People

Yonggan Fu

Yonggan Fu obtained his PhD from Georgia Institute of Technology in May 2025. Prior to that, he received his Bachelor's degree with a dual major in Applied Physics and Computer Science from the School of The Gifted Young at the University of Science and Technology of China in 2019. He is a recipient of IBM PhD Fellowship and was selected as Machine Learning and Systems Rising Stars 2023.

His research focuses on democratizing cutting-edge AI technology on everyday devices by developing efficient foundation models. His research work has been featured as spotlight papers at ICLR (2025 & 2021 & 2021 & 2020), an oral paper at ECCV (2024), and selected as an IEEE Micro Top Pick (2023).

Research Area(s)
Artificial Intelligence and Machine Learning
Generative AI
Natural Language Processing
Main Field of Interest
Artificial Intelligence and Machine Learning
Google Scholar
https://scholar.google.com/citations?user=pt3GfXcAAAAJ&hl=en&oi=ao

Publications

2026

Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding
Yonggan Fu, Lexington Whalen, Abhinav Garg, Chengyue Wu, Maksim Khadkevich, Nicolai Oswald, Enze Xie, Daniel Egert, Sharath Turuvekere Sreenivas,, Shizhe Diao, Chenhan Yu, Ye Yu, Weijia Chen, Sajad Norouzi, Jingyu Liu, Shiyi Lan, Ligeng Zhu, Jin Wang, Jindong Jiang, Morteza Mardani, Mehran Maghoumi, Song Han, Ante Jukić, Nima Tajbakhsh, Jan Kautz, Pavlo Molchanov

2025

Hymba: A Hybrid-head Architecture for Small Language Models
Xin Dong, Yonggan Fu*, Shizhe Diao, Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van keirsbilck, Min-Hung Chen, Yoshi Nishi, Yingyan Celine Lin, Jan Kautz, Pavlo Molchanov
Hymba - ICLR 2025
ICLR spotlight paper