About Me

I am a PHD student in National University of Singapore, and my adviser is Gim Hee Lee. I worked as a computer vision algorithm engineer in Alibaba Damo Academy, and my tutors were Mr. Sun Xiuyu and Dr. Lin Ming. My research interests are machine learning and 3D computer vision, especially in neural rendering, visual perception and understanding in the real world. I just got my master’s degree in Pattern Recognition and Intelligent Systems from Beihang University.

Journal & Conference Papers

• Hanlin Chen, Li Chen, Mengqi Guo, Zhiwen Yan, Gim Hee Lee. GNeSF: Generalizable Neural Semantic Fields. NeurIPS, 2023.

• Hanlin Chen, Li’an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, Rongrong Ji, David Doermann, Guodong Guo. Binarized Neural Architecture Search for Efficient Object Recognition. IJCV, 2021.

• Hanlin Chen, Baochang Zhang, Song Xue, Xuan Gong, Hong Liu, Rongrong Ji, David Doermann. Anti-Bandit Neural Architecture Search for Model Defense. ECCV, 2020. [CODES]

• Hanlin Chen, Li’an Zhuo, Baochang Zhang, Xiawu Zheng, Jianzhuang Liu, David Doermann, Rongrong Ji. Binarized Neural Architecture Search. AAAI, 2020. [CODES]

• Song Xue^†, Hanlin Chen^†(co-first), Chunyu Xie, Baochang Zhang, Xuan Gong, David Doermann. Fast and Unsupervised Neural Architecture Evolution for Visual Representation Learning. IEEE Computational Intelligence Magazine, 2021.

• Hanlin Chen, Xudong Zhang, et al. Efficient Facial Landmark Localization based on Binarized Neural Networks. Electronics, 2020.

• Li’an Zhuo, Baochang Zhang, Linlin Yang, Hanlin Chen, Qixiang Ye, David Doermann, Rongrong Ji, Guodong Guo. Cogradient Descent for Bilinear Optimization. CVPR, 2020. [CODES]

• Li’an Zhuo, Baochang Zhang, Hanlin Chen, Linlin Yang, Chen Chen, Yanjun Zhu, David Doermann. CP-NAS: Child-Parent Neural Achitecture Search for 1-bit CNNs. IJCAI 2020.

• Sheng Xu, Hanlin Chen, Kexin Liu, Jinhu Lii, Baochang Zhang, Efficient Block Pruning based on kernel and feature stabilization. Neural Computing and Applications, 2020.

• Sheng Xu, Hanlin Chen, Kexin Liu, Jinhu Lii, Baochang Zhang. Efficient Block Pruning based on kernel and feature stablization. Proceedings of Digital Image Computing: Techniques and Applications, 2019. (DICTA 2019)

• Chunlei Liu, Wenrui Ding, Yu Hu, Hanlin Chen, Baochang Zhang, Shuo Liu. Guided Convolutional Network. 13th International Conference on Distributed Smart Cameras. (ICDSC 2019)

Research Experience

• Machine Intelligence, Vision Lab (Alibaba DAMO Academy)

  • Research on Neural Architecture Search (NAS).

  • Research on 2D & 3D vision

• The Baochang Zhang’s Group (Beihang University)

  • Research on Neural Architecture Search (NAS).

  • Research on model quantization and pruning.

  • Research on unsupervised learning.

  • Research on adversarial training.

Education

• Beihang University, Beijing, China

  Master of Pattern Recognition and Intelligent System, Sep 2018 - Jan 2021

• Shenyang Aerospace University, Shenyang, China

  Bachelor of Aircraft Design and Engineering, Sep 2014 - Jun 2018

Awards

• Excellent Graduation Thesis in Beihang University, 2021.

• Excellent Graduate in Beihang University, 2021.

• National Scholarship in China, 2021.

• Liaoning Provincial Government Scholarship, 2016.

Skills

• Programming Languages: Python, C/C++, matlab

• Technologies and Frameworks: Pytorch, Tensorflow, Linux

Contact

Institution: Machine Intelligence, Vision Lab, Alibaba DAMO Academy, Beijing, China

E-mail: hlchen@buaa.edu.cn or hlinchen@foxmail.com or hlchen1105@gmai.com

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