Bing Liu (刘冰) Ph.D. Candidate Electrical and Computer Engineering Carnegie Mellon University Email: liubing at cmu dot edu Office: Bldg 19, NASA Research Park [Publications] [Education] [Professional Experiences] [Awards] [Teaching] [CV] My Github @hadoopit

Hi, I am a Ph.D. candidate (expected to graduate in 2018) in the Department of ECE at Carnegie Mellon University.
I work in SPEECH@SV group in CMU Silicon Valley Campus, advised by Professor Ian Lane.
I received my Bachelor degree in Electrical and Electronic Engineering from Nanyang Technological University (Singapore) in 2011.
Before joining CMU in 2013, I was at Oracle building big data solutions on Hadoop.

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

  @inproceedings{Liu+2017,
    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]


• 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},
    month     = {September},
    year      = {2016},
    address   = {Los Angeles},
    publisher = {Association for Computational Linguistics},
    pages     = {22--30},
    url       = {http://www.aclweb.org/anthology/W16-3603}
  }
  

[bib] [paper] [slides] [talk] [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},
    doi={10.21437/Interspeech.2016-1352},
    url={http://dx.doi.org/10.21437/Interspeech.2016-1352},
    pages={685--689}
  }
  

[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]


• Fabrication Tolerance Study on Mode-coupling-based Polarization Rotators
  Bing Liu, Ping Shum, Jing Zhang, and Guo-Qiang Lo.
  In IEEE ICCS 2010.


• A Novel Side-Pumping Coupler for High-Power Fiber Laser
  Bing Liu, Chinlon Lin.
  In Proceedings of URECA (NTU) 2009.

• Carnegie Mellon University
• Ph.D. in Electrical and Computer Engineering (2013.08 - Present)
• 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 - Present)

• Design and develop end-to-end trainable neural network model for task-oriented dialog that shows robust performance in tracking dialog state and handling ambiguous user input
• Optimize dialog policy with deep reinforcement learning in the end-to-end trainable framework


• 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)

• Conducted research on designing high performance polarization rotators and splitters

• 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. 11-751/18-781 Speech Recognition and Understanding, CMU. Fall 2016
• 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: June, 2017