Zhiquan Sui
About Zhiquan Sui
Zhiquan Sui is a Staff Software Engineer at ThoughtSpot, where he has worked since 2020, focusing on data storage and retrieval. He holds a Ph.D. in Computer Science from Colorado State University and has expertise in distributed systems, cloud computing, and machine learning.
Work at ThoughtSpot
Zhiquan Sui has been employed at ThoughtSpot as a Staff Software Engineer since 2020. In this role, he has focused on implementing key functionalities such as the Google File System and Google Search. His work emphasizes critical areas including data storage, retrieval, content harvesting, parsing, and failure detection and recovery. Prior to his current position, he served as a Member of Technical Staff (MTS) - Software Engineer at ThoughtSpot from 2015 to 2020.
Education and Expertise
Zhiquan Sui holds a Bachelor's degree in Computer Science from Shanghai Jiao Tong University, which he completed from 2004 to 2008. He furthered his education at Colorado State University, where he earned a Doctor of Philosophy (PhD) in Computer Science from 2008 to 2014. His research expertise encompasses distributed systems, cloud computing, and machine learning, with specific interests in dynamic load balancing and execution time prediction.
Background
Zhiquan Sui's professional background includes significant experience in software engineering and research. He worked as a Research Assistant at Colorado State University from 2009 to 2014, where he engaged in various machine learning projects, including the development of a feature selection algorithm. He also completed an internship at Intel Corporation from 2007 to 2008, contributing to High Performance Computing by proving conditions for Generalized Change of Basis (GCoB) and implementing it in the AlphaZ system.
Research Contributions
During his PhD research, Zhiquan Sui developed orchestration algorithms based on iterative MapReduce for distributed stochastic discrete event simulations. His work in machine learning included projects involving Support Vector Machines, where he focused on algorithm development and performance profiling with diverse datasets.