Yongyi Zang

Yongyi Zang is a Machine Learning Engineer at Neosensory, Inc. since June 2023, known for optimizing training, data collection, and generation pipelines, achieving a 12.2x faster training process and a 30x increase in training data. Previously, as a Research Assistant at AIR Lab from July 2021 to June 2023, Yongyi developed a real-time web-based musical agent for interactive jamming, showcasing the project at ISMIR and in the Journal of AES, and created the largest synthesized guitar tablature dataset, significantly expanding the existing resources. Yongyi also worked as a Software Development Engineer at Voice Biometrics Group for a brief period in 2022, successfully migrating backend systems for improved deployment speed and optimizing speaker verification processes. Yongyi holds a Bachelor of Applied Science in Audio & Music Engineering with minors in Computer Science from the University of Rochester, and has previous education at the University of California, Berkeley, and Nankai High School.