Qi Liu

Assistant Professor at the University of Hong Kong

The University of Hong Kong

Biography

I am an assistant professor at the Department of Computer Science, the University of Hong Kong, and a cofounder of Reka. I earned my Ph.D. in computer science from the University of Oxford. In the past, I obtained a Master of Science degree from the National University of Singapore, and a Bachelor of Engineering degree from Shandong University. My research interests include natural language processing and machine learning. I also spent some time at Google DeepMind, Facebook AI Research, and Microsoft Research before and during my PhD study.

I have multiple fully-funded PhD, MPhil, postdoc, RA, and intern positions available at the University of Hong Kong. Email me for more information.

Reka is hiring for platform and machine learning. Email us for more information. We are committed to the development of multimodal foundation models.

Interests

Natural Language Processing
Machine Learning
Artificial Intelligence

Education

Ph.D. in Artificial Intelligence
University of Oxford, Advisors: Phil Blunsom, Matt Kusner
M.Sc in Computer Science
National University of Singapore, Advisor: Anthony K.H. Tung
BEng in Computer Science
Shandong University

Experiences

Research Scientist Intern

Google DeepMind

Jul 2020 – Jun 2021 London

Advisors: Phil Blunsom, Dani Yogatama, Lei Yu, Laura Rimell

Researcher

Facebook AI Research

Aug 2018 – Aug 2019 New York City

Advisors: Douwe Kiela, Maximilian Nickel

Research Intern

Microsoft Research

Mar 2018 – Jun 2018 Cambridge

Advisors: Alexander Gaunt, Marc Brockschmidt, Miltos Allamanis

Research Assistant

SUTD

Feb 2017 – Feb 2018 Singapore

Advisor: Yue Zhang

Research Intern

Microsoft Research

Sep 2016 – Dec 2016 Beijing

Advisors: Ying Yan, Thomas Moscibroda

Selected Awards

AMiner AI Most Influential Scholar

AMiner Jan 2022

Google DeepMind Scholarship

Google DeepMind Sep 2019

Lee Kuan Yew Global Business Plan Competition Winner (3 out of 550)

SMU Aug 2017

NUS Research Scholarship

NUS Sep 2014

Publications

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Lei Li, Yuwei Yin, Shicheng Li, Liang Chen, Peiyi Wang, Shuhuai Ren, Mukai Li, Yazheng Yang, Jingjing Xu, Xu Sun, Lingpeng Kong, Qi Liu (2023). M3IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning. In arXiv.

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Haiteng Zhao, Shengchao Liu, Chang Ma, Hannan Xu, Jie Fu, Zhi-Hong Deng, Lingpeng Kong, Qi Liu (2023). GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning. In bioRxiv.

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Lei Li, Jingjing Xu, Qingxiu Dong, Ce Zheng, Qi Liu, Lingpeng Kong, Xu Sun (2023). Can Language Models Understand Physical Concepts?. In arXiv.

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Peiyi Wang, Lei Li, Liang Chen, Dawei Zhu, Binghuai Lin, Yunbo Cao, Qi Liu, Tianyu Liu, Zhifang Sui (2023). Large Language Models are not Fair Evaluators. In arXiv.

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Yazheng Yang, Zhou Zhao, Qi Liu (2023). MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer. In KDD.

Yuwei Yin, Jean Kaddour, Xiang Zhang, Yixin Nie, Zhenguang Liu, Lingpeng Kong, Qi Liu (2023). TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models. In arXiv.

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Chang Ma, Haiteng Zhao, Lin Zheng, Jiayi Xin, Qintong Li, Lijun Wu, Zhihong Deng, Yang Lu, Qi Liu, Lingpeng Kong (2023). Retrieved Sequence Augmentation for Protein Representation Learning. In bioRxiv.

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Qi Liu, Zihuiwen Ye, Tao Yu, Phil Blunsom, Linfeng Song (2022). Augmenting Multi-Turn Text-to-SQL Datasets with Self-Play. In EMNLP Findings.

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Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva (2022). Causal Machine Learning: A Survey and Open Problems. In arXiv.

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Hanchen Wang, Jean Kaddour, Shengchao Liu, Jian Tang, Matt Kusner, Joan Lasenby, Qi Liu (2022). Evaluating Self-Supervised Learning for Molecular Graph Embeddings. In arXiv.

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Dingmin Wang, Shengchao Liu, Hanchen Wang, Linfeng Song, Jian Tang, Song Le, Bernardo Cuenca Grau, Qi Liu (2022). Augmenting Message Passing by Retrieving Similar Graphs. In arXiv.

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Qi Liu, Dani Yogatama, Phil Blunsom (2022). Relational Memory Augmented Language Models. In TACL.

