Education
Aug. 2018 - Aug. 2023
2018.08 ~ 2023.08
Ph.D. in Computer Science
Arizona State University, Tempe, AZ
Advisor: Ross Maciejewski
Dissertation: Explaining Vulnerabilities in Machine Learning through Visual Analytics
Committee: Ross Maciejewski, Huan Liu, Chris Bryan, and Hanghang Tong
Aug. 2015 - May 2017
2015.08 ~ 2017.05
M.S. in Computer Science
Steven Institute of Technology, Hoboken, NJ
Sep. 2011 - July 2015
2011.09 ~ 2015.07
B.S. in Computer Science
Beijing Forestry University, Beijing, China
Research Experience
Aug. 2023 - Present
2023.08 ~ Present
Postdoctoral Research Scholar
VADER Lab, Arizona State University, Tempe, AZ
Advisor: Ross Maciejewski
Work as a postdoctoral research scholar at the VADER Lab. Collaborate with multidisciplinary teams, mentor graduate and undergraduate students, and participate in grant writing activities to secure funding for ongoing and future research projects in machine learning and visual analytics fields.
Aug. 2018 - Aug. 2023
2018.08 ~ 2023.08
Graduate Research Associate
VADER Lab, Arizona State University, Tempe, AZ
Advisor: Ross Maciejewski
Work as a graduate research associate at the VADER Lab with the research topics in Explainable AI and Visual Analytics. The dissertation topic is Explaining the vulnerabilities of machine learning models through visual analytics.
Industry Experience
May 2021 - Aug. 2021
2021.05 ~ 2021.08
Data Scientist Intern
Epsilon Data Management, LLC., Chicago, IL
Mentor: Chihua Ma
Designed and implemented the algorithm to extract highlights from the aggregated audience data across 2500+ companies. Designed, implemented and integrated the Intelligent Audience Profile (IAP) visualization view driven by the designed highlighting algorithm into the DiME visual analytics platform.
July 2017 - May 2018
2017.07 ~ 2018.05
Co-founder
RobotGyms, Inc., San Mateo, CA
Designed, implemented Robotgyms's infrastructure and curriculum. and maintained the company's teaching devices, including local network and devices' software and hardware installation and upgrade. Developed policies and training plans for online resource administration and usage. Give lectures for 40+ students and took charge of customer consultation, and conducted SEO and SMO for branding programs as well as the company.
Publications
Big Data 2022
Infofair: Information-theoretic intersectional fairness
Jian Kang, Tiankai Xie, Xintao Wu, Ross Maciejewski, and Hanghang Tong
IEEE International Conference on Big Data
VIS 2021
FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models
Tiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong, and Ross Maciejewski
IEEE Transactions on Visualization and Computer Graphics, 2021
VIS 2020
Auditing the Sensitivity of Graph-based Ranking with Visual Analytics
Tiankai Xie, Yuxin Ma, Jian Kang, Hanghang Tong, and Ross Maciejewski
IEEE Transactions on Visualization and Computer Graphics, 2020
VIS 2019
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
Yuxin Ma, Tiankai Xie, Jundong Li, and Ross Maciejewski
IEEE Transactions on Visualization and Computer Graphics, 2019
Invited Talks
Oct. 2021
2021.10
FairRankVis: A Visual Analytics Framework for Exploring Algorithmic Fairness in Graph Mining Models
IEEE Transactions on Visualization and Computer Graphics, 2021
Oct. 2020
2020.10
Auditing the Sensitivity of Graph-based Ranking with Visual Analytics
IEEE Transactions on Visualization and Computer Graphics, 2020
Oct. 2019
2019.10
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics
IEEE Transactions on Visualization and Computer Graphics, 2019
Professional Services
2024
Reviewer
ACM Transactions on Intelligent Systems and Technology
2024
Reviewer
Pacific Visualization Conference
2023
Reviewer
IEEE Transactions on Visualization and Computer Graphics
2022
Reviewer
IEEE Computer Graphics & Applications
2021
Reviewer
IEEE Transactions on Visualization and Computer Graphics