Song Luan

Song Luan has extensive work experience in both research and development roles. From 2018 to the present, Luan has been the Head of PoC Device at DNANUDGE, responsible for overseeing the development of a proof-of-concept device. Prior to this, Luan worked as a Senior Research And Development Engineer at DNANUDGE from 2018 to 2022.

Before joining DNANUDGE, Luan held various research positions at Imperial College London. From 2017 to 2018, Luan worked as a Research Associate, focusing on developing a scalable miniature system for real-time hardware spike sorting and creating a platform for recording neural signals. From 2014 to 2017, Luan worked as a Research Associate, responsible for providing chronic in-vivo recording solutions and conducting research on integrated electronics for safe and efficient intraspinal microstimulation. Luan also worked as a Research Assistant from 2010 to 2014, primarily focusing on their Ph.D. research in developing integrated electronics for selective intraspinal microstimulation.

Song Luan completed a Doctor of Philosophy (Ph.D.) degree in Electrical and Electronics Engineering from Imperial College London from 2010 to 2014. Prior to that, from 2009 to 2010, Song Luan obtained a Master's Degree in Analogue and Digital Integrated Circuit Design from the same institution. Before pursuing the Master's degree, from 2008 to 2009, Song Luan earned a Bachelor's Degree in Electrical & Electronic Engineering from the University of Birmingham. Song Luan's undergraduate studies began in 2005 at Fudan University, where they earned a Bachelor's Degree in Electronic Engineering from 2005 to 2009. Song Luan completed their high school education at Tianjin Yaohua High School from 2002 to 2005, graduating with a High School Diploma. Additionally, Song Luan obtained several certifications, including Engineering Drawings for Manufacturing, Introduction to Geometric Dimensioning and Tolerancing, and Quality Management Foundations from LinkedIn in December 2020. They also completed a certification in Machine Learning from Coursera in July 2020.