Zhijian Liu

Zhijian Liu
zhijian [at] ucsd (dot) edu

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

I am always looking for talented research interns to join our group! If you're interested, please fill out this form.

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 )

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