Wei WANG

I am a research engineer at TikTok working on ByConity, a cloud native data warehouse engine. Before joining TikTok, I was an assistant professor at NUS School of Computing from 2017 to 2020. I got my B.S. from Renmin University of China in 2011 and PhD from NUS in 2017. My research projects included machine learning system optimizations and multimedia applications. I was the leading developer of Apache SINGA. I am also a vice president of Apache Software Foundation. I have served as an associative editor for VLDB2024, an area chair for ICDCS2020, and PC member for ICDE, VLDB, SIGMOD, DASFFA, ACM Multimedia. I am one of the recipients of SIGMOD System Award 2024.

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Papers

• Mixup for Node and Graph Classification
  Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai and Bryan Hooi. WWW 2021.

• CurGraph: Curriculum Learning for Graph Classification
  Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai and Bryan Hooi. WWW 2021.

• BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
  Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, Shi Gu. ICLR 2021.

• Detecting Implementation Bugs in Graph Convolutional Network based Node Classifiers.
  Yiwei Wang, Wei Wang, Yujun Cai, Bryan Hooi, Beng Chin Ooi. ISSRE2020.

• Learning Effective Representations for Person-Job Fit by Feature Fusion.
  Junshu Jiang, Songyun Ye, Wei Wang, Jingran Xu, Xiaosheng Luo. CIKM 2020.

• Progressive Supervision for Node Classification.
  Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi. ECML-PKDD 2020.

• NodeAug: Semi-Supervised Node Classification with Data Augmentation.
  Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi. SIGKDD 2020

• TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications.
  Kaiping Zheng, Shaofeng Cai, Horng Ruey Chua, Wei Wang, Kee Yuan Ngiam, Beng Chin Ooi. SIGMOD 2020.

• Efficient Bitwidth Search for Practical Mixed Precision Neural Network.
  Yuhang Li, Wei Wang, Haoli Bai, Ruihao Gong, Xin Dong, Fengwei Yu. 2020.

• The Disruptions of 5G on Data-driven Technologies and Applications.
  Dumitrel Loghin, Shaofeng Cai, Gang Chen, Anh Dinh, Feiyi Fan, Qian Lin, Janice Ng, Beng Chin Ooi, Xutao Sun, Quang-Trung Ta, Wei Wang, Xiaokui Xiao, Yang Yang, Meihui Zhang, Zhonghua Zhang. TKDE 2020.

• Understanding Architectures Learnt by Cell-based Neural Architecture Search.
  Yao Shu, Wei Wang, Shaofeng Cai. ICLR 2020. Code

• Additive Powers-of-Two Quantization: A Non-uniform Discretization for Neural Networks.
  Yuhang Li, Xin Dong, Wei Wang. ICLR 2020. Code

• Dynamic Malware Analysis with Feature Engineering and Feature Learning.
  Zhaoqi Zhang, Panpan Qi, Wei Wang, Chang Yao. AAAI 2020.

• One-Shot Image Classification by Learning to Restore Prototypes.
  Wanqi Xue, Wei Wang. AAAI 2020.

• RTN: Reparameterized Ternary Network.
  Yuhang Li, Xin Dong, Sai Zhang, Haoli Bai, Yuanpeng Chen, Wei Wang. AAAI 2020.

• Convolutional Neural Networks for Food Image Recognition: An Experimental Study.
  Yi Sen Ng, Wanqi Xue, Wei Wang, Panpan Qi. International Workshop on Multimedia Assisted Dietary Management, 2019.

• 5G: Agent for Further Digital Disruptive Transformations.
  Beng Chin Ooi, Gang Chen, Dumitrel Loghin, Wei Wang, Meihui Zhang. IEEE Bulletin of the Technical Committee on Data Engineering, 43(3), 9-12, September 2019.

• Deploying Hash Tables on Die-Stacked High Bandwidth Memory.
  Xuntao Cheng, Bingsheng He, Eric Lo, Wei Wang, Shengliang Lu and Xinyu Chen. CIKM 2019.

• A Distributed System for Large-scale n-gram Language Models at Tencent.
  Qiang Long, Wei Wang, Jinfu Deng, Song Liu, Wenhao Huang, Fangying Chen, and Sifan Liu. VLDB 2019.

• ISBNet: Instance-aware Selective Branching Network.
  Shaofeng Cai, Yao Shu, Wei Wang and Beng Chin Ooi. 2019.

• Effective and Efficient Dropout for Deep Convolutional Neural Networks.
  Shaofeng Cai, Jinyang Gao, Meihui Zhang, Wei Wang, Gang Chen, Beng Chin Ooi. 2019.

