Zhijian Liu

Zhijian Liu
zhijian [at] mit (dot) edu

I am a research scientist at NVIDIA. I finished my PhD at MIT, advised by Song Han. My research focuses on efficient machine learning and systems.

Email / Google Scholar / LinkedIn / GitHub

News

I commit 1 hour every week to provide guidance, suggestions, and/or mentorships for students from underrepresented groups or whoever is in need. Please fill in this form if you are interested.
I was selected as one of the Rising Stars in Data Science by UChicago and UCSD!
I was selected as one of the Rising Stars in ML and Systems by MLCommons!
I was awarded Qualcomm Innovation Fellowship. Thanks, Qualcomm!
Our SPVCNN++ won the first place in nuScenes LiDAR Segmentation Challenge.
Our HAQ has been integrated into Intel's OpenVINO toolkit.

Publications ( show selected / show all )

NVILA: Efficient Frontier Visual Language Models
Zhijian Liu*, Ligeng Zhu*, Baifeng Shi, Zhuoyang Zhang, Yuming Lou, Shang Yang, Haocheng Xi, Shiyi Cao, Yuxian Gu, Dacheng Li, Xiuyu Li, Yunhao Fang, Yukang Chen, Cheng-Yu Hsieh, De-An Huang, An-Chieh Cheng, Vishwesh Nath, Jinyi Hu, Sifei Liu, Ranjay Krishna, Daguang Xu, Xiaolong Wang, Pavlo Molchanov, Jan Kautz, Hongxu Yin, Song Han, Yao Lu*
CVPR 2025 / Paper / Project Page / Code

SparseVILA: Query-Aware Visual Sparsity Should Happen at Decoding
Samir Khaki, Junxian Guo, Jiaming Tang, Shang Yang, Yukang Chen, Konstantinos N. Plataniotis, Yao Lu, Song Han, Zhijian Liu
ICCV 2025

SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
Samir Khaki*, Xiuyu Li*, Junxian Guo*, Ligeng Zhu, Chenfeng Xu, Konstantinos N. Plataniotis, Amir Yazdanbakhsh, Kurt Keutzer, Song Han, Zhijian Liu
ICML 2025 / Paper

Fast-dLLM: Training-Free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
Chengyue Wu, Hao Zhang, Shuchen Xue, Zhijian Liu, Shizhe Diao, Ligeng Zhu, Ping Luo, Song Han, Enze Xie
arXiv 2025 / Paper / Project Page / Code

FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer
Zhijian Liu*, Xinyu Yang*, Haotian Tang, Shang Yang, Song Han
CVPR 2023 / Paper / Project Page / Code

SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer
Xuanyao Chen*, Zhijian Liu*, Haotian Tang, Li Yi, Hang Zhao, Song Han
CVPR 2023 / Paper / Project Page / Code

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
Zhijian Liu*, Haotian Tang*, Alexander Amini, Xinyu Yang, Huizi Mao, Daniela L. Rus, Song Han
ICRA 2023 / Paper / Project Page / Code

TorchSparse: Efficient Point Cloud Inference Engine
Haotian Tang*, Zhijian Liu*, Xiuyu Li*, Yujun Lin, Song Han
MLSys 2022 / Paper / Project Page / Code

VISTA 2.0: An Open, Data-Driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles
Alexander Amini*, Tsun-Hsuan Wang*, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, Daniela L. Rus
ICRA 2022 / Paper / Project Page / Code / MIT News

Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications
Han Cai*, Ji Lin*, Yujun Lin*, Zhijian Liu*, Haotian Tang*, Hanrui Wang*, Ligeng Zhu*, Song Han
TODAES 2022 / Paper

LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision
Zhijian Liu, Simon Stent, Jie Li, John Gideon, Song Han
ICCV 2021 / Paper / Project Page

SemAlign: Annotation-Free Camera-LiDAR Calibration with Semantic Alignment Loss
Zhijian Liu*, Haotian Tang*, Sibo Zhu*, Song Han
IROS 2021 / Paper / Project Page

PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution
Zhijian Liu*, Haotian Tang*, Shengyu Zhao, Kevin Shao, Song Han
TPAMI 2021 / Paper / Project Page

Efficient and Robust LiDAR-Based End-to-End Navigation
Zhijian Liu*, Alexander Amini*, Sibo Zhu, Sertac Karaman, Song Han, Daniela L. Rus
ICRA 2021 / Paper / Project Page / CSAIL News

Differentiable Augmentation for Data-Efficient GAN Training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han
NeurIPS 2020 / Paper / Project Page / Code

Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
Haotian Tang*, Zhijian Liu*, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, Song Han
ECCV 2020 / Paper / Project Page / Code

DataMix: Efficient Privacy-Preserving Edge-Cloud Inference
Zhijian Liu*, Zhanghao Wu*, Chuang Gan, Ligeng Zhu, Song Han
ECCV 2020 / Paper

HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
Hanrui Wang, Zhanghao Wu, Zhijian Liu, Han Cai, Ligeng Zhu, Chuang Gan, Song Han
ACL 2020 / Paper / Project Page / Code / MIT News

GAN Compression: Efficient Architectures for Interactive Conditional GANs
Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, Song Han
CVPR 2020 / Paper / Project Page / Code

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
Tianzhe Wang*, Kuan Wang*, Han Cai, Ji Lin, Zhijian Liu, Hanrui Wang, Yujun Lin, Song Han
CVPR 2020 / Paper / Code

Hardware-Centric AutoML for Mixed-Precision Quantization
Kuan Wang*, Zhijian Liu*, Yujun Lin*, Ji Lin, Song Han
IJCV 2020 / Paper

Lite Transformer with Long-Short Range Attention
Zhanghao Wu*, Zhijian Liu*, Ji Lin, Yujun Lin, Song Han
ICLR 2020 / Paper / Code

Point-Voxel CNN for Efficient 3D Deep Learning
Zhijian Liu*, Haotian Tang*, Yujun Lin, Song Han
NeurIPS 2019 / Paper / Project Page / Code / NVIDIA News
Spotlight Presentation

Deep Leakage from Gradients
Ligeng Zhu, Zhijian Liu, Song Han
NeurIPS 2019 / Paper / Project Page / Code

AutoML for Architecting Efficient and Specialized Neural Networks
Han Cai*, Ji Lin*, Yujun Lin*, Zhijian Liu*, Kuan Wang*, Tianzhe Wang*, Ligeng Zhu*, Song Han
IEEE Micro 2019 / Paper

HAQ: Hardware-Aware Automated Quantization with Mixed Precision
Kuan Wang*, Zhijian Liu*, Yujun Lin*, Ji Lin, Song Han
CVPR 2019 / Paper / Project Page / Code
Oral Presentation

Unsupervised Discovery of Parts, Structure, and Dynamics
Zhenjia Xu*, Zhijian Liu*, Chen Sun, Kevin Murphy, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
ICLR 2019 / Paper / Project Page / Code

Learning to Exploit Stability for 3D Scene Parsing
Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
NeurIPS 2018 / Paper / Project Page

AMC: AutoML for Model Compression and Acceleration on Mobile Devices
Yihui He*, Ji Lin*, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han
ECCV 2018 / Paper / Project Page / Code

Physical Primitive Decomposition
Zhijian Liu, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu
ECCV 2018 / Paper / Project Page