Xin Zhao, Ph.D

Xin Zhao headshot

Faculty Fellow and Assistant Professor of Computer Science

Phone: 206-220-8028

Building/Room: SINE 220-02

There is no doubt that information technology is fueling the U.S. economy. In 2021, the United States tech sector “contributed around 1.8 trillion U.S. dollars to the country's overall gross domestic product (GDP), making up approximately 9.3 percent of total GDP.” Information technology playing an important role is even more true for Washington State – as a global hub for information technology, in total, it has more than 13,000 information technology companies and is the birthplace of renowned businesses such as Amazon, Microsoft, Expedia, and Zillow.

Despite the lightning growth of information technology employment opportunities, there has been a distinct lack of opportunities for females, workers over 40, and other minority groups. Based on a diversity study conducted by U.S. Equal Employment Opportunity Commission (EECO), the information technology sector hired a larger share of white compared with African Americans and Hispanics, a larger share of male compared with female professionals. Besides age, race, and gender, other types of discrimination, such as pregnancy, religion, sexual orientation and gender identity, and disability, are barely studied. Therefore, the project’s overarching goal is to understand the Forms, Causes, and Effects of Employment Discrimination in Information Technology Corporates.

During his fellowship, Xin will conduct an empirical investigation to gain deeper insights into workplace discrimination in information technology field. He will analyze three questions: 1) What kind of discrimination has employees has experienced? 2) What reasons lead to employment discrimination? 3) What impact does the discrimination have on employees? He will also provide feedback to Information Technology Business based on the result of this study to further improve the Diversity, Equity, and Inclusion (DEI) in their workplace.

Recent Research

Xin Zhao and Jeff Gray, “A Survey-Based Empirical Evaluation of Bad Smells in LabVIEW Systems Models,” 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER'21), pp. 177-188, Virtual - Honolulu, Hawaii. USA.

Saheed Popoola, Xin Zhao and Jeff Gray, “Evolution of Bad Smells in LabVIEW Graphical Models.” Journal of Object Technology, Vol 20, No. 1, pp. 1-15, 2021. DOI: 10.5381/jot.2021.20.1.a1

Xin Zhao and Jeff Gray, “BESMER: An Approach for Bad Smells Summarization in Systems Models.” in Models and Evolution at ACM/IEEE 22th International Conference on Model Driven Engineering Languages and Systems (MODELS’19) , Munich, Germany.