Ran Liu

Ran Liu has a long and varied career in the fields of AI, machine learning, and data science. In 2020, Ran was appointed Chief AI Scientist at Amira Learning, where they lead the development of AI models that power Amira's ability to automatically understand students' oral reading, detect/classify reading miscues and infer skill mastery, and select personalized, just-in-time interventions to improve foundational reading skills. From 2019 to 2020, Ran was a Machine Learning Mentor at SharpestMinds, where they mentored aspiring data scientists to produce production-grade machine learning projects and positioned them for job success. In 2017, Ran was Chief Data Scientist at MARi and a Data Science Advisor at WestEd. From 2009 to 2017, Ran was a Postdoctoral Fellow at Carnegie Mellon University's School of Computer Science, where they managed over 8 different interdisciplinary EdTech research projects resulting in a dozen peer-reviewed publications. Ran also developed predictive, explanatory models that improved upon the state-of-the art and significantly improved learning outcomes when deployed in the classroom. In 2015, Ran was Scientific Advisor at RoboTutor, where they led the development of math curriculum content and user testing for Carnegie Mellon's RoboTutor team, a finalist in the $15M Global Learning XPRIZE Competition. From 2011 to 2015, Ran was a Private Tutor at Wyzant, and from 2006 to 2009, they were a Teaching Assistant at Carnegie Mellon University.

Ran Liu obtained a High School Diploma from Thomas Jefferson High School for Science and Technology in 2004. Ran then attended Carnegie Mellon University, where they obtained a Bachelor of Science (B.S.) in Cognitive Science in 2008. Subsequently, they returned to Carnegie Mellon University where they earned a Doctor of Philosophy (Ph.D.) in Cognitive Science in 2014.