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Dr. Liu Yang
PhD in Computer Science
Senior Software Engineer/ Researcher of IR/NLP/ML/DM
1600 Amphitheatre Pkwy, Mountain View, CA
yangliuy@google.com
I am a senior software engineer/ researcher of IR/NLP/ML/DM at Google. My work at Google includes research&development on information retrieval, ranking, machine learning and building deep learning models for search ads (e.g. shopping related ads at google.com, Google image search, shopping.google.com, etc.) quality optimization. Before joining Google, I was a PhD student at the Center for Intelligent Information Retrieval (CIIR) , College of Information and Computer Sciences, University of Massachusetts Amherst under the supervision of Prof. W. Bruce Croft. I got my PhD and MS degree in Computer Science from University of Massachusetts Amherst and another Master degree from Peking University. I worked as a Research Assistant at Text Mining Group of Singapore Management University with Prof. Jing Jiang and a visiting PhD student in CAS Key Lab of Network Data Science and Technology with Prof. Jiafeng Guo. For industrial experiences, I worked as a research intern in Microsoft Research Redmond, Microsoft Bing and a software engineer intern in Search R&D Department of Baidu Inc. My research areas include information retrieval, natural language processing, text mining and machine learning. I have published more than 35 papers with more than 3000 citations in top conferences such as WWW, SIGIR, ACL, ICML, ICLR, EMNLP, CIKM, WSDM, ICDM and NAACL. Moreover, I have served as the SPC/PC member for top conferences including KDD, ACL, SIGIR, WWW, AAAI, EMNLP, WSDM and CIKM. I'm interested in research&development on deep learning, text matching, question answering, neural conversational models, search, ranking and relevance, learning to rank, statistical language models, probabilistic graphical models, user modeling/profiling and ads quality optimization.
Academic Experience
UMass Amherst, Research Assistant in Center for Intelligent Information Retrieval(CIIR), Advisor: Prof. W. Bruce Croft, Amherst, MA, USA. Aug. 2014 - May 2019
Institute of Computing Technology, Chinese Academy of Science, Visiting PhD student in CAS Key Lab of Network Data Science and Technology, Advisor: Prof. Jiafeng Guo, Beijing, China. Sept. 2017 - Nov. 2017
Singapore Management University, Research Assistant in Text Mining Group, Advisor: Prof. Jing Jiang, Singapore. Sept. 2012 - Jun. 2014
Industrial Experience
Google, Senior Software Engineer, Mountain View, CA , USA. July 2019 - Present
Google Research, Document Understanding/Query Understanding
Shopping Ads Quality at Google, Deep Learning/Machine Learning/IR/Ranking/Search/Ads Quality/ CTR Models
Microsoft Research Redmond, Research Intern in Microsoft AI & Research, Redmond, Seattle Area, WA, USA. May 2018 - Aug. 2018
Mentors: Dr. Jianfeng Gao, Dr. Yelong Shen, Dr. Xiaodong Liu, Dr. Jingjing Liu from MSR
Microsoft Research Redmond, Research Intern in CLUES (Context, Learning, and User Experience for Search) group. Redmond, Seattle Area, WA, USA. Jun. 2016 - Sept. 2016
Mentors: Dr. Susan Dumais, Dr. Paul Bennett, Dr. Ahmed Hassan Awadallah from MSR
Microsoft Research Redmond/Bing, Research Intern on Bing Contextual Relevance. Bellevue, Seattle Area, WA, USA. May 2015 - Aug. 2015
Mentors: Dr. Kieran McDonald, Dr. Qi Guo, Dr. Sha Meng from Bing and Dr. Yang Song, Dr. Milad Shokouhi from MSR
Baidu Inc, Software Engineer Intern in Search R&D Department, Beijing, China. Feb. 2011 - Aug. 2011
Research Interests
Deep Learning in QA/Conversations and IR/Ranking/Search/Ads/Recommender System
Information Retrieval/ Web Search/ Question Answering/ Ads Quality
Ranking and Relevance/ Language Modeling/ Learning to Rank, Answer Retrieval/ Question Answering/ Machine Comprehension/ Learning to Match, Dialogue Systems/ Human-Computer Conversation/ Sequence-to-Sequence Models, Query Expansion/Query Reformulation/Query Processing and Understanding, Search Evaluation/ User Satisfaction/ Search Personalization, Ads Quality/ pCTR models
Text Mining/ Data Mining/ Natural Language Processing
Topic Modeling, Sentiment Analysis/ Opinion Mining, Online User Modeling/ Profiling, Recommender System, Community Question Answering, Information Extraction and Summarization
Statistical Machine Learning/ Deep Learning/ Reinforcement Learning/ Artificial Intelligence
Probabilistic Graphical Models, Matrix Factorization/ Collaborative Filtering, Neural Networks/ Deep Learning/ Representation Learning, Reinforcement Learning/ Deep Reinforcement Learning, Generative Adversarial Network
Distant Supervision/ Weakly Supervision/ Semi-supervised Learning/ Unsupervised Learning
Transfer Learning/ Multi-task Learning/ Pre-training
Recent News
[Aug. 2021] One long paper is accepted by CIKM'21.
