Yangqiu Song
I am now also a visiting academic scholar at Amazon Search Science and AI Team@A9 (Jan. 2022 - present).
I am now an associate professor at Department of CSE at HKUST, and an associate director of HKUST-WeBank Joint Lab. I was an assistant professor at Lane Department of CSEE at WVU (2015-2016); a post-doc researcher at UIUC (2013-2015), a post-doc researcher at HKUST and visiting researcher at Huawei Noah's Ark Lab, Hong Kong (2012-2013); an associate researcher at Microsoft Research Asia (2010-2012); a staff researcher at IBM Research-China (2009-2010). I received my B.E. and PhD degree from Tsinghua University, China, in July 2003 and January 2009. I also worked as interns at Google in 2007-2008 and at IBM Research-China in 2006-2007.
Office: Room 3518
HKUST, Clearwater Bay, Kowloon, Hong Kong
Email: yqsong # cse dot ust dot hk
Research Interests: Machine Learning, Data Mining, Natural Language Processing, Knowledge Graph and Information Networks.
Recent Research Topics (Full Publications (DBLP) and KnowComp Group Code):
My research goal is to use machines to understand human languages and eventually facilitate natural human language interaction and communication. Our current approach is to extract useful knowledge from existing resources to construct knowledge graphs and use knowledge graphs to do reasoning and inference for understanding. When meeting downstream applications, we also need to care about privacy, security, and fairness issues to build trustworthy real-world systems.
- Knowledge graph construction and information extraction.
- ProBase: a concept knowledge graph extracted from billions of Web pages (latest version).
- ASER: an eventuality knowledge graph of activities, states, events, and their relations.
- TransOMCS: population of a commonsense knowledge base in the format of OMCS transferred from linguistic patterns in ASER.
- DISCOS: population of ATOMIC if-then inferential commonsense knowledge base with the discourse relations in ASER (Extension: CSKB Population Benchmark).
- Abstract ATOMIC: a conceptualization framework of commonsense knowledge aquisition and its resulting abstract knowledge in the form of ATOMIC.
- FolkScope: Eventuality-based Intention Knowledge Graph for E-commerce Commonsense
- Natural language understanding and grounding to knowledge graphs.
- Selectional preference and conceptualization with large-scale knowledge bases.
- Entity linking, typing, semantic parsing, and discourse analysis.
- Machine learning, inference, and reasoning with world knowledge (A survey about text categorization).
- Learning with flat knowledge feature representation and domain adaptation.
- Learning problems with structural representation and new kinds of supervision signals.
- Leveraging (commonsense) knowledge to improve privacy, security, explainability, and fairness issues in machine learning models for NLP.
Invited Talks:
- 2023 Summer: IJCAI-FL. Privacy Attacks on Large Language Models. [pdf], [ppt]
- 2023 Summer: KDD-China. Activity (or Process), State, and Event-based Knowledge Graphs . [pdf], [ppt]
- 2022 July: Amazon Search Science Team. Acquiring and Modeling Abstract Commonsense Knowledge via Conceptualization. [pdf], [ppt]
- 2021 Novermber: CCKS Tutorial. Commonsense Knowledge Acquisition and Reasoning. [pdf], [ppt]
- 2021 September: Huawei Workshop on Commonsense. Commonsense Knowledge Base Population. [pdf], [ppt]
