Albert Zhang

Albert Zhang is a highly skilled professional with extensive experience in quantitative research and machine learning. Since December 2022, Albert has been serving as a Blockchain and Quantitative Researcher at Injective Labs. Previous roles include Quantitative Researcher at Weiss Asset Management and Quantitative Trader at Optiver. Albert's technical expertise is complemented by a background as a Machine Learning Software Engineer at Scale AI and as a Machine Learning Research Assistant at Harvard University. Additional experience includes a position on Google's Machine Learning Team and founding Helping Everyday, Inc., a nonprofit organization. Albert's education is rooted in computer science, with ongoing master's and bachelor's degrees at Institut Français de la Mode, alongside studies in mathematics at Georgia Institute of Technology.