[Jan. 2021] One long paper is accepted by ICLR'20.
[Sept. 2020] One full paper is accepted by EMNLP'20 Findings.
[Jul. 2020] One full paper is accepted by CIKM'20.
[Jun. 2020] One full paper is accepted by ICML'20.
[Apr. 2020] One paper preprint on "Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching" is on arXiv.
[Apr. 2020] Two full papers are accepted by SIGIR'20.
[Jan. 2020] One short paper is accepted by WWW'20.
[Aug. 2019] Two full papers are accepted by CIKM'19.
[Jun. 2019] One short paper is accepted by ICTIR'19.
[May 2019] I passed the PhD dissertation defense and got my PhD.
[Apr. 2019] One paper preprint on a hybrid retrieval-generation neural conversation model is on arXiv.
[Apr. 2019] One short paper is accepted by SIGIR'19.
[Mar. 2019] A survey paper on neural ranking models is on arXiv, which is the pre-print of the IP&M submission.
[Nov. 2018] Two papers are accepted by CHIIR'19.
[Oct. 2018] One full paper is accepted by WSDM'19.
[Aug. 2018] One full paper is accepted by CIKM'18.
[Apr. 2018] One short paper is accepted by ACL'18.
[Apr. 2018] Passed the PhD dissertation proposal defense.
[Apr. 2018] One full paper and two short papers are accepted by SIGIR'18. See you in Ann Arbor Michigan during SIGIR'18.
[Sept. 2017] Visited Prof. Jiafeng Guo in ICT/CAS, Dr. Hang Li in ByteDance Inc, Dr. Minghui Qiu in Alibaba Inc. and Dr. Zhaochun Ren in data science lab at JD.com.
[Apr. 2017] One full paper is accepted by SIGIR'17 and one paper is accepted by SIGIR'17 Neu-IR workshop. See you in Tokyo during SIGIR'17.
[Sept. 2016] Finished a summer internship in Microsoft Research Redmond.
[Jul. 2016] One full paper is accepted by CIKM'16 and I will attend CIKM'16 in Indianapolis, IN, USA.
[Jun. 2016] One full paper is accepted by ICTIR'16.
[Mar. 2016] One short paper is accepted by SIGIR'16.
[Dec. 2015] Two full papers are accepted by ECIR'16 and I will attend ECIR'16 in Padova, Italy.
[Aug. 2015] Finished a summer internship in Microsoft Research Redmond/Bing.
[May. 2014] One full paper is accepted by COLING'14.
[Oct. 2013] Attended CIKM'13 in San Francisco, CA, USA.
[Jul. 2013] One full paper and one short paper are accepted by CIKM'13.
Publications By Years and Topics Google Scholar My DBLP Google Calendar CS Top Cited Papers (8 SIGIR, 8 CIKM, 1 ICML, 1 ICLR, 1 ACL, 1 WWW, 1 WSDM, 1 EMNLP, 1 ICDM, 1 NAACL)
Deep Learning in QA/Conversations and IR/Ranking/Search/Ads/Recommender System
[36] Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky and Marc Najork, Natural Language Understanding with Privacy-Preserving BERT. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 1-5, 2021. Full Oral Paper. Acceptance rate=21.7% (271 out of 1251).