- 2021 Summer: WeBank, BUPT, and 4Paradigm. Differentially Private Federated Knowledge Graphs Embedding. [pdf], [ppt]
- 2021 Summer: Renmin University and THU. An Overview of Commonsense Knowledge Graph Construction and Reasoning at HKUST. [pdf], [ppt]
- 2020 KDD Tutorial. Recent Advances on Graph Analytics and Its Applications in Healthcare. [Tutorial Page] [Part 3 ppt]
- 2020 July: Knowledge Works at Fudan and THU. ASER: Building a Commonsense Knowledge Graph by Higher-order Selectional Preference. [pdf], [ppt]
- 2019 July: HIT Event Reasoning Workhop, BUPT, PKU, Beihang. ASER: A Large scale Eventuality Knowledge Graph. [pdf], [ppt], [WWW20 Version]
- 2018 November: ICDM Workshop on Large Scale Graph Representation Learning and Applications (GRLA). Automatic Information Fusion with Heterogeneous Information Networks. [ppt] [pdf]
- 2017 Summer: SCUT, PKU. Recent Development of Heterogeneous Information Networks: From Meta-paths to Meta-graphs. [ppt] [pdf]
- 2016 IJCAI Workshop on Heterogeneous Information Network Analysis (HINA). Incorporating Structured World Knowledge into Unstructured Text via Heterogeneous Information Networks. [ppt] [pdf] (extended abstract [pdf])
- 2015 ICDM Workshop on Practical Transfer Learning. Text Classification without Supervision: Incorporating World Knowledge and Domain Adaptation. [ppt] [pdf]
Teaching:
- COMP4222@HKUST, Machine Learning with Structured Data, Fall 2022
- COMP5222/MATH5471@HKUST, Statistical Learning Models for Text and Graph Data: Fall 2019, Fall 2021
- COMP4901K/MATH4824B@HKUST, Machine Learning for Natural Language Processing: Fall 2018, Fall 2020
- MSBD6000h/MSBD5018@HKUST, Natural Language Processing: Spring 2021, Spring 2022, Spring 2023
- COMP4332/RMBI4310@HKUST, Big Data Mining: Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023
- COMP6211B/MATH6450D@HKUST, Statistical Learning for Text Data Analytics: Spring 2018
- COMP3211@HKUST, Fundamentals of Artificial Intelligence: Spring 2017, Fall 2017
- COMP6211A@HKUST, Topics in Text Mining and Knowledge Graph Construction, Inference, and Applications: Fall 2016
- CS472@WVU, Artificial Intelligence: Spring 2016
- CS493n@WVU, Big Data Engineering: Fall 2015
Group:
PhDs:
- Zhaowei Wang (Since Fall 2023)
- Jiayang Cheng (Since Fall 2023)
- Jacky Chun Kit Chan (Since Fall 2023)
- Weiqi Wang (Since Fall 2022)
- Zheye Deng (Since Fall 2022)
- Qi Hu (Since Fall 2020)
- Haoran Li (Since Fall 2020)
- Zihao Wang (Since Fall 2020)
- Jiaxin Bai (Since Fall 2020)
- Zizheng Lin (Since Fall 2019)
- Tianqing Fang (Since Fall 2019)
MPhils:
- Wei Fan (Since Fall 2023)
- Yau Wai YIM (Since Fall 2023)
- Peng Xie (Since Fall 2023, Co-supervised with Prof. Kani Chen)
- Louis Chun Yi Bo (Since Fall 2022)
- Zihan Li (Since Fall 2022, Co-supervised with Prof. Bo Li)
- Zirui Wang (Since Fall 2022, Co-supervised with Qian Xu)
- Sehyun Choi (Since Fall 2022)
- Van Quyet DO (Since Fall 2022)
GZ Campus:
- Nuo Chen (Since Spring 2023, Co-supervised with Prof. Jia Li)
- Zeteng Lin (Since Spring 2023, Co-supervised with Prof. Jing Tang)
- Duanyi Yao (Since Fall 2022, Co-supervised with Prof. Songze Li)
- He Cao (Since Fall 2020, Co-supervised with Prof. Yuan Yao)
- Yiran Cheng (Since Fall 2020, Co-supervised with Prof. Qiong Luo)
- Amanda So (Since Fall 2020, Co-supervised with Prof. Yangguang Huang)
- Ying Su (Since Fall 2020, Co-supervised with Prof. Tong Zhang)
- Yue Guo (Since Fall 2020, Co-supervised with Prof. Yi Yang)
