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I am Yonggan Fu, a final-year PhD student at Georgia Institute of Technology, working with Dr. Yingyan (Celine) Lin. I'm also an upcoming Research Scientist at NVIDIA Research. Before that, I obtained my 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. I am a recipient of IBM PhD Fellowship and was selected as Machine Learning and Systems Rising Stars 2023.

My research focus is to democratize cutting-edge AI technology on everyday devices via developing efficient and robust AI models and co-designing the corresponding hardware systems. My 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). My CV can be found here (lastest update: Feb. 2025).

   /      /      /   yfu314 [at] gatech (dot) edu & yonggan (dot) gatech [at] gmail (dot) com


Research Interest



News



Selected Publications (see full publication list here; * indicates equal contribution)

Yonggan Fu*, Xin Dong*, Shizhe Diao, Wonmin Byeon, Zijia Chen, Ameya Sunil Mahabaleshwarkar, Shih-Yang Liu, Matthijs Van Keirsbilck, Min-Hung Chen, Yoshi Suhara, Yingyan (Celine) Lin, Jan Kautz, Pavlo Molchanov
Hymba: A Hybrid-head Architecture for Small Language Models
ICLR 2025 [Paper] [Code] [Hymba-1.5B-Base][Hymba-1.5B-Instruct]
Spotlight Paper
Yonggan Fu, Zhongzhi Yu, Jiayi Qian, Junwei Li, Yongan Zhang, Dachuan Shi, Xiangchi Yuan, Roman Yakunin, Yingyan (Celine) Lin
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
NeurIPS 2024 [Paper] [Code] [Video] [Slide]
Yonggan Fu, Huaizhi Qu, Zhifan Ye, Chaojian Li, Kevin Zhao, Yingyan (Celine) Lin
Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields
ECCV 2024 [Paper] [Code] [Video] [Slide]
Oral Paper
Yonggan Fu*, Yongan Zhang*, Zhongzhi Yu*, Sixu Li, Zhifan Ye, Chaojian Li, Cheng Wan, Yingyan (Celine) Lin
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
ICCAD 2023 [Paper] [Slide], Covered by [The Next Platform] [Anastasi In Tech]
Yonggan Fu, Ye Yuan, Souvik Kundu, Shang Wu, Shunyao Zhang, Yingyan (Celine) Lin
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations
ICML 2023 [Paper] [Code] [Video] [Slide]
In collaboration with Intel
Yonggan Fu, Yuecheng Li, Chenghui Li, Jason Saragih, Peizhao Zhang, Xiaoliang Dai, Yingyan (Celine) Lin
Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence
CVPR 2023 [Paper] [Video] [Slide]
In collaboration with Meta
Yonggan Fu*, Zhifan Ye*, Jiayi Yuan, Shunyao Zhang, Sixu Li, Haoran You, Yingyan (Celine) Lin
Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design
ISCA 2023 [Paper] [Video] [Slide]
2nd Place in the 33rd ACM SIGDA/IEEE CEDA University Demonstration at DAC 2023
Yonggan Fu, Yang Zhang, Kaizhi Qian, Zhifan Ye, Zhongzhi Yu, Cheng-I Lai, Yingyan (Celine) Lin
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
NeurIPS 2022 [Paper] [Code] [Video] [Slide]
In collaboration with MIT-IBM Watson AI Lab
Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan (Celine) Lin
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
ICML 2022 [Paper] [Code] [Video], Covered by [The Next Platform]
In collaboration with Meta
Yonggan Fu*, Shunyao Zhang*, Shang Wu*, Cheng Wan, Yingyan (Celine) Lin
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
ICLR 2022 [Paper] [Code] [Video]
Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan (Celine) Lin
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
NeurIPS 2021 [Paper] [Code] [Video]
In collaboration with MIT-IBM Watson AI Lab
Yonggan Fu, Yang Zhao, Qixuan Yu, Chaojian Li, Yingyan (Celine) Lin
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
MICRO 2021 [Paper] [Video]
Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan (Celine) Lin
SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam
ICCV 2021 [Paper] [Code] [Video]
In collaboration with MIT-IBM Watson AI Lab
Yonggan Fu, Qixuan Yu, Meng Li, Vikas Chandra, Yingyan (Celine) Lin
Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference
ICML 2021 [Paper] [Code] [Video]
In collaboration with Meta
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan (Celine) Lin
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
ICML 2021 [Paper] [Code] [Video]
In collaboration with MIT-IBM Watson AI Lab
Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan (Celine) Lin
CPT: Efficient Deep Neural Network Training via Cyclic Precision
ICLR 2021 [Paper] [Code] [Video]
Spotlight paper (top 6%), in collaboration with Meta
Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan (Celine) Lin
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
NeurIPS 2020 [Paper] [Code] [Video]
Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan (Celine) Lin, Zhangyang Wang
AutoGan-Distiller: Searching to Compress Generative Adversarial Networks
ICML 2020 [Paper] [Code] [Video]


Education



Experience



Selected Awards



Community Services



Invited Talks