[35] Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Phillip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, Donald Metzler. Long Range Arena: A Benchmark for Efficient Transformers. In Proceedings of the Ninth International Conference on Learning Representations (ICLR 2021) [PDF] [Code]
[34] Jiecao Chen, Liu Yang, Karthik Raman, Michael Bendersky, Jung-Jung Yeh, Yun Zhou, Marc Najork, Danyang Cai and Ehsan Emadzadeh. DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling. In the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020). Findings of EMNLP. [PDF]
[33] Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan. Sparse Sinkhorn Attention. In Proceedings of the 37th International Conference on Machine Learning (ICML 2020), Vienna, Austria. July 12-18, 2020. Full Oral Paper. Acceptance rate=21.8% (1088 out of 4990) (CCF Rank A) [PDF]
[32] Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork, Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching, In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19-23, 2020. Full Oral Paper. Acceptance rate=21% (193 out of 920). arXiv preprint. [PDF][Code][Media Coverage]
[31] Chen Qu, Liu Yang, Cen Chen, Minghui Qiu, W. Bruce Croft and Mohit Iyyer. Open-Retrieval Conversational Question Answering. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China. July 25-30, 2020. Full Oral Paper. Acceptance rate=26% (147 out of 555) (CCF Rank A) [PDF]
[30] Zizhen Wang, Yixing Fan, Jiafeng Guo, Liu Yang, Ruqing Zhang, Yanyan Lan, Xueqi Cheng, Hui Jiang and Xiaozhao Wang. Match^2: A Matching over Matching Model for Similar Question Identification. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China. July 25-30, 2020. Full Oral Paper. Acceptance rate=26% (147 out of 555) (CCF Rank A) [PDF]
[29] Liu Yang, Minghui Qiu, Chen Qu, Cen Chen, Jiafeng Guo, Yongfeng Zhang, Bruce Croft and Haiqing Chen. IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems. In Proceedings of The Web Conference 2020 (WWW 2020), Taipei, China, April 20-24, 2020. Short Oral Paper. Acceptance rate=24.6% (98 out of 397). [PDF][Bibtex][arXiv Preprint][Code] (CCF Rank A)
[28] Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft and Mohit Iyyer. Attentive History Selection for Conversational Question Answering. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), Beijing, China, November 03-07, 2019. Full Oral Paper. Acceptance rate=19.4% (200 out of 1030). [PDF][Bibtex][arXiv Preprint]
[27] Liu Yang, Junjie Hu, Minghui Qiu, Chen Qu, Jianfeng Gao, W. Bruce Croft, Xiaodong Liu, Yelong Shen, Jingjing Liu. A Hybrid Retrieval-Generation Neural Conversation Model. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), Beijing, China, November 03-07, 2019. Full Oral Paper. Acceptance rate=19.4% (200 out of 1030). [PDF][Bibtex][arXiv Preprint][Code][Slides]
[26] Liu Yang, Response Retrieval in Information-seeking Conversations. PhD thesis, University of Massachusetts Amherst, 2019. [PDF][Bibtex][Talk Slides][Talk PDF]
[25] Sheikh Muhammad Sarwar, John Foley, Liu Yang and James Allan. Sentence Retrieval for Entity List Extraction with a Seed, Context and Topic, In Proceedings of The 5th ACM SIGIR International Conference on the Theory of Information Retrieval(ICTIR 2019). Santa Clara, California, USA. October 2-5, 2019. Short Paper.
[24] Chen Qu, Liu Yang, Minghui Qiu, W. Bruce Croft, Yongfeng Zhang and Mohit Iyyer. BERT with History Answer Embedding for Conversational Question Answering, In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), Paris, France. July 21-25, 2019. Short Paper. Acceptance rate=24% (108 out of 443) (CCF Rank A) [PDF][Code][Data and Leaderboard]
[23] Jiafeng Guo, Yixing Fan, Liang Pang, Liu Yang, Qingyao Ai, Hamed Zamani, Chen Wu, W. Bruce Croft, Xueqi Cheng. A Deep Look into Neural Ranking Models for Information Retrieval, arXiv:1903.06902. Accepted by Information Processing & Management, 2019, (IP&M 2019). [arXiv Preprint]
[22] Chen Qu, Liu Yang, W. Bruce Croft, Yongfeng Zhang, Johanne R Trippas and Minghui Qiu. User Intent Prediction in Information-seeking Conversations, In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), Glasgow, Scotland, UK, March 10-14, 2019. Full Paper. [PDF][Code]
[21] Chen Qu, Liu Yang, W. Bruce Croft, Falk Scholer and Yongfeng Zhang. Answer Interaction in Non-factoid Question Answering Systems, In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), Glasgow, Scotland, UK, March 10-14, 2019. Short Paper. [PDF]
