Xiaolin Wang
About Xiaolin Wang
Xiaolin Wang serves as the Technical Director of Data Science at Securiti, where he focuses on the safe use of data and GenAI. With over a decade of experience in machine learning and artificial intelligence, he has held various significant roles in the tech industry, contributing to advancements in data security and wearable devices.
Work at Securiti
Xiaolin Wang serves as the Technical Director of Data Science at Securiti, a position he has held since 2020. In this role, he focuses on enabling the safe use of data and Generative AI through Securiti's Data Command Center. He has contributed to the development of core algorithms for cloud and web security products. Under his leadership, the team at Securiti has received several industry accolades, including recognition as the 'Most Innovative Startup' by RSA and being listed among the 'Top 25 Machine Learning Startups' by Forbes.
Previous Experience
Before joining Securiti, Xiaolin Wang worked at Netskope as a Senior Staff Data Scientist from 2019 to 2020. Prior to that, he was a Principal Data Scientist at Elastica, which was acquired by Symantec, from 2015 to 2019. He also served as a Machine Learning Consultant for Wearable Devices in 2015. His earlier experience includes a role as a Principal Data Scientist and Algorithm Engineer at Senseonics, Incorporated from 2008 to 2015, and a postdoctoral position at George Washington University from 2007 to 2008.
Education and Expertise
Xiaolin Wang holds a Doctor of Philosophy (PhD) in Mechanical Engineering from Stony Brook University, where he studied from 2005 to 2007. He also earned a Master's degree in Mechanical Engineering from the same institution from 2003 to 2005. His undergraduate education includes a Bachelor's degree in Mechanical Engineering from the University of Science and Technology of China, completed from 1998 to 2003. Additionally, he completed a Data Science BootCamp at Galvanize Inc in 2015.
Technical Skills and Contributions
Xiaolin Wang has over a decade of experience applying machine learning and artificial intelligence to long-term implantable sensors and wearable fitness and wellness devices. He has expertise in providing unified data intelligence, controls, and orchestration across hybrid multicloud environments. His work has significantly contributed to advancements in data science and security technologies.