Ynnerman, and Kwan-Liu Ma
arXiv Preprint.
arXiv supp. materials source code
Contrastive Multiple Correspondence Analysis (cMCA): Using Contrastive Learning to Identify Latent Subgroups in Political Parties
Takanori Fujiwara* and Tzu-Ping Liu* (*equally contributed)
arXiv Preprint.
arXiv supp. materials source code poster (at PolMeth XXXVII) slides (invited by University of Essex POPE (Public Opinion, Parties and Elections) Research Group)
2022
Network Comparison with Interpretable Contrastive Network Representation Learning
(previously, titled "Interpretable Contrastive Learning for Networks")
Takanori Fujiwara, Jian Zhao, Francine Chen, Yaoliang Yu, and Kwan-Liu Ma
Journal of Data Science, Statistics, and Visualisation, 2022.
Journal website (Open Access) arXiv datasets, analysis details, etc source code
A Predictive Visual Analytics System for Studying Neurodegenerative Disease Based on DTI Fiber Tracts
Chaoqing Xu, Tyson Neuroth, Takanori Fujiwara, Ronghua Liang, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics, early access.
IEEE Xplore arXiv demo video
A Visual Analytics Method for Time-Series Log Data Using Multiple Dimensionality Reduction
(The extended version from the one for Proc. Asia Simulation Conference)
Keijiro Fujita, Naohisa Sakamoto, Takanori Fujiwara, Toshiyuki Tsukamoto, Jorji Nonaka
Journal of Advanced Simulation in Science and Engineering, 2022.
Paper at J-STAGE (Open Access)
A Visual Analytics Approach for Hardware System Monitoring with Streaming Functional Data Analysis
(previously, titled "A Visual Analytics Approach to Monitor Time-Series Data with Incremental and Progressive Functional Data Analysis")
Shilpika, Takanori Fujiwara, Naohisa Sakamoto, Jorji Nonaka, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics (also in proc. PacificVis 2022). Best Paper Honorable Mention
IEEE Xplore arXiv demo video
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data
Yun-Hsin Kuo, Takanori Fujiwara, Charles C.-K. Chou, Chun-houh Chen, and Kwan-Liu Ma
In Proc. Pacific Visualization Symposium (PacificVis), 2022.
IEEE Xplore arXiv demo video
2021
Interactive Dimensionality Reduction for Comparative Analysis
Takanori Fujiwara, Xinhai Wei, Jian Zhao, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics (also in proc. IEEE VIS 2021).
IEEE Xplore arXiv demo videos, supp. evaluations, etc. source code talk
A Visual Analytics System for Water Distribution System Optimization
Yiran Li, Erin Musabandesu, Takanori Fujiwara, Frank J. Loge, and Kwan-Liu Ma
In Proc. IEEE Visualization Conference (VIS)—Short Papers, 2021.
IEEE Xplore arXiv demo video
A Visual Analytics Approach for the Diagnosis of Heterogeneous and Multidimensional Machine Maintenance Data
Xiaoyu Zhang, Takanori Fujiwara, Senthil Chandrasegaran, Michael P. Brundage, Thurston Sexton, Alden Dima, and Kwan-Liu Ma
In Proc. IEEE Pacific Visualization Symposium (PacificVis), 2021.
IEEE Xplore paper demo video
A Visual Analytics Method for Time-Series Log Data Using Multiple Dimensionality Reduction
Keijiro Fujita, Naohisa Sakamoto, Takanori Fujiwara, Jorji Nonaka, Toshiyuki Tsukamoto
In Proc. Asia Simulation Conference (AsiaSim), 2021.
2020
A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction
Takanori Fujiwara, Shilpika, Naohisa Sakamoto, Jorji Nonaka, Keiji Yamamoto, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics (also in proc. IEEE VIS 2020).
IEEE Xplore arXiv demo video, datasets, etc source code talk
A Visual Analytics Framework for Contrastive Network Analysis
Takanori Fujiwara, Jian Zhao, Francine Chen, and Kwan-Liu Ma
In Proc. IEEE Conference on Visual Analytics Science and Technology (VAST), 2020.
IEEE Xplore arXiv demo video, datasets, etc talk
A Visual Analytics System for Multi-model Comparison on Clinical Data Predictions
Yiran Li, Takanori Fujiwara, Yong K. Choi, Katherine K. Kim, and Kwan-Liu Ma
Journal of Visual Informatics (also in proc. PacificVis 2020 Visualization Meets AI Workshop).
ScienceDirect (open access) arXiv demo video
Comparative Visual Analytics for Assessing Medical Records with Sequence Embedding
Rongchen Guo, Takanori Fujiwara, Yiran Li, Kelly M. Lima, Soman Sen, Nam K. Tran, and Kwan-Liu Ma
Journal of Visual Informatics (also in proc. PacificVis 2020 Visualization Meets AI Workshop).
