About me

I'm currently a Senior Engineering Manager at Twitter Cortex. Previously, I was leading the Machine Learning and Data Platform efforts at Fast. Before that, I was also a Research Scientist Manager at Facebook (now Meta) supporting a team that focuses on building Multimodal AI Assistant. I received my Ph.D. degree in September, 2017 from the Department of Computer Science, University of California, Santa Barbara, under the supervision of Prof. Xifeng Yan. During my Ph.D Studies, I worked on various research projects on sequence mining, information extraction, active learning and deep learning. In general, my research was focused on developing better knowledge extraction tools for sequence data (e.g., biological sequences, event streams, text corpus). In addition, I also had some experiences with bioinformatics research such as DNA sequences assembly, SNPs calling and gene expression analysis.

Before I started my Ph.D. studies at UCSB, I also obtained B.S. and M.S. in Computer Science from Northeastern University, China. Find more details about me in my CV.

What's New

  • 08/2021: Paper "NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions" accepted to EMNLP 2021.
  • 08/2021: Open-sourced NUANCED:: a user-centric conversational recommendation dataset that contains 5.1k annotated dialogues and 26k high-quality user turns.
  • 03/2021: Paper "Adding Chit-Chats to Enhance Task-Oriented Dialogues" accepted to NAACL 2021.
  • 09/2020: Paper "User Memory Reasoning for Conversational Recommendation" accepted to COLING 2020.
  • 10/2019: Open-sourced ReAgent: a modular, end-to-end platform for building reasoning systems. It closes the loop of turning actions into feedback, and feedback into training data for RL and online learning. ReAgent is used at Facebook to drive tens of billions of decisions per day.
  • 12/2018: Open-sourced PyText: a deep-learning based NLP modeling framework now being used as the goto platform at Facebook and the open source community.
  • 07/2017: We developed a new motif discovery tool, DeepMotif, that acheives even better performance than ASC+MEME (already 10,000 times faster than MEME). It's 10-100 times faster and doesn't rely on MEME. Learn more about them here. For more information or licensing, please contact me.
  • 06/2017: Our motif discovery solution, ASC+MEME (paper), is licensed to SerImmune Inc. funded by NIH, illumina, Merck, etc. to find motifs from massive protein sequences generated by modern sequencing techniques.

Publications

  • NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions
    Zhiyu Chen, Honglei Liu, Hu Xu, Seungwhan Moon, Hao Zhou, Bing Liu. Proc. of the Conf. on Empirical Methods in Natural Language Processing (EMNLP 2021). [paper][data]
  • Adding Chit-Chats to Enhance Task-Oriented Dialogues
    Kai Sun, Seungwhan Moon, Paul Crook, Stephen Roller, Becka Silvert, Bing Liu, Zhiguang Wang, Honglei Liu, Eunjoon Cho, Claire Cardie. Proc. of the Annual Conf. of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2021). [paper]
  • User Memory Reasoning for Conversational Recommendation
    Hu Xu, Seungwhan Moon, Honglei Liu, Bing Liu, Pararth Shah, Bing Liu, Philip S. Yu. Proc. of Int. Conf. on Computational Linguistics (COLING 2020). [paper]
  • Federated User Representation Learning
    Duc Bui, Kshitiz Malik, Jack Goetz, Honglei Liu, Seungwhan Moon, Anuj Kumar, Kang G. Shin. arXiv preprint arXiv:1909.12535 (2019). [paper]
  • Active Federated Learning
    Jack Goetz, Kshitiz Malik, Duc Bui, Seungwhan Moon, Honglei Liu, Anuj Kumar. Workshop on Federated Learning for Data Privacy and Confidentiality at Neural Information Processing Systems (NeurIPS 2019). [paper]
  • Global Textual Relation Embedding for Relational Understanding
    Zhiyu Chen, Hanwen Zha, Honglei Liu, Wenhu Chen, Xifeng Yan, Yu Su. Proc. of the Annual Meeting of the Association for Computational Linguistics (ACL 2019). (Short Paper) [paper]
  • Interpretability of Deep Reinforcement Learning Models in a Conversational System
    Honglei Liu, Parath Shah, Wenxuan Li, Wenhai Yang, Anuj Kumar. in submission
  • Explore-Exploit: A Framework for Interactive and Online Learning
    Honglei Liu, Anuj Kumar, Wenhai Yang, Benoit Dumoulin. Systems for Machine Learning Workshop at Neural Information Processing Systems (NeurIPS 2018). [paper]
    Open-sourced as ReAgent , a modular, end-to-end platform for building reasoning systems
  • PoQaa: Text Mining and Knowledge Sharing for Scientific Publications
    Keqian Li, Ping Zhang, Honglei Liu, Hanwen Zha, Xifeng Yan. Proc. of Int. Conf. on Knowledge Discovery and Data Mining (KDD 2018). (demo) [paper][video]
  • In Vitro Validation of in Silico Identified Inhibitory Interactions
    Honglei Liu, Daniel Bridges, Connor Randall, Sara A. Solla, Bian Wu, Paul Hansma, Xifeng Yan, Kenneth S. Kosik, Kristofer Bouchard. Journal of Neuroscience Methods 321 (2019): 39-48. [paper]
  • Global Relation Embedding for Relation Extraction
    Yu Su*, Honglei Liu*, Semih Yavuz, Izzeddin Gur, Huan Sun, Xifeng Yan. Proc. of the Annual Conf. of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018). (*: Equal Contribution) [paper][source code]
  • Active Learning of Functional Networks from Spike Trains
    Honglei Liu, Bian Wu. SIAM Int. Conf. on Data Mining (SDM 2017). [paper][supplementary materials][source code]
  • Fast Motif Discovery in Short Sequences
    Honglei Liu, Fangqiu Han, Hongjun Zhou, Xifeng Yan, Kenneth S. Kosik. Proc. of Int. Conf. on Data Engineering (ICDE 2016). [paper] [slides] [poster] [software]
    Software licensed to SerImmune Inc. to produce real world value
  • ALAE: Accelerating Local Alignment with Affine Gap Exactly in Biosequence Databases
    Xiaochun Yang, Honglei Liu, Bin Wang. Proc. of Int. Conf. on Very Large Data Bases (VLDB 2012). [paper][source code]
  • Approximate Substring Query Algorithms Supporting Local Optimal Matching
    Honglei Liu, Xiaochun Yang, Bin Wang, Rong Jin. Journal of Frontiers of Computer Science and Technology, 2011. [source code]

