Biography

Lin Chen is Chief Scientist of Wyze Labs,  leading the AI Team and Subscription Engineering Team to build smart home & home security products and services, with the mission of making great technology accessible to everyone by building a trusted video AI platform that makes life safe, convenient, fulfilling, and joyful. Prior to that, Lin was a Principal Scientist at Futurewei (Huawei Research USA) ,  leading the efforts to conducting R&D in computer vision, to improve products, launch new products, and explore new directions . Prior to that, Lin was a Senior Applied Scientist at Amazon. Before joining Amazon, Lin was a Research Scientist at the Ocular Imaging Programme, directed by Jimmy Jiang Liu, at the Institute for Infocomm Research (I²R).  Lin obtained his Ph.D. degree from the School of Computer Engineering, Nanyang Technological University in 2014, advised by Professor Dong Xu and co-advised by Processor Ivor Wai-Hung Tsang, and his B.Eng. from the Electronic Engineering and Information Science (EEIS) in University of Science and Technology of China (USTC) in 2009.

Research Interests

• Computer Vision: Object Detection/Recognition, Image Classification/Annotation/Retrieval, Event Recognition, Gender Recognition, Medical Image Analysis.

• Machine Learning: Deep Learning, Support Vector Machine, Manifold Regularization, Semi-Supervised Learning, Large-Scale Learning, Domain Adaptation & Transfer Learning, Multiple Kernel Learning.

Selected Publications

[Google Scholar]

[view full list here]

• Xinyi Zhao, Congjing Zhang, Pei Guo, Wei Li, Lin Chen, Chaoyue Zhao, Shuai Huang, "SmartHome-Bench: A Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language Models," in the Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshop, 2025.

• Mohammad Mahdi Kamani, Yuhang Yao, Hanjia Lyu, Zhongwei Cheng, Lin Chen, Liangju Li, Carlee Joe-Wong, Jiebo Luo, "Wyze Rule: Federated Rule Dataset for Rule Recommendation Benchmarking, " in 37th Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS), 2023.   [Dataset] [Challenge]

• Zhongjie Yu, Shuyang Wang, Lin Chen, Zhongwei Cheng, "HalluAudio: Hallucinate Frequency as Concepts for Few-Shot Audio Classification," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. 

• Yuhang Yao, Mohammad M. Kamani, Zhongwei Cheng, Lin Chen, Carlee Joe-Wong, Tianqiang Liu, "FedRule: Federated Rule Recommendation System with Graph Neural Networks," ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), 2023.

• Sheng Liu, Zhongwei Cheng, Lin Chen, Jiebo Luo, Junsong Yuan,  "A Compositional Model for Visual Relationship Grounding," IEEE Transactions on Image Processing (T-IP), 2022

• Yiming Xu, Lin Chen, Lixin Duan, Ivor Tsang, Jiebo Luo, "Open Set Domain Adaptation with Soft Unknown-Class Rejection," IEEE Transactions on Neural Networks and Learning Systems (T-NNLS),  2021.

• Jin Chen, Xinxiao Wu, Lixin Duan, Lin Chen, "Sequential Instance Refinement for Cross-Domain Object Detection in Images," IEEE Transactions on Image Processing (T-IP), 2021.

• Gaoang Wang, Lin Chen,  Tianqiang Liu, Mingwei He, Jiebo Luo, "DAIL: Dataset-Aware and Invariant Learning for Face Recognition," International Conference on Pattern Recognition (ICPR), Milan, Italy, December 2020.

• Yiming Xu , Lin Chen, Zhongwei Cheng, Lixin Duan, Jiebo Luo, "Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation," The Conference on Empirical Methods in Natural Language Processing (EMNLP), Findings of EMNLP, November 2020.

• Zhongjie Yu, Lin Chen, Zhongwei Cheng, Jiebo Luo, "TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning," in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR),  June 2020. 

• Wen Li, Lin Chen, Dong Xu, Luc Van Gool, "Visual Recognition in RGB Images and Videos by Learning from RGB-D Data," IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2017

• Li Niu, Xinxing Xu, Lin Chen, Lixin Duan, and Dong Xu, "Action and Event Recognition in Videos by Learning From Heterogenous Web Sources," IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), March 2016

• Lin Chen, Wen Li, and Dong Xu, "Recognizing RGB Images by Learning from RGB-D Data," in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 1418-1425.

• Lin Chen, Dong Xu, Ivor W. Tsang, and Xuelong Li, "Spectral Embedded Hashing for Scalable Image Retrieval," IEEE Transactions on Systems, Man, and Cybernetics, Part B (T-SMCB), November 2013.

• Lin Chen, Dong Xu, Ivor W. Tsang, and Jiebo Luo, "Tag-based Image Retrieval Improved by Augmented Features and Group-based Refinement," IEEE Transactions on Multimedia (T-MM), 14(4):1057-1067, August 2012

• Lin Chen, Lixin Duan, and Dong Xu, "Event Recognition in Videos by Learning From Heterogeneous Web Sources," in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2013, pp. 2666-2673. 

• Lin Chen, Ivor W. Tsang, Dong Xu, "Laplacian Embedded Regression for Scalable Manifold Regularization," IEEE Transactions on Neural Networks and Learning Systems (T-NNLS) 23(6): 902-915, June 2012. 

• Lin Chen, Dong Xu, Ivor W. Tsang and Jiebo Juo, "Tag-based Web Photo Retrieval Improved by Batch Mode Re-Tagging," in IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2010, pp. 3440-3446. 

Awards

• The 2nd Place in Multi-Camera Multiple People Tracking Challenge 2021 - Camera View Track link 

• The 3rd Place in WebVision Challenge 2019 link 

• The 4th Place in Challenge-2019 on Object Detection in Aerial Images 2019

• Multi-Media Prize Paper Award 2014  link 

Professional Services

• Reviewer for Journals:

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)

  • IEEE Transactions on Image Processing (T-IP)

  • IEEE Transactions on Neural Networks and Learning Systems (T-NNLS)

  • IEEE Transactions on Multimedia (T-MM)

  • IEEE Transactions on Systems, Man, and Cybernetics: Part B (T-SMCB)

  • International Journal on Computer Vision (IJCV)

  • Neurocomputing (Elesvier)

  • Machine Vision and Applications (MVAP)

  • The Visual Computer

  • IPSJ Transactions on Computer Vision and Applications (CVA)

• Program Committee Member (Reviewer) for Conferences: CVPR 2011 - 2016, 2018 - 2011; ICCV 2013 - 2015, 2019 - 2021; ECCV 2012, 2016 - 2020; NIPS 2015; IJCAI 2013, 2020; ACCV 2016; AAAI 2017-2020; BMVC 2018-2020

• External Reviewer for Conferences: ICME 2013 - 2014

• Organizer/co-organizer 

  • ICDM Workshop on Practical Transfer Learning 2015

• Teaching

  • Spring 2012: CE1007/CZ1007, Data Structures, School of Computer Engineering, Nanyang Technological University, Instructor

  • Fall 2013: CE1003/CZ1003, Introduction to Computational Thinking, Nanyang Technological University, Teaching Assistant