ScienceDirect (open access) arXiv demo video
A Visual Analytics Framework for Reviewing Streaming Performance Data
Suraj P. Kesavan, Takanori Fujiwara, Jianping Kelvin Li, Caitlin Ross, Misbah Mubarak, Christopher D. Carothers, Robert B. Ross, and Kwan-Liu Ma
In Proc. IEEE Pacific Visualization Symposium (PacificVis), 2020.
IEEE Xplore arXiv demo video source code
2019
A Visual Analytics Framework for Analyzing Parallel and Distributed Computing Applications
Jianping Kelvin Li, Takanori Fujiwara, Suraj P. Kesavan, Caitlin Ross, Misbah Mubarak, Christopher D. Carothers, Robert B. Ross, and Kwan-Liu Ma
In Proc. Symposium on Visualization in Data Science (VDS), 2019.
IEEE Xplore paper talk
Supporting Analysis of Dimensionality Reduction Results with Contrastive Learning
Takanori Fujiwara, Oh-Hyun Kwon, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics (also in proc. IEEE VIS 2019). Best Paper Honorable Mention
IEEE Xplore arXiv demo system, datasets, etc source code talk
An Incremental Dimensionality Reduction Method for Visualizing Streaming Multidimensional Data
Takanori Fujiwara, Jia-Kai Chou, Shilpika, Panpan Xu, Liu Ren, and Kwan-Liu Ma
IEEE Transactions on Visualization and Computer Graphics (also in proc. IEEE VIS 2019).
IEEE Xplore arXiv supp. materials and videos source code talk
2018
Concise Provenance of Interactive Network Analysis
Takanori Fujiwara, Tarik Crnovrsanin, and Kwan-Liu Ma
Journal of Visual Informatics, 2018.
ScienceDirect (open access) supp. materials demo video
An Organic Visual Metaphor for Public Understanding of Conditional Co-occurrences
Keshav Dasu, Takanori Fujiwara, and Kwan-Liu Ma
In Proc. IEEE Scientific Visualization (SciVis, short paper), 2018
IEEE Xplore paper demo video source code talk
A Visual Analytics System for Optimizing the Performance of Large-scale Networks in Supercomputing Systems
Takanori Fujiwara, Jianping Kelvin Li, Misbah Mubarak, Caitlin Ross, Christopher D. Carothers, Robert B. Ross, and Kwan-Liu Ma
Journal of Visual Informatics (also in proc. PacificVAST), 2018
ScienceDirect (open access)
2017
A Visual Analytics System for Optimizing Communications in Massively Parallel Applications
Takanori Fujiwara, Preeti Malakar, Khairi Reda, Venkatram Vishwanath, Michael E. Papka, and Kwan-Liu Ma
In Proc. IEEE Conference on Visual Analytics Science and Technology (VAST), 2017
IEEE Xplore paper demo video source code dataset talk
Threatening Event, National Identity and Network Dynamics of Motivated Information Processing: Exploring Japanese Twitter during the Rise of Territorial Disputes, April through October 2012
Gento Kato, Takanori Fujiwara, Christian Collet, Tetsuro Kobayashi, and Takafumi Suzuki
In Proc. APSA Annual Meeting, 2017
paper
A Gesture System for Graph Visualization in Virtual Reality Environments
Yi-Jheng Huang, Takanori Fujiwara, Yun-Xuan Lin, Wen-Chieh Lin, and Kwan-Liu Ma
In Proc. IEEE Pacific Visualization Symposium (PacificVis, short paper), 2017
IEEE Xplore paper demo video
A Visual Analytics System for Brain Functional Connectivity Comparison across Individuals, Groups, and Time Points
Takanori Fujiwara, Jia-Kai Chou, Andrew M. McCullough, Charan Ranganath, and Kwan-Liu Ma
In Proc. IEEE Pacific Visualization Symposium (PacificVis), 2017
IEEE Xplore paper demo video source code
2015
Multi-Agent-Based Simulation of Knowledge Propagation in Organizations
Gaku Hashimoto, Takanori Fujiwara, Masaaki Suzuki, Hiroshi Okuda, Junji Ise, and Masanori Shioya
Electronics and Communications in Japan, 2015
Wiley Online Library
2011
A Fractal-based 2D Expansion Method for Multi-scale Volume Data Visualization
Takanori Fujiwara, Masaki Iwamaru, Manabu Tange, Satoshi Someya, and Koji Okamoto
Journal of Visualization, 2011
Springer Link paper
2010
Fractal Map: Fractal-Based 2D Expansion Method for Multi-Scale High-Dimensional Data Visualization
Takanori Fujiwara, Ryo Matsushita, Masaki Iwamaru, Manabu Tange, Satoshi Someya, and Koji Okamoto
In Proc. International Symposium on Visual Computing (ISVC), 2010
Springer Link paper
OTHER WORKS
2018
Learning About Disease Associations in Taiwan
Keshav Dasu, Suyun Bae, Takanori Fujiwara, and Kwan-Liu Ma
Honorable Mention, IEEE PacificVis Visual Storytelling Contest, 2018
demo site abstract