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Zhenguang Liu, Shuang Wu, Shuyuan Jin, Qi Liu, Shouling Ji, Shijian Lu, Li Cheng (2022). Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction. In PAMI.

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Jean Kaddour, Yuchen Zhu, Qi Liu, Matthew J. Kusner, Ricardo Silva (2021). Causal Effect Inference for Structured Treatments. In NeurIPS.

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Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matthew J. Kusner (2021). Unsupervised Point Cloud Pre-Training via View-Point Occlusion Completion. In ICCV.

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Qi Liu, Lei Yu, Laura Rimell, Phil Blunsom (2021). Pretraining the Noisy Channel Model for Task-Oriented Dialogue. In TACL.

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Qi Liu, Matt J. Kusner, Phil Blunsom (2021). Counterfactual Data Augmentation for Neural Machine Translation. In NAACL.

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Dingmin Wang, Chenghua Lin, Qi Liu, Kam-Fai Wong (2021). Fast and Scalable Dialogue State Tracking with Explicit Modular Decomposition. In NAACL Short Paper.

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Qi Liu, Matt J. Kusner, Phil Blunsom (2020). A Survey on Contextual Embeddings. In arXiv.

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Yuan Zhuang, Zhenguang Liu, Peng Qian, Qi Liu, Xiang Wang, Qinming He (2020). Smart Contract Vulnerability Detection using Graph Neural Network. In IJCAI.

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Shaolei Wang, Wanxiang Che, Qi Liu, Pengda Qin, Ting Liu, William Yang Wang (2020). Multi-Task Self-Supervised Learning for Disfluency Detection. In AAAI.

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Qi Liu, Maximilian Nickel, Douwe Kiela (2019). Hyperbolic Graph Neural Networks. In NeurIPS.

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Shuai Zhang, Yi Tay, Lina Yao, Qi Liu (2019). Quaternion Knowledge Graph Embedding. In NeurIPS.

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Jiatao Gu, Qi Liu, Kyunghyun Cho (2019). Insertion-based Decoding with Automatically Inferred Generation Order. In TACL.

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Zhenguang Liu, Shuang Wu, Shuyuan Jin, Qi Liu, Shijian Lu, Roger Zimmermann, Li Cheng (2019). Towards Natural and Accurate Future Motion Prediction of Humans and Animals. In CVPR.

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Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt (2018). Constrained Graph Variational Autoencoders for Molecule Design. In NeurIPS.

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Yue Zhang, Qi Liu, Linfeng Song (2018). Sentence-State LSTM for Text Representation. In ACL.

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Qi Liu, Yue Zhang (2018). Mining Evidences for Concept Stock Recommendation. In NAACL.

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Qi Liu, Yue Zhang, Jiangming Liu (2018). Learning Domain-specific Representations for Multi-Domain Sentiment Classification. In NAACL.

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Qi Liu, Yue Zhang, Zhenguang Liu, Ye Yuan, Li Cheng, Roger Zimmermann (2018). Multi-modal Multi-task Learning for Automatic Dietary Assessment. In AAAI.

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Yixuan Tang, Weilong Huang, Qi Liu, Anthony K.H. Tung, Xiaoli Wang, Jisong Yang, Beibei Zhang (2017). QALink: Enrich Text Documents with Relevant Q&A Site Contents. In CIKM.

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Yang Li, Kai Zheng, Ying Yan, Qi Liu, Xiaofang Zhou (2017). EtherQL: A Query Layer for Blockchain. In DASFAA.

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Zhenguang Liu, Yingjie Xia, Qi Liu, Qinming He, Yanxiang Chen, Roger Zimmermann (2017). Towards Personalized Activity Level Prediction in Community Question Answering Websites. In TOMM.

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Butian Huang, Zhenguang Liu, Jianhai Chen, Anan Liu, Qi Liu, Qinming He (2017). Behavior Pattern Clustering in Blockchain Networks. In MTAP.

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Zhenguang Liu, Luming Zhang, Qi Liu, Yifang Yin, Li Cheng, Roger Zimmermann (2016). Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-free and More Effective. In TMM.

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Shubham Goyal, Qi Liu, Khairina Tajul-Arifin, Waqas Awan, Bimlesh Wadhwa, Zhenguang Liu (2016). I Ate This: A Photo-based Food Journaling System with Expert Feedback. In SIGCHI Workshop.

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Qiang Hu, Qi Liu, Xiaoli Wang, Anthony K.H. Tung, Shubham Goyal, Jisong Yang (2015). DocRicher: An Automatic Annotation System for Text Documents Using Social Media. In SIGMOD Demo Track.

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