Bing Liu (刘冰) Ph.D. Candidate Electrical and Computer Engineering Carnegie Mellon University Email: liubing at cmu dot edu [Publications] [Education] [Professional Experiences] [Awards] [Teaching] [CV] My Github @hadoopit

Hi, I am a Ph.D. candidate in the Department of ECE at Carnegie Mellon University.
I work in SPEECH@SV group, advised by Professor Ian Lane.
I received my Bachelor degree in Electrical Engineering from Nanyang Technological University (Singapore) in 2011.
Before joining CMU in 2013, I was at Oracle building big data solutions on Hadoop.

• 2018/08/30: Successfully defended my PhD thesis! [thesis]
• 2018/04/22: Our (long) paper on "Adversarial Learning of Task-Oriented Neural Dialog Models" is accepted at SIGDIAL 2018!
• 2018/04/02: Thesis proposal paper on "End-to-End Learning of Task-Oriented Dialogs" is accepted for presentation at NAACL 2018 Student Research Workshop. See you in NAACL! [slides] [video]
• 2018/03/26: Presented research work on "Reinforcement Learning for End-to-End Trainable Neural Dialog Models" in GTC 2018.
• 2018/03/26: Our paper on "Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning" is accepted at NAACL 2018 (Industry Track)!
• 2018/02/14: Our paper on "Dialogue Learning with Human Teaching and Feedback in End-To-End Trainable Task-Oriented Dialogue Systems" is accepted at NAACL 2018 as a long paper!
• 2017/11/30: Successfully passed PhD thesis proposal!
• 2017/11/21: We have two papers accepted at NIPS 2017 Workshop on Conversational AI. See you in NIPS!
• 2017/11/08: Our paper on "Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models" is accepted at AAAI 2018! [paper]

• Adversarial Learning of Task-Oriented Neural Dialog Models
  Bing Liu, Ian Lane.
  In SIGDIAL 2018.

  @inproceedings{liu2018adversarial,
    author    = {Bing Liu and Ian Lane},
    title     = {Adversarial Learning of Task-Oriented Neural Dialog Models},
    booktitle = {SIGDIAL},
    year      = {2018}
  }
  

[bib] [paper]


• Dialogue Learning with Human Teaching and Feedback in End-To-End Trainable Task-Oriented Dialogue Systems
  Bing Liu, Gokhan Tur, Dilek Hakkani-Tur, Pararth Shah, and Larry Heck
  In NAACL 2018.

  @inproceedings{liu2018dialogue,
    author={Liu, Bing and Tur, Gokhan and Hakkani-Tur, Dilek and Shah, Pararth and Heck, Larry}, 
    title     = {Dialogue Learning with Human Teaching and Feedback in End-To-End Trainable Task-Oriented Dialogue Systems},
    booktitle = {NAACL},
    year      = {2018}
  }
  

[bib] [paper] [poster]


• Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning
  Pararth Shah, Dilek Hakkani-Tur, Bing Liu, and Gokhan Tur
  In NAACL 2018.

  @inproceedings{shah2018bootstrapping,
    author={Shah, Pararth and Hakkani-Tur, Dilek and Liu, Bing and Tur, Gokhan}, 
    title     = {Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning},
    booktitle = {NAACL},
    year      = {2018}
  }
  

[bib] [paper]


• End-to-End Learning of Task-Oriented Dialogs
  Bing Liu, Ian Lane.
  In NAACL 2018 SRW (thesis proposal paper).

  @inproceedings{liu2018e2e,
    author={Liu, Bing and Lane, Ian}, 
    title     = {End-to-End Learning of Task-Oriented Dialogs},
    booktitle = {NAACL Student Research Workshop},
    year      = {2018}
  }
  

[bib] [paper] [slides] [video]


• Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models
  Bing Liu, Tong Yu, Ian Lane, and Ole Mengshoel.
  In AAAI 2018.

  @inproceedings{liu2018customized,
    author    = {Liu, Bing and Yu, Tong and Lane, Ian and Mengshoel, Ole},
    title     = {Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models},
    booktitle = {AAAI},
    year      = {2018}
  }
  

[bib] [paper]


• Iterative Policy Learning in End-to-End Trainable Task-Oriented Neural Dialog Models
  Bing Liu, Ian Lane.
  In ASRU 2017.

  @inproceedings{liu2017iterative,
    author    = {Bing Liu and Ian Lane},
    title     = {Iterative Policy Learning in End-to-End Trainable Task-Oriented Neural Dialog Models},
    booktitle = {Proceedings of 2017 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU)},
    year      = {2017}
  }
  

[bib] [paper]


• End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learning
  Bing Liu, Gokhan Tur, Dilek Hakkani-Tur, Pararth Shah, and Larry Heck
  In NIPS 2017 Workshop on Conversational AI.

  @inproceedings{liu2017e2e,
    title={End-to-End Optimization of Task-Oriented Dialogue Model with Deep Reinforcement Learning},
    author={Liu, Bing and Tur, Gokhan and Hakkani-Tur, Dilek and Shah, Pararth and Heck, Larry}, 
    booktitle={NIPS Workshop on Conversational AI},
    year={2017}
  }
  

[bib] [paper]


• Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understanding
  Bing Liu, Ian Lane.
  In NIPS 2017 Workshop on Conversational AI.