[20] Chen Qu, Feng Ji, Minghui Qiu, Liu Yang, Zhiyu Min, Haiqing Chen, Jun Huang and W. Bruce Croft. Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching. In Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019), Melbourne, Australia, February 11-15, 2019. Full Oral Paper. Acceptance rate=16% (84 out of 511) [PDF]
[19] Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft. Towards Conversational Search and Recommendation: System Ask, User Respond. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), Turin, Italy, October 22-26, 2018. Full Oral Paper. Acceptance rate=17% (147 out of 862). [PDF][Bibtex]
[18] Minghui Qiu, Liu Yang, Feng Ji, Wei Zhou, Weipeng Zhao, Jun Huang, Haiqing Chen, W. Bruce Croft, Wei Lin. Transfer Learning for Context-Aware Question Matching in Information-seeking Conversation Systems in E-commerce. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), Melbourne, Australia, July 15-20, 2018. Short Paper. Acceptance rate=24% (126 out of 526) [PDF][Bibtex] (CCF Rank A)
[17] Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, Haiqing Chen. Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems, In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, U.S.A. July 8-12, 2018. Full Oral Paper. Acceptance rate=21% (86 out of 409). [PDF][Code][Data][Slides][PPT][Bibtex] (CCF Rank A)
[16] Chen Qu, Liu Yang, W. Bruce Croft, Johanne R Trippas, Yongfeng Zhang, Minghui Qiu. Analyzing and Characterizing User Intent in Information-seeking Conversations, In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, U.S.A. July 8-12, 2018. Short Paper. Acceptance rate=30% (98 out of 327).[PDF][Data][Poster][Bibtex] (CCF Rank A)
[15] Daniel Cohen, Liu Yang, W. Bruce Croft. WikiPassageQA: A Benchmark Collection for Research on Non-factoid Answer Passage Retrieval, In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), Ann Arbor, Michigan, U.S.A. July 8-12, 2018. Short Paper. Acceptance rate=30% (98 out of 327).[PDF][Data][Bibtex] (CCF Rank A)
[14] Liu Yang, Susan T. Dumais, Paul N. Bennett and Ahmed Hassan Awadallah. Characterizing and Predicting Enterprise Email Reply Behavior, In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), Tokyo, Japan, August 7-11, 2017. Full Oral Paper. Acceptance rate=22% (78 out of 362).[PDF][Data][Slides][Bibtex] (CCF Rank A)
[13] Liu Yang, Hamed Zamani, Yongfeng Zhang, Jiafeng Guo, W. Bruce Croft. Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation, In Neu-IR 2017: The SIGIR 2017 Workshop on Neural Information Retrieval (SIGIR Neu-IR 2017), Tokyo, Japan, August 7-11, 2017. Oral Presentation. [Arxiv Version][Slides][Poster][Bibtex]
[12] Liu Yang, Qingyao Ai, Jiafeng Guo, W. Bruce Croft. aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model, In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, IN, USA. October 24-28, 2016. Full Oral Paper. Acceptance rate=17.6% (165 out of 935). [PDF][Slides][Bibtex][Code in Java][Code with TensorFlow/Keras in MatchZoo V1.0][ACL Wiki on QA][Arxiv Version][aNMM metrics on WikiQA data]
[11] Qingyao Ai, Liu Yang, Jiafeng Guo, W. Bruce Croft. Analysis of the Paragraph Vector Model for Information Retrieval, In Proceedings of The 2nd ACM International Conference on the Theory of Information Retrieval (ICTIR 2016). Newark, DE, USA. September 12-16, 2016. Full Oral Paper. [PDF][Slides][Bibtex]
[10] Qingyao Ai, Liu Yang, Jiafeng Guo, W. Bruce Croft. Improving Language Estimation with the Paragraph Vector Model for Ad-hoc Retrieval, In Proceedings of the 39th Annual ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2016). Pisa, Italy. July 18-10, 2016. Short Paper.[PDF][Bibtex] (CCF Rank A)
[9] Liu Yang, Qingyao Ai, Damiano Spina, Ruey-Cheng Chen, Liang Pang, W. Bruce Croft, Jiafeng Guo and Falk Scholer. Beyond Factoid QA: Effective Methods for Non-factoid Answer Sentence Retrieval. In Proceedings of the 38th European Conference on Information Retrieval (ECIR 2016), Padova, Italy, March 20-23, 2016. Full Oral Paper. Acceptance rate = 21%.[PDF][Data][Code][Slides][Poster][Bibtex]
[8] Liu Yang, Qi Guo, Yang Song, Sha Meng, Milad Shokouhi, Kieran McDonald and W. Bruce Croft. Modelling User Interest for Zero-query Ranking. In Proceedings of the 38th European Conference on Information Retrieval (ECIR 2016), Padova, Italy, March 20-23, 2016. Full Oral Paper. Acceptance rate = 21%.[PDF][Slides][Bibtex]
