Welcome to Lichen's Homepage

Lichen Wang (王莅尘)

Applied Scientist

Zillow Group

Russell Investments Center, 1301 Second Avenue,

Seattle, WA 98101, USA

Email: wanglichenxj [at] gmail [dot] com

wang.lich [at] northeastern [dot] edu

I'm an Applied Scientist in Zillow since 2021. I received my Ph.D. degree in SMILE Lab, Department of Electrical & Computer Engineering at Northeastern University under the supervision of Prof. Yun (Raymond) Fu, in 2021. I received my M.S. degree in Electrical Engineering from Xi'an Jiaotong University (XJTU), China, in 2016. I received my B.S. degree in Electrical Engineering from Harbin Institute of Technology (HIT), China, in 2013. My research interests include Machine Learning and Computer Vision.

Research Interests

    • Computer Vision, 3D data processing, and Deep Learning (CNN, RNN, GAN)

    • Data mining & graph representation learning

    • Subspace learning & sparse representation

    • Transfer Learning & domain adaptation

Working Experience

    • Applied Scientist at Zillow Group, WA, USA. Indoor image and 3D floor plan data processing and learning.

    • Research Intern at Samsung Research America, CA, USA. As a Machine Learning researcher in 05, 2020 - 08, 2020. Machine learning, Multi-view Learning, Computer Vision.

    • Research Intern at NEC Labs America, NJ, USA. As a Data Scientist in 05, 2019 - 08, 2019. Machine learning, graph representation learning.

    • Research Intern at Zebra Technology, IL, USA. As Computer Vision researcher in 06,2018 - 08, 2018. Object detection, domain adaptation.

    • Research Intern at Zebra Technology, IL, USA. As Computer Vision researcher in 06,2017 - 08, 2017. Vision based 3D data processing, tracking and recognition.

    • Research Intern at Nanjing Intelligent, Jiangsu, China. As Electrical engineer in 05, 2013 - 09, 2013. Simulation device for smart grids.

Publications

    • Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu, "Semi-supervised Domain Adaptive Structure Learning," IEEE Transactions on Image Processing (TIP) [Paper]

    • Lichen Wang, Zhengming Ding, Kasey Lee, Seungju Han, Jae-Joon Han, Changkyu Choi, Yun Fu, "Generative Multi-Label Correlation Learning," ACM Transactions on Knowledge Discovery from Data (TKDD) [Paper]

    • Yi Xu, Lichen Wang, Yizhou Wang, Can Qin, Yulun Zhang, Yun Fu, "MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning," 2022 International Joint Conference on Artificial Intelligence (IJCAI), Messe Wien, Vienna, Austria [Paper]

    • Yi Xu, Lichen Wang, Yizhou Wang, Yun Fu, "Adaptive Trajectory Prediction via Transferable GNN," 2022 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Paper]

    • Chang Liu, Lichen Wang, Yun Fu, "Meta Adversarial Weight for Unsupervised Domain Adaptation," 2022 SIAM International Conference on Data Mining (SDM) [Paper]

    • Yue Bai, Zhiqiang Tao, Lichen Wang, Sheng Li, Yu Yin, Yun Fu, "Collaborative Attention Mechanism for Multi-Modal Time Series Classification," 2022 SIAM International Conference on Data Mining (SDM) [Paper]

    • Lichen Wang, Yunyu Liu, Hang Di, Can Qin, Gan Sun, Yun Fu, "Semi-supervised Dual Relation Learning for Multi-label Classification," IEEE Transactions on Image Processing (TIP) [Paper]

    • Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu, "Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation," 2021 Neural Information Processing Systems (NeurIPS) [Code] [Paper]

    • Lichen Wang, Bo Zong, Yunyu Liu, Can Qin, Wei Cheng, Wenchao Yu, Xuchao Zhang, Haifeng Chen, Yun Fu, "Aspect-based Sentiment Classification via Reinforcement Learning," 2021 IEEE International Conference on Data Mining (ICDM) [Paper]

    • Chang Liu, Lichen Wang, Kai Li, Yun Fu, "Domain Generalization via Feature Variation Decorrelation," 2021 ACM Multimedia (MM) [Paper]

    • Songyang Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li, Yun Fu, "Skeleton Aware Multi-modal Sign Language Recognition," 2021 IEEE Computer Vision and Pattern Recognition (CVPR) Workshop [Code] [Paper] [Video] [Conference]

