Xingquan Guan
About Xingquan Guan
Xingquan Guan is a Senior Data Scientist at Zest AI in the Los Angeles Metropolitan Area with a background in structural engineering and artificial intelligence.
Company
Xingquan Guan is currently employed at Zest AI as a Senior Data Scientist. The company is situated in the Los Angeles Metropolitan Area and specializes in leveraging artificial intelligence for various applications.
Title
Xingquan Guan holds the position of Senior Data Scientist at Zest AI. His role involves advanced data analysis and application of AI models to solve complex problems.
Education and Expertise
Xingquan Guan earned his Doctor of Philosophy (PhD) in Structural Engineering from the University of California, Los Angeles, where he studied from 2016 to 2021. Prior to this, he completed his Master's degree in Structural Engineering and his Bachelor's degree in Civil Engineering at Huazhong University of Science and Technology. His education laid a strong foundation for his expertise in structural and earthquake engineering, further complemented by his extensive research on integrating artificial intelligence in hazard engineering.
Background
Xingquan Guan has a diverse professional background, having worked in various academic and research positions. He was a Postdoctoral Scholar at UCLA from 2021 to 2022, a Teaching Assistant from 2018 to 2021, and a Graduate Researcher from 2017 to 2021. He also served as a Research Assistant at Huazhong University of Science and Technology from 2013 to 2016. His roles have consistently been at the intersection of structural engineering and data science.
Achievements
Xingquan Guan has published multiple research papers on the application of artificial intelligence in hazard engineering. He has also presented his findings at international conferences focusing on structural and earthquake engineering. Notably, he developed a novel machine learning model to predict structural damage from seismic activities. Furthermore, he received a grant for research focused on integrating AI with structural engineering to improve earthquake resilience and collaborated with interdisciplinary teams to enhance the accuracy of hazard prediction models using AI.