Research

Natural language processing

  1. Eric Graves, Qiang Ning, and Prithwish Basu. “An information theoretic model for summarization, and some basic results.” To appear in the IEEE International Symposium on Information Theory (ISIT), 2019. [arxiv version]
  2. Qiang Ning, Hangfeng He, Chuchu Fan, and Dan Roth. “Partial or Complete, That’s The Question.” To appear in NAACL, 2019. [website] [pdf]
  3. Qiang Ning, Ben Zhou, Zhili Feng, Haoruo Peng, and Dan Roth. “CogCompTime: A Tool for Understanding Time in Natural Language Text.” EMNLP (demo track), 2018. [website] [pdf] [poster] [online demo][github].
    • A state-of-the-art automatic tool for:
    • Time expression extraction and normalization
    • Temporal relation extraction
  4. Qiang Ning, Hao Wu, and Dan Roth. “A Multi-Axis Annotation Scheme for Event Temporal Relations.” ACL, 2018. [website] [pdf] [Annotation Guidelines] [talk] [github:MATRES]
    • A new crowdsourcing annotation scheme for collecting temporal relation data more reliably and more efficiently
    • Achieved approx. 20% improvement in performance
  5. Qiang Ning, Zhili Feng, Hao Wu, and Dan Roth. “Joint Reasoning for Temporal and Causal Relations.” ACL, 2018. [website][pdf] [talk] [github:TCR]
  6. Qiang Ning, Zhongzhi Yu, Chuchu Fan, and Dan Roth. “Exploiting Partially Annotated Data in Temporal Relation Extraction.” *SEM, 2018 (short paper). [website][pdf] [poster] [github]
    • Incidental supervision for temporal relation extraction
  7. Qiang Ning, Hao Wu, Haoruo Peng, and Dan Roth. “Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource.” NAACL, 2018. [website][pdf] [poster] [github:TemProb] [Download TemProb]
    • Knowledge-base encoding prior statistics
    • For example, “die” should be after “explode”, instead of before; “ask” should be before “help” instead of after
    • Mined from a million NYT news articles using Amazon Web Services (AWS)
  8. Qiang Ning, Zhili Feng, and Dan Roth. “A Structured Learning Approach to Temporal Relation Extraction.” EMNLP, 2017. [website][pdf] [talk] [github]
    • Structured Learning
    • Constraint-Driven Learning (CoDL)

Signal processing

  1. Qiang Ning, Chao Ma, Fan Lam, and Zhi-Pei Liang. “Spectral Quantification for High-Resolution MR Spectroscopic Imaging with Spatiospectral Constraints.” IEEE Transactions on Biomedical Engineering, vol. 64, no. 5, p1178-1186, May 2017 (DOI: 10.1109/TBME.2016.2594583). [pdf]
    • Brain anatomy guided metabolite measuring
    • Cramer-Rao bound analysis
    • Accelerated brain imaging
  2. Chao Ma, Fan Lam, Qiang Ning, Curtis Johnson, and Zhi-Pei Liang. “High-Resolution 1H-MRSI of the Brain Using Short-TE SPICE.” Magnetic Resonance in Medicine, vol. 77, no. 2, p467-479, Feb 2017. [pdf]
  3. Qiang Ning, Chao Ma, Fan Lam, Bryan Clifford, and Zhi-Pei Liang. “Removal of Nuisance Signal from Sparsely Sampled 1H-MRSI Data Using Physics-based Spectral Bases.” 24th Annual ISMRM Scientific Meeting and Exhibition, Singapore, Singapore, May 2016. [pdf] [unsubmitted draft]
  4. Qiang Ning, Chao Ma, and Zhi-Pei Liang. “Spectral Estimation for Magnetic Resonance Spectroscopic Imaging with Spatial Sparsity Constraints.” IEEE International Symposium on Biomedical Imaging: From Nano to Macro, New York, April 2015. [pdf]
  5. Qiang Ning, Chao Ma, and Zhi-Pei Liang. “Joint Estimation of Spectral Parameters from MR Spectroscopic Imaging Data” 23nd Annual ISMRM Scientific Meeting and Exhibition, Toronto, Canada, June 2015. [pdf]
  6. Qiang Ning, Chao Ma, Curtis Johnson, and Zhi-Pei Liang. “Towards Short-TE MR Spectroscopic Imaging: Spectral Decomposition and Removal of Baseline Signals.” 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, August 2014. [pdf] [poster]
  7. Qiang Ning, Kan Chen, Li Yi, Chuchu Fan, Yao Lu, and Jiangtao Wen. “Image Super-Resolution via Analysis Sparse Prior.” IEEE Signal Processing Letters, vol. 20, no. 4, p399-402, April 2013. [pdf] [code]
    • Image reconstruction/super-resolution
    • Compressed sensing

Patent

  1. CN2012105247162, granted April 17, 2013.

Reviewer for

  • The Annual Meeting of the Association for Computational Linguistics (ACL)
  • Conference on Empirical Methods in Natural Language Processing (EMNLP)
  • The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)
  • AAAI Conference on Artificial Intelligence
  • European Conference on Information Retrieval (ECIR)
  • Journal of Artificial Intelligence Research (JAIR)
  • IEEE Signal Processing Letters (SPL)
  • IEEE Transactions on Biomedical Engineering (TBME)
  • Magnetic Resonance Imaging (MRM)