RAs:
- Qineng Wang (UG Intern, Summer 2023, Zhejiang University)
- Yujun Zhang (UROP, Summer 2023, HKUST)
- Hong Ting TSANG (UROP, Summer 2023, HKUST)
- Tung Duong VUONG (UROP, Summer 2023, HKUST)
Past students, interns, visitors, collaborators with first employment:
- HKUST PhD:
- Xin Liu (Fall 2018-Summer 2023, First Employment: Amazon A9 in Palo Alto). Thesis: Theory and Practice: Graph Representation Learning For Subgraph Isomorphisms and Substructure-Augmented Applications
- Huiru Xiao (Fall 2016-Summer 2022, First Employment: Lecturer at HKUST). Thesis: Learning with Hierarchical Data
- Wenyi Xiao (Fall 2016-Fall 2021, First Employment: Huawei in Hong Kong). Thesis: Path Learning in Complex Networks
- Hongming Zhang (Fall 2018-Summer 2021, First Employment: Tencent AI Lab in Seattle). Thesis: Towards Commonsense Reasoning with Higher-order Selectional Preference over Eventualities
- Hongliang Dai (Fall 2017-Summer 2021, First Employment: Tencent Jarvislab in Shenzhen). Thesis: Weak Supervision for Information Extraction
- Ziqian Zeng (Fall 2016-Summer 2021, First Employment: SCUT in Guangzhou). Thesis: On the Use of Auxiliary Information for Label-less Text Mining Tasks
- Yinghua Zhang (Fall 2015-Spring 2021, Co-supervised with Prof. Qiang Yang, First Employment: Meituan in Shanghai). Thesis: Deep Transfer Learning: Generalization on Clean and Adversarial Data
- Nedjma Ousidhoum (Fall 2014-Summer 2021, Co-supervised with Prof. DY Yeung, First Employment: Postdoc at Cambridge). Thesis: On the Importance of Normalization of the Experimental Design of Multilingual Toxic Content Detection
- HKUST MPhil:
- Zhaowei Wang (Fall 2021-Summer 2023, First Employment: HKUST PhD). Thesis: SubeventWriter: Iterative Sub-event Sequence Generation with Coherence Controller
- Jiayang Cheng (Fall 2021-Summer 2023, First Employment: HKUST PhD). Thesis: Narrative Reasoning by Grounding to Event-centric Knowledge Graphs
- Jacky Chun Kit Chan (Fall 2021-Summer 2023, First Employment: HKUST PhD). Thesis: Promp Learning on Abductive Commonsense Reasoning
- Gio Tsz Ho Chan (Fall 2021-Summer 2023, First Employment: Huawei Hong Kong). Thesis: Exploring Contextualized Conceptualization: An Evaluation of Prompt-Driven Responses in Diverse Language Models
- Cynwell Yik Lun Lau (Fall 2021-Summer 2023, First Employment: HKUST). Thesis:
- Ngo Yin Wong (Fall 2019-Summer 2023, First Employment: Amazon AWS in Hong Kong). Thesis: Reasoning over Merged Semantic Graphs across Multiple Frameworks for Fact Verification
- Haowen Ke (Fall 2019-Summer 2022, First Employment: PhD at HKUST). Thesis: Personalised Knowledge-aware News Recommendation
- Mutian He (Fall 2019-Spring 2022, First Employment: PhD at EPFL). Thesis: Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization
- Haojie Pan (Fall 2018-Spring 2020, First Employment: Alibaba): Thesis: Pragmatical Discourse Analysis in Dialogues
- Yan Liang (Fall 2016-Summer 2019, First Employment: Financial Industry). Thesis: Relation Discovery with Out-of-Relation Knowledge Base as Supervision
- Ruixiang Zhang (Fall 2016-Summer 2018, First Employment: PhD at UMontreal). Thesis: An Adversarial Approach to Few-Shot Learning
- Hongming Zhang (2016.08-2018.08, First Employment: PhD at HKUST). Thesis: FinFlow
- HKUST PG Interns: Yichun Yin (RA, 2016-2017, PhD candidate, PKU->Huawei), He Jiang (RA, 2016-2017, B.E., PKU->PhD, USC), Xiaofeng Yu (MSC Intern, 2018.09-2019.05, HKUST), Linyi Wang (MSC Intern, 2018.09-2019.05, HKUST)
