Summary
Guan-Ting Lin is a speech and machine learning researcher with a PhD from NTU EECS and six years of experience translating cutting-edge research into production-grade speech systems. Based in the Bay Area, he has interned and collaborated with Meta AI, Google DeepMind, and Amazon, contributing to full‑duplex speech LMs, language expansion for Gemini, and the first end-to-end Speech LLM with RL accepted to ACL 2025. His work at Amazon on NAS for acoustic event classification and paralinguistics-enhanced multimodal LLMs led to multiple ICASSP publications, demonstrating a knack for combining theoretical advances with resource‑efficient engineering. Currently at ByteDance and concurrently working with Meta’s Superintelligence Lab Voice Modeling Team, he focuses on scalable speech models and alignment. Colleagues describe him as equally comfortable prototyping novel architectures and shepherding models toward real-world deployment. An unassuming detail: he bridges medical imaging denoising experience from early research with contemporary speech modeling, reflecting a broad applied-ML toolkit.
6 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Electrical, Electronics and Communications Engineering, Doctor of Philosophy - PhD, Electrical, Electronics and Communications Engineering at National Taiwan University
Bachelor's degree, Advanced Applied Artificial Intelligence Program, Bachelor's degree, Advanced Applied Artificial Intelligence Program at National Tsing Hua University