Woongjib Choi

Hello! I am an incoming Ph.D. student in EECS at MIT. I received my B.S. and M.S. in Electrical and Electronic Engineering from Yonsei University (South Korea) in 2024 and 2026, respectively, and worked at DSPAI Lab under Prof. Hong-Goo Kang. My primary research goal is to bridge the gap between classic signal processing and modern deep learning, with interests spanning audio and speech processing, audio compression, and generative models.

My first research experience as an undergraduate at the SRIP Lab involved implementing and analyzing traditional image signal processing algorithms such as denoising, demosaicing, and super-resolution. This interest in combining established algorithms with data-driven approaches has continued throughout my graduate studies.

During my M.S., I focused on neural audio codecs and audio super-resolution. Specifically, I worked on non-blind bandwidth extension using side information for legacy audio codec enhancement, as well as blind audio super-resolution using flow matching, where both approaches are grounded in time-frequency and subband analysis. Currently, my research interests extend to audio tokenization and generative models for audio, with additional experience in multilingual speech processing.