Patents

  • Generating Proactive Reminders for Assistant Systems
    US Patent Pending US17035253
  • Personalized Conversational Recommendations by Assistant Systems
    US Patent Pending US16921665
  • Personalized Federated Learning for Assistant Systems
    US Patent Pending US16815990
  • Active Federated Learning for Assistant Systems
    US Patent Pending US16815960
  • Methods, Mediums, and Systems for Training a Model
    US Patent Pending US16731321
  • Methods, Mediums, and Systems for Representing a Model in a Memory of Device
    US Patent Pending US16731345
  • Methods, Mediums, and Systems for Providing a Model for an End-User Device
    US Patent Pending US16731304
  • Suppressing Reminders for Assistant Systems
    US Patent Pending US16733044
  • Interpretability of Deep Reinforcement Learning Models in Assistant Systems
    US Patent Pending US16389769
  • Building Customized User Profiles Based on Conversational Data
    US/EU Patent Pending US2019327330A1/EP3557500A1
  • Smart Assistant Systems
    US Patent Pending US62923342
  • Systems and Methods for Off-Target Sequence Detection
    US Patent Pending US20180075186A1
  • Biological Sequence Local Comparison Method Capable of Obtaining Complete Solution
    CN Patent Granted CN102750461B
  • An Electric Automobile Battery Replacing Device
    CN Patent Granted CN202089042U

Experience

  • 07/2022 - Present: Senior Engineering Manager - Machine Learning, Twitter
  • 04/2022 - 07/2022: Senior Engineering Manager - Machine Learning, Affirm
  • 09/2021 - 04/2022: Head of Machine Learning and Data Platform, Fast
  • 04/2020 - 09/2021: Research Scientist Manager, Facebook
  • 02/2020 - 04/2020: Staff Research Scientist, Facebook
  • 01/2019 - 02/2020: Senior Research Scientist, Facebook
  • 07/2017 - 12/2018: Research Scientist, Facebook
  • 06/2016 - 09/2016: Intern, Facebook
    Topic: Indexing and Mining Billions of Time Series
  • 07/2015 - 09/2015: Bioinformatics Intern, Illumina
    Topic: Fast Specificity Checking for Multiplex PCR Primer Design

Fun Stuff

Facebook Lunar New Year Gala

I was the organizer/director of the 2020 Facebook Lunar New Year Gala, which had 30+ volunteers, 150+ performers, 900+ guests and FB VP level speakers attended. We spent 4+ months in preparation for this. Every year, we organize this event so that our co-workers and their families can have a place to get together and celebrate lunar new year.

Shanghui Life

An iOS app that allows users to post, find and join events. Users can also invite friends to events, search nearby businesses, follow others, post texts and pictures, etc. I did all the coding for the backend.

Intelligent car

An intelligent car that can navigate by itself and follow a road track. I was in charge of the software part. We won the first prize in a national competition. Check more photos here.

Acoustic positioning car

A car that can locate its position by sending / receving sound wave signals and do a series of tasks. I was in charge of the software part. We won the second prize in a national competition with our design. Check more photos here.