    • Lichen Wang, Zhengming Ding, Yun Fu, "Generic Multi-label Annotation via Adaptive Graph and Marginalized Augmentation," ACM Transactions on Knowledge Discovery from Data (TKDD), [Code] [Paper]

    • Can Qin, Lichen Wang, Qianqian Ma, Yu Yin, Huan Wang, Yun Fu, "Contradictory Structure Learning for Semi-supervised Domain Adaptation," 2021 SIAM International Conference on Data Mining (SDM), [Paper]

    • Yue Bai, Lichen Wang, Zhiqiang Tao, Sheng Li, Yun Fu, "Correlative Channel-Aware Fusion for Multi-View Time Series Classification," 2021 AAAI Conference on Artificial Intelligence (AAAI), [Paper]

    • Jiahua Dong, Yang Cong, Gan Sun, Bingtao Ma, Lichen Wang, "I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting," 2021 AAAI Conference on Artificial Intelligence (AAAI), [Paper] [Video]

    • Yue Bai, Lichen Wang, Yunyu Liu, Yu Yin, Yun Fu, "Dual-Side Auto-Encoder for High-Dimensional Time Series Segmentation," 2020 International Conference on Data Mining (ICDM), [Code] [Paper] [Poster]

    • Yunyu Liu, Lichen Wang, Yue Bai, Can Qin, Zhengming Ding, and Yun Fu, “Generative View-Correlation Adaptation for Semi-Supervised Multi-View Learning,” 2020 European Conference on Computer Vision (ECCV), [Code] [Paper] [Poster]

    • Lichen Wang, Bin Sun, Joseph Robinson, Taotao Jing, and Yun Fu, “EV-Action: Electromyography-Vision Multi-Modal Action Dataset,” 2020 IEEE International Conference on Automatic Face and Gesture Recognition (FG), Buenos Aires, Argentina [Code] [Paper] [Slides] [Video]

    • Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjing Song, Haifeng Chen, and Yun Fu, “Inductive and Unsupervised Representation Learning on Graph Structured Objects,” 2020 International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia [Code] [Paper] [Slides] [Video]

    • Lichen Wang, Yunyu Liu, Can Qin, Gan Sun, and Yun Fu, “Dual Relation Semi-supervised Multi-label Learning,” 2020 The National Conference on Artificial Intelligence (AAAI), New York, USA [Code] [Paper] [Spotlight] [Poster]

    • Can Qin, Haoxuan You, Lichen Wang, C.-C. Jay Kuo, and Yun Fu, “PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation,” 2019 Neural Information Processing Systems (NeurIPS), Vancouver, Canada [Code] [Paper]

    • Lichen Wang, Zhengming Ding, Seungju Han, Jae-Joon Han, Changkyu Choi, Yun Fu, "Generative Correlation Discovery Network for Multi-Label Learning," 2019 IEEE International Conference on Data Mining (ICDM) (Regular paper), Beijing, China [Code] [Paper] [Slides]

    • Denghui Zhang, Junming Liu, Hengshu Zhu, Yanchi Liu, Lichen Wang, Pengyang Wang, Hui Xiong," Job2Vec: Job Title Benchmarking with Collective Multi-View Representation Learning", 2019 ACM International Conference on Information and Knowledge Management (CIKM) (Regular paper), Beijing, China [Code] [Paper]

    • Lichen Wang, Zhengming Ding, Zhiqiang Tao, Yunyu Liu, Yun Fu, "Generative Multi-View Human Action Recognition," 2019 International Conference on Computer Vision (ICCV) (Oral Presentation), Seoul, Korea [Code] [Paper][Slides][Poster][Video]

    • Can Qin, Lichen Wang, Yulun Zhang, Yun Fu, “Generatively Inferential Co-Training for Unsupervised Domain Adaptation,” 2019 International Conference on Computer Vision (ICCV) Workshop (Best paper award), Seoul, Korea [Code] [Paper]

    • Gan Sun, Yang Cong, Lichen Wang, Zhengming Ding, Yun Fu, “Online Multi-task Clustering for Human Motion Segmentation,” 2019 International Conference on Computer Vision (ICCV) Workshop, Seoul, Korea [Paper]

    • Lichen Wang, Zhengming Ding, Yun Fu, "Low-Rank Transfer Human Motion Segmentation," IEEE Transactions on Image Processing (TIP) [Code] [Paper]

    • Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, Yun Fu. "Image Super-Resolution Using Very Deep Residual Channel Attention Networks," 2018 European Conference on Computer Vision (ECCV), Munich, Germany [Code] [Paper]

    • Lichen Wang, Zhengming Ding, Yun Fu. "Adaptive Graph Guided Embedding for Multi-label Annotation," 2018 International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden [Code] [Paper][Slides]

    • Lichen Wang, Zhengming Ding, Yun Fu. "Learning Transferable Subspace for Human Motion Segmentation," 2018 AAAI Conference on Artificial Intelligence (AAAI), New Orleans, USA [Code] [Paper] [Poster]

    • Lichen Wang, Aimin Zhang, Chujia Guo, Pervez Bhan, Tian Yan. “Modified Multi-target Recognition Based on CamCom,” 2015 Chinese Control Conference (CCC), Hangzhong, China [Paper]

    • Lichen Wang, Aimin Zhang, Chujia Guo, Songyun Zhao, Pervez Bhan, “3-D Reconstruction for SMT Solder Joint Based on Joint Shadow,” 2015 Chinese Control and Decision Conference (CCDC), Qingdao, China [Paper]

Patents

    • Bo Zong, Haifeng Chen, Lichen Wang. "Reinforced Text Representation Learning," under reviewed U.S. Invention Patent Application No. 62975280 [PDF] [Paper]

    • Bo Zong, Haifeng Chen, Lichen Wang. "Unsupervised Graph Similarity Learning Based on Stochastic Subgraph Learning," under reviewed U.S. Invention Patent Application No. 62902997 [PDF] [Paper]

    • Lichen Wang, Yan Zhang, Kevin O'Connell. "Three-Dimensional (3D) Depth Imaging Systems and Methods for Dynamic Container Auto-Configuration," granted U.S. Invention Patent No.11010915 [Link]

    • Yan Zhang, Kevin O'Connell, Jay Williams, Lichen Wang. “Systems and methods for automatic camera installation guidance (CIG),” granted U.S. Invention Patent No. 10820307 [Link]

    • Lichen Wang, Min Wu, Qinglin Liu. "Novel Methods and System for Evaporator Frosting Inspection," granted China Invention Patent No. CN201511025257.3 [PDF]

    • Zhenshen Qu, Lichen Wang, Wenhua Jiao, et al. “Novel Methods and System of Foreign Matter Inspection in Infusion Bottle,” granted China Invention Patent No. CN2013102084539 [PDF]

Professional Service

    • International Conference on Machine Learning (ICML), Program Committee, 2021, 2022

    • ACM Special Interest Group on Knowledge Discovery and Data Mining (SIG KDD), 2022

    • International Conference on Learning Representations (ICLR), Reviewer, 2021, 2022, 2023

    • Conference on Neural Information Processing Systems (NeurIPS), 2020, 2021, 2022

    • AAAI Conference on Artificial Intelligence (AAAI), Program Committee, 2019, 2020, 2021, 2022

    • International Joint Conference on Artificial Intelligence (IJCAI), Program Committee, 2020, 2021, 2022

    • IEEE Computer Vision and Pattern Recognition (CVPR), 2016, 2017, 2018, 2019, 2021, 2022

    • European Conference on Computer Vision (ECCV), 2022

    • International Conference on Web Search and Data Mining (WSDM), 2022

    • IEEE Multimedia Information Processing and Retrienal (MIPR), 2018, 2020, 2021

    • ACM Conference of Multimedia (ACM MM), 2018

    • IEEE Conference on Automatic Face and Gesture Recognition (FG), 2018, 2020, 2021

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

    • IEEE Transactions on Image Processing (TIP)

    • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

    • IEEE Computational Intelligence Magazine (IEEE CIM)

    • IEEE Access

    • ACM Transactions on Knowledge Discovery from Data (TKDD)

    • Neurocomputing (NEUCOM)

    • Neural Networks (NEUNET)

    • IS&T SPIE Journal of Electronic Imaging (SPIE JEI)

    • IET Image Processing (IET IP)

    • PLUS ONE

Award

    • AAAI Student Travel Award, 2017, 2020

    • Third prize of Microsoft Imagine Cup Competition (Shaanxi), 2015

    • Meritorious Winner of International Mathematical Contest in Modeling, 2013

    • National Scholarship, China, 2011