Terrance Law (he/him)
I am a full-stack developer with extensive experience building interactive visualization systems. I received dual degrees in Computer Science and General Business Management from the Hong Kong University of Science and Technology, and a PhD in Computer Science from Georgia Institute of Technology. During my PhD, I was a member of Georgia Tech Visualization Lab.
For more information, you can see my resume.
You can contact me at pmlaw (at) gatech (dot) edu and find me on LinkedIn.
Visualization systems I built
Research during my PhD
My dissertation
Exploring User Perception of Causality in Automated Data Insights (PhD Dissertation)
Exploring User Perception of Causality in Automated Data Insights
Po-Ming Law
PhD Dissertation, Georgia Institute of Technology
CHI 2021 paper
Causal Perception in Question-Answering Systems (CHI 2021)
Causal Perception in Question-Answering Systems
Po-Ming Law, Leo Yu-Ho Lo, Alex Endert, John Stasko, and Huamin Qu
ACM Conference on Human Factors in Computing Systems (CHI 2021)
IEEE VIS 2020 interview study paper
What are Data Insights to Professional Visualization Users? (IEEE VIS 2020)
What are Data Insights to Professional Visualization Users?
Po-Ming Law, Alex Endert, and John Stasko
IEEE VIS Short Paper (IEEE VIS 2020)
IEEE VIS 2020 literature review paper
Characterizing Automated Data Insights (IEEE VIS 2020)
Characterizing Automated Data Insights
Po-Ming Law, Alex Endert, and John Stasko
IEEE VIS Short Paper (IEEE VIS 2020)
GI 2020 paper
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias (GI 2020)
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias
Po-Ming Law, Sana Malik, Fan Du, and Moumita Sinha
Graphics Interface 2020 (GI 2020)
CoBi 2020 paper
Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study (CoBi 2020)
Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study
Po-Ming Law, Sana Malik, Fan Du, and Moumita Sinha
CHI 2020 Workshop on Detection and Design for Cognitive Biases in People and Computing Systems (CoBi 2020)
CHI 2019 paper
Comparing Apples and Oranges: Taxonomy and Design of Pairwise Comparisons within Tabular Data (CHI 2019)
Comparing Apples and Oranges: Taxonomy and Design of Pairwise Comparisons within Tabular Data
Po-Ming Law, Subhajit Das, and Rahul C. Basole
ACM Conference on Human Factors in Computing Systems (CHI 2019)
IEEE VIS 2018 Duet paper
Duet: Helping Data Analysis Novices Conduct Pairwise Comparisons by Minimal Specification (IEEE VIS 2018)
Duet: Helping Data Analysis Novices Conduct Pairwise Comparisons by Minimal Specification
Po-Ming Law, Rahul C. Basole, and Yanhong Wu
IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2018)
IEEE VIS 2018 MAQUI paper
MAQUI: Interweaving Queries and Pattern Mining for Recursive Event Sequence Exploration (IEEE VIS 2018)
MAQUI: Interweaving Queries and Pattern Mining for Recursive Event Sequence Exploration
Po-Ming Law, Zhicheng Liu, Sana Malik, and Rahul C. Basole
IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2018)
IEEE VIS 2018 Segue paper
Segue: Overviewing Evolution Patterns of Egocentric Networks by Interactive Construction of Spatial Layouts (IEEE VIS 2018)
Segue: Overviewing Evolution Patterns of Egocentric Networks by Interactive Construction of Spatial Layouts
Po-Ming Law, Yanhong Wu, and Rahul C. Basole
IEEE Conference on Visual Analytics Science and Technology (IEEE VIS 2018)
DECISIVe 2017 paper
Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases (DECISIVe 2017)
Designing Breadth-Oriented Data Exploration for Mitigating Cognitive Biases
Po-Ming Law and Rahul C. Basole
2nd Workshop on Dealing with Cognitive Biases in Visualizations (DECISIVe 2017)
IEEE VIS 2016 paper
VisMatchmaker: Cooperation of the User and the Computer in Centralized Matching Adjustment (IEEE VIS 2016)
VisMatchmaker: Cooperation of the User and the Computer in Centralized Matching Adjustment
Po-Ming Law, Wenchao Wu, Yixian Zheng, and Huamin Qu
IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2016)