  @inproceedings{liu2017multi,
    title={Multi-Domain Adversarial Learning for Slot Filling in Spoken Language Understanding},
    author={Liu, Bing and Lane, Ian},
    booktitle={NIPS Workshop on Conversational AI},
    year={2017}
  }
  

[bib] [paper] [slides]


• An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog
  Bing Liu, Ian Lane.
  In Interspeech 2017.

  @inproceedings{Liu2017,
    author={Bing Liu and Ian Lane},
    title={An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog},
    year={2017},
    booktitle={Interspeech 2017}
  }
  

[bib] [paper] [slides]


• Dialog Context Language Modeling with Recurrent Neural Networks
  Bing Liu, Ian Lane.
  In ICASSP 2017.

  @inproceedings{liu-lane:2017:ICASSP,
    title={Dialog Context Language Modeling with Recurrent Neural Networks},
    author={Liu, Bing  and  Lane, Ian},
    booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International Conference on},
    year={2017},
    organization={IEEE}
  }
  

[bib] [paper]


• Joint Online Spoken Language Understanding and Language Modeling With Recurrent Neural Networks
  Bing Liu, Ian Lane.
  In SIGDIAL 2016.

  @InProceedings{liu-lane:2016:SIGDIAL,
    author    = {Liu, Bing  and  Lane, Ian},
    title     = {Joint Online Spoken Language Understanding and Language Modeling With Recurrent Neural Networks},
    booktitle = {Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue},
    year      = {2016}
  }
  

[bib] [paper] [slides] [video] [code]


• Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling
  Bing Liu, Ian Lane.
  In Interspeech 2016.

  @inproceedings{Liu+2016,
    author={Bing Liu and Ian Lane},
    title={Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling},
    year=2016,
    booktitle={Interspeech 2016}
  }
  

[bib] [paper] [code]


• Recurrent Neural Network Structured Output Prediction for Spoken Language Understanding
  Bing Liu, Ian Lane.
  In NIPS Workshop 2015.

  @inproceedings{liu2015recurrent,
    title={Recurrent Neural Network Structured Output Prediction for Spoken Language Understanding},
    author={Liu, Bing and Lane, Ian},
    booktitle={Proc. NIPS Workshop on Machine Learning for Spoken Language Understanding and Interactions},
    year={2015}
  }
  

[bib] [paper]

• Carnegie Mellon University
• Ph.D. in Electrical and Computer Engineering (2013.08 - 2018.08 (Expected))
• Research Area: Machine Learning, Deep Learning, Natural Language Understanding, Spoken Dialog Systems.

• Nanyang Technological University, Singapore
• B.Eng in Electrical and Electronic Engineering (2007.08 - 2011.06)
• Minor Degree: Business
• GPA 4.87/5.0 (Top 2%)

• KTH Royal Institute of Technology, Sweden
• Exchange student in school of Information and Communication Technology (2010.01 - 2010.06)

• Google Research
Software Engineer Intern (2017.05 - 2017.08)

• Designed and developed an end-to-end trainable neural network model for task-oriented dialogs that shows robust performance in natural language understanding, dialog state tracking, and dialog policy learning


• Capio.ai
Software Engineer Intern (2015.05 - 2015.08)

• Developed and integrated Natural Language Understanding modules (intent identification & semantic tagging) with Capio’s Automatic Speech Recognition (ASR) core engine
• Designed contextual RNN language model in Capio’s core engine for enhanced ASR performance


• Capio.ai
Software Engineer Intern (2014.05 - 2014.08)

• Designed and developed the first version of Capio’s cloud infrastructure and APIs for speech recognition


• Oracle
Technical Consultant / Data Engineer (2011.07 - 2013.07)

• Designed and delivered Big Data solution to top tier telecommunication companies in Oracle APAC
• Took full accountability for Big Data project delivery: gathering functional requirements, designing and developing applications, testing and trouble shooting, engaging and advising clients


• Agency for Science, Technology and Research (A*STAR), Singapore
Research Intern (2009.07 - 2009.12)

• Designed high performance polarization rotators and splitters for optical communication

• Google ASRU Travel Grant (2017.10)
• Leo Finzi Memorial Fellowship, CMU ECE (2017/18)
• Outstanding Entry Award - CMU Silicon Valley Annual Tech Showcase (2014.08)
• Carnegie Institute of Technology Dean’s Fellowship (2013.08)
• Oracle Consulting Services ASEAN - Consultant of the Month (2012.05)
• NTU Industrial Attachment Book Prize (Best Overall Performance) (2010.12)
• NTU EEE Dean’s List and President Research Scholar (2008/09/10/11)

• Project Sponsor for 11-751/18-781 Speech Recognition and Understanding, CMU. Fall 2016 and Fall 2017
• Teaching Assistant for 11-755/18-797 Machine Learning for Signal Processing, CMU. Fall 2015
• Teaching Assistant for 18-645 How to Write Fast Code, CMU. Spring 2015

Last updated: September, 2018