- HKUST UG Interns: Sheng Zhou (UROP and UG Intern, 2017.02-2018.02, HKUST), Phoomraphee LUENAM (UG Intern, Summer 2017-2018.02, HKUST), Wenxuan Zhou (UROP and UG Intern, 2017.07-2018.06, HKUST->PhD, USC), Yingqi Zhou (UG Intern, 2017.09-2018.06, HKUST->Master, CMU), Hantian Ding (UG Intern, 2017.09-2018.06, HKUST->Master, UIUC), Zhiyuan Li (UROP, 2018.09-2018.12, HKUST), Xinyu Sun (UROP and UG Intern, 2018.02-2018.12, HKUST), Sixuan Chen (UROP and UG Intern, 2018.02-2019.05, HKUST), Donghong Du (UROP and UG Intern, 2018.02-2019.05, HKUST), Emily Cheng-hsin WUU (UROP and UG Intern, 2019.02-2019.05, HKUST), Yili Wang (UROP and UG Intern, 2018.02-2019.05, HKUST), Zizheng Lin (UG Intern, 2019.01-2018.08, HKUST), Jiaxin Bai (UROP and UG Intern, 2018.02-2019.05, HKUST), Zhi Yun YAP (UROP, 2019-Summer 2020, HKUST), Yik Lun LAU (UROP, 2019-Summer 2020, HKUST), Tianqi XIANG (UROP, 2019-Summer 2020, HKUST), Kaixing Wu (UROP and UG Intern, Fall 2019, Summer 2020, HKUST), Jiefu Ou (UROP and UG Intern, 2019.05-2021.03, HKUST->CMU), Xinran Zhao (UG Intern, 2019.05-2021.03, HKUST->Stanford), Jiachen Zhao (UROP, Spring 2021, HKUST), Chi Ho WONG (UROP, Fall 2021, HKUST), Sehyun Choi (UROP and UG Intern, Spring 2021-Summer 2022, HKUST->MPhil, HKUST), Weiqi Wang (UG Intern, Fall 2020-Summer 2022, HKUST->PhD, HKUST), Wai Chung TSE (UROP, Summer 2022, HKUST),Baixuan Xu (UROP, Summer 2022, HKUST), Tianyi Xiao (UG Intern, Fall 2020-Fall 2022, HKUST), Wenxuan Ding (UROP, Spring 2023, HKUST), Yicheng Wang (UROP, Summer 2022-Spring 2023, HKUST)
- HKUST UG Visiting Students: Haojie Pan (SENG UG Visiting Program, Summer 2017, ZJU->PhD HKUST), Xiaogang Xu (SENG UG Visiting Program, Summer 2017, ZJU), Jennifer Zou (IROP, Summer 2017, MIT), Zheye Deng (UG Visiting Student, 2018.02-2018.06, PKU), Xin Liu (SENG UG Visiting Program, 2018.01-2018.07, SYSU->PhD, HKUST), Ziyan Wang (UG Visiting Student, 2018.06-2018.09, UMich), Jie Huang (UG Student at FYTRI, 2018.12-2019.07), Yintong Huo (UG Visiting, 2019.10-2020.02, UESTC), Zi-Yuan Hu (UG Intern, Spring 2021, SYSU), Shibo Hao (UG Intern, Spring 2021, PKU), Claire Zhao (Intern, Spring 2022-Summer 2022, CentraleSupelec)
- WVU: Wentian Zhou (PhD candidate, 2015.10-2016.05, WVU), Yiming Zhang (Master, 2016.01-2016.05, WVU)
- UIUC: Chenguang Wang (2014.08-2015.02, PKU->IBM Research-Almaden), Shaoshi Ling (2014.12-2015.03, UIUC BEng->UIUC Master)
- MSRA: Zekai J. Gao (2010.12-2011.04, ZJU->Rice), Erik Cambria (2011.03-2011.05, NTU), Xueqing Liu (2011.07-2012.03, THU->UIUC), Shusen Wang (2011.08-2012.03, ZJU->Berkeley), Wen Hua (2012.04-2012.08, RUC->UQ), Xiting Wang (2012.06-2012.11, THU->MSRA), Fangzhao Wu (2012.06-2012.11, THU->MSRA)
Student Achievements:
- Haoran Li: HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2022/23
- Tianqing Fang: HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2022/23
- Zhaowei Wang: Hong Kong PhD Fellowship (HKPF), 2023
- Jiayang Cheng: Hong Kong PhD Fellowship (HKPF), 2023
- Jacky Chun Kit Chan: Hong Kong PhD Fellowship (HKPF), 2023
- Sehyun Choi: Asian Future Leaders Scholarship Program (AFLSP), 2022
- Weiqi Wang: Hong Kong PhD Fellowship (HKPF), 2022
- Zheye Deng: Hong Kong PhD Fellowship (HKPF), 2022
- Xin Liu: HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2021/22
- Haoran Li: HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2021/22
