About

Qian Wan is a highly experienced Staff Software Engineer at Facebook, with a passion for tackling unknown problems and exploring new solutions. With a background in machine learning, data mining, and bioinformatics, Qian is skilled in developing innovative solutions that push the boundaries of what is possible with technology. Qian's expertise in software engineering has been honed over more than six years of relevant experience, during which time they have held a range of roles in both industry and academia. Prior to joining Facebook, Qian worked as a Scientific Computing Engineer at Emerald Cloud Lab and as a Bioinformatics Scientist at Affymetrix. In both roles, they demonstrated a deep understanding of the complex challenges involved in developing cutting-edge technologies for the life sciences. Qian's educational background is equally impressive, having earned a Master of Science in Computational Biology from Carnegie Mellon University, a Master of Science in Electrical Engineering from Texas Tech University, and a Bachelor of Engineering in Software Engineering from Jinan University. This diverse range of academic achievements has equipped Qian with a broad range of skills and knowledge that they are able to apply to their work in software engineering. As a software engineer at Facebook, Qian is currently working on Core Feed Ranking, where they are responsible for developing machine learning algorithms that help to optimize the social media platform's news feed. Qian's expertise in machine learning and data mining has been instrumental in the success of this project, and they continue to be a valued member of the Facebook team. In addition to their work at Facebook, Qian is also an accomplished researcher, with a number of publications to their name. Their work has been featured on Google Scholar, where they have received recognition for their contributions to the field of machine learning and bioinformatics. Overall, Qian Wan is a highly skilled and accomplished software engineer with a passion for solving complex problems and pushing the boundaries of what is possible with technology. Their expertise in machine learning, data mining, and bioinformatics make them a valuable asset to any organization, and their track record of success in both industry and academia speaks to their exceptional talent and dedication to their craft.