Jingxiao Ma is currently a fourth-year Ph.D. candidate in Electrical and Computer Engineering at Brown University. He completed his Bachelor of Science in Computer Science at the University of Nottingham in 2018 and his Master of Science from Brown University in 2020. He then joined the SCALE lab at Brown University. Initially, his research focused on electronic design automation and approximate computing, leading to his development of a comprehensive methodology for generating approximate circuits using Boolean matrix factorization. Presently, his research has expanded to encompass Deep Learning, Adaptive/Dynamic Neural Networks, and Edge Computing. He is now developing a low-precision training algorithm. Additionally, he is integrating his knowledge in electronic design automation with Large Language Models to investigate their potential in revolutionizing circuit design and analysis.