[7] Liu Yang, Minghui Qiu, Swapna Gottipati, Feida Zhu, Jing Jiang, Huiping Sun and Zhong Chen. CQARank: Jointly Model Topics and Expertise in Community Question Answering. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, CA, USA. October 2013. Full Oral Paper, Top 3 Cited Papers in CIKM'13 . Acceptance rate=16.8% (143 out of 848). [PDF][Slides][PPT][Bibtex][Code][Data]
[6] Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu and Lizi Liao. Generating Supplementary Travel Guides from Social Media. In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), Dublin, Ireland, August 23-29, 2014. Full Oral Paper. [PDF][Slides][Data][Bibtex] (Travel CQA text summarization)
[5] Jianguang Du, Jing Jiang, Liu Yang, Dandan Song, Lejian Liao. ShellMiner: Mining Organizational Phrases in Argumentative Texts in Social Media. In Proceedings of the 14th IEEE International Conference on Data Mining (ICDM 2014 ), Shenzhen, China, December 14-17, 2014. Short Paper. Acceptance rate = 19.7% (143 out of 727). [PDF][Bibtex]
[4] Minghui Qiu, Liu Yang and Jing Jiang. Modeling Interaction Features for Debate Side Clustering. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, CA, USA. October 2013. Short Paper, Acceptance rate=12.5% (106 out of 848). [PDF][Bibtex]
[3] Minghui Qiu, Liu Yang and Jing Jiang. Mining User Relations from Online Discussions using Sentiment Analysis and Probabilistic Matrix Factorization.In Proceedings of the 2013 Conference of North American Chapter of Association for Computational Linguistics: Human Language Technologies (NAACL 2013), Atlanta, GA, USA. June 2013. Long Paper, Acceptance rate=30% (88 out of 293). [PDF][Bibtex][Code][Data]
[2] Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang. An Integrated Model for User Attribute Discovery: A Case Study on Political Affiliation Identification. In Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014), Tainan, Taiwan, May 2014. Full Oral Paper. Acceptance rate=10.8% (40 out of 371).[PDF][Bibtex]
[1] Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu and Jing Jiang. Predicting User's Political Party using Ideological Stances. In Proceedings of the 5th International Conference on Social Informatics (SocInfo 2013), Kyoto, Japan. November 2013. Full Oral Paper, Best Paper Runner-ups .[PDF][Slides][Bibtex]
Selected Professional Services
Session Chair for Neural Networks & Applications, CIKM 2020
Senior Program Committee (SPC) Member for CIKM 2020, CIKM 2021, CIKM 2022, CIKM 2023
Program Committee Member after 2021: WSDM 2021, WWW 2021, AAAI 2021, IJCAI 2021, SIGIR 2021, ACL 2021, WSDM 2022, WWW2022, SIGIR 2022, WSDM 2023, SIGIR 2023, ACL 2023
Program Committee Member 2020: AAAI 2020, SIGIR 2020, KDD 2020, EMNLP 2020, AACL 2020
Program Committee Member 2019: AAAI 2019, WWW 2019, WSDM 2019, SIGIR 2019, KDD 2019, ACL 2019, EMNLP 2019
Program Committee Member 2018: KDD 2018, ACL 2018, EMNLP 2018, WSDM 2018, CIKM 2018, ICTIR 2018, ECIR 2018 (Reviewer), AIRS 2018
Program Committee Member 2017: ICTIR 2017, CIKM 2017, WWW 2017 (Reviewer)
Program Committee Member 2015: CIKM 2015
Invited Journal Reviewer, Journal of the Association for Information Science and Technology (JASIST)
Invited Journal Reviewer, ACM Transactions on Information Systems (TOIS)
Patents
I am a co-inventor on several US patents related to machine learning, IR and NLP based on my work at Google.
US20210248450A1, Sorting attention neural networks
US20210374345A1, Processing large-scale textual inputs using neural networks
US20220129638A1, Systems and methods for machine-learned prediction of semantic similarity between documents
Invited Talks
Deep Learning for Answer Retrieval and Information-seeking Conversations
Research talks at Google Research, Amazon and Alibaba Seattle
Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
Microsoft Research Redmond, August 2, 2018. Host: Dr. Paul Bennett
Question Answering with Deep Text Matching and Learning to Rank
Data Science Lab of JD.com, October 25, 2017. Host: Dr. Zhaochun Ren
Selected Open Source Projects
MatchZoo: MatchZoo is a toolkit for deep neural text matching. It was developed with a focus on facilitating the designing, comparing and sharing of deep text matching models. The implemented models include ARC-I/ARC-II, DSSM, CDSSM, MatchPyramid, DRMM, aNMM, MV-LSTM, Duet, etc.
NeuralResponseRanking: NeuralResponseRanking is an open source package for several neural matching models for response ranking in information-seeking conversations.
LDAGibbsSampling: LDAGibbsSampling is an open source package for Gibbs sampling inference of LDA model, which could be used for topic modeling in text mining.