- Tianqing Fang: HKUST RedBird Academic Excellence Award for Continuing PhD Students in 2021/22
- Xin Liu: HKUST CSE Professor Samuel Chanson Best Teaching Assistant Award 2020
- Xin Liu: HKUST School of Engineering Academic Award for Continuing PhD Students 2019-2020
- Hongming Zhang: HKUST School of Engineering Academic Award for Continuing PhD Students 2019-2020
- Zihao Wang: Hong Kong PhD Fellowship (HKPF), 2020
- Jiaxin Bai: Hong Kong PhD Fellowship (HKPF), 2020
- Hongming Zhang: Tencent Rhino-Bird Scholarship, 2019
- Hongming Zhang: Microsoft Research Asia Fellowship, 2019
- Hongliang Dai: HKUST School of Engineering Academic Award for Continuing PhD Students 2018-2019
- Ziqian Zeng: HKUST School of Engineering Academic Award for Continuing PhD Students 2018-2019
- Zizheng Lin: Hong Kong PhD Fellowship (HKPF), 2019
- Tianqing Fang: Hong Kong PhD Fellowship (HKPF), 2019
- Xin Liu: Huawei PhD Fellowship, 2018
- Hongming Zhang: Hong Kong PhD Fellowship (HKPF), 2018
- Ziqian Zeng: Hong Kong PhD Fellowship (HKPF), 2016
- Yinghua Zhang: Hong Kong PhD Fellowship (HKPF), 2015
Best Paper Awards:
- AKBC 2021: Outstanding Paper Award
- IEEE VIS 2021: Best Paper Award-Honorable Mention
- WSDM 2018 workshop on KBCOM: Best Paper Award-Honorable Mention
- Yelp 2018: Grand Prize for Best Paper Award in Yelp Dataset Challenge - Round 10
- KDD 2017: Best Data Science Track Paper Award
- IUI 2015: Best Paper Award-Honorable Mention
- KDD 2014: Selected in TKDD Special Issue of Best Papers in ACM SIGKDD 2014 (One out of Nine)
- PAKDD 2007: Best Paper Award-Honorable Mention
Service:
- Journal Editorial Board: Journal of Artificial Intelligence Research (2016.07-Present)
- Journal Editorial Board, Standing Reviewer: Transactions of the Association for Computational Linguistics
- Journal Guest Editor: ACM Transactions on Intelligent Systems and Technology (TIST) Special Issue on “Federated Learning: Algorithms, Systems, and Applications”
- Journal Guest Editor: IEEE Transaction on Big Data Special Issue on “Knowledge Graphs: Techniques and Applications.”
- Journal Guest Editor :ACM Transactions on Interactive Intelligent Systems (TIIS) Special Issue on “Modeling User Trait and Behavior with Machine Learning.”
- Conference Chair: ICKG'21: Knowledge Graph for NLP Track Area Chair; EMNLP'21: Information Extraction Track Chair; ACL-IJCNLP'21: Information Extraction Track Area Chair; NAACL'21: Semantics: Sentence-level Semantics and Textual Inference Track Area Chair; IJCAI'21: Area Chair; EMNLP'20: Information Extraction Track Area Chair; ACL'20: Information Retrieval and Text Mining Track Area Chair; NLPCC'19: Knowledge Graphs Track Area Chair; IJCAI'19 in Macau: Local Chair; NLPCC'17: Machine Learning Track Area Chair
- Senior Program Committee: KDD'21 Data Science; CIKM'19,21; AAAI'18,20,21; IJCAI'15
- Program Committee: KDD'13-21; NIPS'15-18,20; COLING'14,18,20; IJCAI'13,16,19,20; EMNLP'18,19; *SEM'17,19; ACL'13,17-19; ICDM'14-16,18; CIKM'14,17-18; ECML/PKDD'11,14-18; ICML'15,18; AAAI'15-17; SDM'15-17;DASFAA'17; ICMLA'07-15; IEEE DSAA'15; ICTAI'11-12,14-15; ACML'13-15; BigComp'15; CIKM'14; CIDM'13-14; COLING'14; SMIR'14; WSDM'14; IEEE-CSE'12-13; RecSys'13; LSRS'13; IUI'13; ParLearning'12-13; LSVA'11; OEDM'09-11; SBNMA'11
Current Research Sponsors:
- HK-UGC, HK-RGC, HK-ITC, China NSFC, Tencent AI Lab, Hong Kong Mediation and Arbitration Centre (HKMAAC) and California University, School of Business Law & Technology.