Haibo Wang
About Haibo Wang
Haibo Wang is a Principal Applied Machine Learning Scientist with extensive experience in developing AI applications, particularly in computer vision and machine learning for medical solutions. He has held positions at notable institutions including Philips Research North America and Case Western Reserve University, and he is currently employed at Inari Medical.
Work at Inari Medical
Haibo Wang serves as Principal Applied ML Scientist at Inari Medical, a position he has held since 2022. In this role, he focuses on the development of machine learning solutions that enhance medical technologies. His work contributes to the company's mission of improving patient outcomes through innovative applications of artificial intelligence.
Previous Experience in Academia
Before joining Inari Medical, Haibo Wang worked as an Assistant Professor at Shandong University for seven months in 2011. He later served as a Senior Research Associate at Case Western Reserve University from 2012 to 2015. His academic background includes significant contributions to research in pattern recognition and computer vision.
Educational Background
Haibo Wang obtained his Doctor of Philosophy (PhD) in Pattern Recognition and Computer Vision from the University of Chinese Academy of Sciences, where he studied from 2005 to 2011. He also earned a Bachelor's Degree from Shandong University in Control Science and Engineering between 2001 and 2005. Additionally, he completed another PhD in Computer Science at the University of Lille 1 Sciences and Technology from 2007 to 2010.
Experience at Philips Research North America
Haibo Wang worked at Philips Research North America as a Senior Scientist and Project Lead from 2015 to 2022. During his tenure, he focused on creating machine learning and computer vision solutions aimed at addressing medical challenges, particularly in cleaning vascular clots.
Research Interests and Contributions
Haibo Wang has a strong interest in the application of artificial intelligence for societal benefit, often referred to as 'AI for good.' He specializes in developing machine learning pipelines and dataflows on AWS platforms, contributing to advancements in healthcare technology.