• Rafiki: Machine Learning as an Analytics Service System.
  Wei Wang, Sheng Wang, Jinyang Gao, Meihui Zhang, Gang Chen, Teck Khim Ng, Beng Chin Ooi, and Jie Shao. VLDB 2019.

• Efficient Memory Management for GPU-based Deep Learning Systems.
  Junzhe Zhang, Sai Ho Yeung, Yao Shu, Bingsheng He, Wei Wang. 2019.

• ScatterNet: A Deep Subjective Similarity Model for Visual Analysis of Scatterplots.
  Yuxin Ma, Anthony K. H. Tung, Wei Wang, Xiang Gao, Zhigeng Pan, Wei Chen. Accepted in Transactions on Visualization and Computer Graphics 2018.

• Capturing Feature-Level Irregularity in Disease Progression Modeling.
  Kaiping Zheng, Wei Wang, Jinyang Gao, Kee Yuan Ngian, Beng Chin Ooi, and Wei Luen James Yip. CIKM 2017.

• Cross-Domain Image Retrieval with Attention Modeling.
  Xin Ji, Wei Wang, Meihui Zhang, and Yang Yang. ACM Multimedia 2017.

• Deep Learning at Scale and At Ease.
  Wei Wang, Gang Chen, Haibo Chen, Tien Tuan Anh Dinh, Jinyang Gao, Beng Chin Ooi, Kian-Lee Tan, and Sheng Wang. ACM Transactions on Multimedia Computing Communications and Applications(TOMM) - Special Section on Best Papers of ACM Multimedia 2015, Volume 12 Issue 4s, November 2016.

• Database Meets Deep Learning: Challenges and Opportunities.
  Wei Wang, Meihui Zhang, Gang Chen, H.V. Jagadish, Beng Chin Ooi, and Kian-Lee Tan. ACM SIGMOD Record, 2016.

• SINGA: Putting Deep Learning in the Hands of Multimedia Users.
  Wei Wang, Gang Chen, Tien Tuan Anh Dinh, Jinyang Gao, Beng Chin Ooi, Kian-Lee Tan, and Sheng Wang. ACM Multimedia 2015. Best paper candidate.

• SINGA: A Distributed Deep Learning Platform.
  Beng Chin Ooi, Kian-Lee Tan, Sheng Wang, Wei Wang, Qingchao Cai, Gang Chen, Jinyang Gao, Zhaojing Luo, Anthony K. H. Tung, Yuan Wang, Zhongle Xie, Meihui Zhang, and Kaiping Zheng. ACM Multimedia (Open Source Software Competition) 2015, project.

• Effective Deep Learning Based Multi-Modal Retrieval.
  Wei Wang, Xiaoyan Yang, Beng Chin Ooi, Dongxiang Zhang, and Yueting Zhuang. VLDB Journal - Special issue of VLDB’14 best papers, 2015, code.

• Effective multi-modal retrieval based on stacked autoencoders.
  Wei Wang, Xiaoyan Yang, Beng Chin Ooi, Dongxiang Zhang, and Yueting Zhuang. VLDB 2014. Best paper candidate, VLDB 2014. Best paper candidate.

• Cross-media hashing with neural networks.
  Yueting Zhuang, Zhou Yu, Wei Wang, Fei Wu, Siliang Tang, and Jian Shao. ACM Multimedia 2014 (short paper).

• Continuously monitoring the correlations of massive discrete streams.
  Yueguo Chen, Wei Wang, Xiaoyong Du, and Xiaofang Zhou. CIKM 2011 (short paper).

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Projects

• ByConity. Cloud data warehouse engine based on ClickHouse.
• SINGA-Auto. AutoML system with optimization on hyper-parameter tuning and model inference.
• Apache SINGA. Apache open-source project for developing a distributed deep learning system. Media report: Strait Times, ASF Blog, CNA938 TechTalk, and others.
• Foodlg. A health tracking and analysis App based on deep learning.

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Professional Activities

• Vice President of Apache Software Foundation; Chair of Apache SINGA project.
• Reviewer of TKDE, Neurocomputing, IEEE Transactions on Multimedia and ACM Transactions on Data Science.
• Associative Editor of 2024
• Area Chair of ICDCS 2020
• Program Committee member of SIGMOD 2021
• Program Committee member of EDBT 2021
• Program Committee member of DASFFA 2021
• Program Committee member of ACM Multimedia 2020
• Program Committee member of DASFFA 2020
• Program Committee member of DASFFA 2019
• Program Committee member of ACM Multimedia 2019
• Program Committee member of VLDB 2018
• Program Committee member of ICDE 2018
• Program Committee member of DASFFA 2017
• Program Committee member of ACM Multimedia 2015