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Thien Huu Nguyen

Assistant Professor
Department of Computer and Information Science
University of Oregon
Email: thien AT cs dot uoregon dot edu
Address:
        330, Deschutes Hall
        University of Oregon
        1477 E. 13th Avenue
        Eugene, OR 97403, USA
       



I am an Assistant Professor in the Department of Computer and Information Science at the University of Oregon. I obtained my Ph.D. and M.S. degrees in Computer Science from New York University (working with Ralph Grishman and Kyunghyun Cho), and my B.S. degree in Computer Science from Hanoi University of Science and Technology. I was also a postdoc in the University of Montréal, working with Yoshua Bengio and people in the Montreal Institute for Learning Algorithms.

RESEARCH

My research explores mechanisms to understand human languages for computers so that computers can perform cognitive language-related tasks for us. Among others, I am especially interested in distilling structured information and mining useful knowledge from the massive human-written text of various domains.

Toward this end, our lab employs and designs effective learning algorithms for information extraction and text mining in natural language processing and data mining. We are currently focusing on deep learning algorithms to solve such problems. We are among the first groups that develop deep learning models and demonstrate their effectiveness for information extraction.

We are also targeting other language-related problems with deep learning, including reading comprehension, machine translation, natural language generation, chatbots and language grounding.

HIRING

I am currently recruiting one or two graduate students for Fall 2020 to work on interesting projects of natural language processing and deep learning. Interested candidates can email me for more information. The application procedure for graduate students in the Department of Computer and Information Science can be found here.

I am also willing to supervise students at UO who would like to do research on natural language processing, deep learning and the related topics. Please email me if you are interested in this possibility.

PUBLICATIONS

2020

  • Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning
    Amir Pouran Ben Veyseh, Nasim Nouri, Franck Dernoncourt, Dejing Dou and Thien Huu Nguyen
    Proceedings of EMNLP 2020
    [To Appear]    
  • Introducing a New Dataset for Event Detection in Cybersecurity Texts
    Hieu Man Duc Trong, Duc Trong Le, Amir Pouran Ben Veyseh, Thuat Nguyen and Thien Huu Nguyen
    Proceedings of EMNLP 2020
    [To Appear]    
  • Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks
    Viet Dac Lai, Tuan Ngo Nguyen and Thien Huu Nguyen
    Proceedings of EMNLP 2020
    [To Appear]    
  • Structural and Functional Decomposition for Personality Image Captioning in a Communication Game
    Minh Thu Nguyen, Duy Phung, Minh Hoai and Thien Huu Nguyen
    Proceedings of EMNLP 2020 (Findings)
    [To Appear]    
  • The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction
    Hieu Minh Tran, Minh Trung Nguyen and Thien Huu Nguyen
    Proceedings of EMNLP 2020 (Findings)
    [To Appear]    
  • Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation
    Amir Pouran Ben Veyseh, Nasim Nouri, Franck Dernoncourt, Quan Hung Tran, Dejing Dou and Thien Huu Nguyen
    Proceedings of EMNLP 2020 (Findings)
    [To Appear]    
  • Bag of Biterms Modeling for Short Texts
    Anh Tuan Phan, Bach Tran, Thien Huu Nguyen, Linh Van Ngo and Khoat Than
    Knowledge and Information Systems Journal (KAIS) 2020
    [To Appear]    
  • Improving Slot Filling by Utilizing Contextual Information
    Amir Pouran Ben Veyseh, Franck Dernoncourt and Thien Huu Nguyen
    Proceedings of the 2nd NLP for Conversational AI Workshop (ConvAI) at ACL 2020, Seattle, USA, July 2020
    [To Appear]    
  • Extensively Matching for Few-shot Learning Event Detection
    Viet Lai, Franck Dernoncourt and Thien Huu Nguyen
    Proceedings of the 1st Joint Workshop on Narrative Understanding, Storylines, and Events (NUSE) at ACL 2020, Seattle, USA, July 2020
    [To Appear]    
  • Exploiting the Syntax-Model Consistency for Neural Relation Extraction
    Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou and Thien Huu Nguyen
    Proceedings of ACL 2020, Seattle, USA, July 2020
    [To Appear]    
  • Exploiting the Matching Information in the Support Set for Few Shot Event Classification
    Viet Lai, Franck Dernoncourt and Thien Huu Nguyen
    Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), Singapore, May, 2020
    [To Appear]    
  • Learning to Select Important Context Words for Event Detection
    Nghia Ngo, Tuan Ngo Nguyen and Thien Huu Nguyen
    Proceedings of the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020), Singapore, May, 2020
    [To Appear]    
  • Multi-view Consistency for Relation Extraction via Mutual Information and Structure Prediction
    Amir Pouran Ben Veyseh, Franck Dernoncourt, My Thai, Dejing Dou and Thien Huu Nguyen
    Proceedings of AAAI 2020, New York, USA, February 2020
    [To Appear]    
  • A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency
    Amir Pouran Ben Veyseh, Franck Dernoncourt, Dejing Dou and Thien Huu Nguyen
    Proceedings of AAAI 2020, New York, USA, February 2020
    [To Appear]    
  • Multi-task Learning for Metaphor Detection with Graph Convolutional Neural Networks and Word Sense Disambiguation
    Duong Minh Le, My Thai and Thien Huu Nguyen
    Proceedings of AAAI 2020, New York, USA, February 2020
    [To Appear]    

2019

  • On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning
    Tuan Ngo Nguyen, Franck Dernoncourt and Thien Huu Nguyen
    Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019) at EMNLP 2019
    [PAPER]    
  • Extending Event Detection to New Types with Learning from Keywords
    Viet Lai and Thien Huu Nguyen
    Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019) at EMNLP 2019
    [PAPER]    
  • Learning Electronic Health Records through Hyperbolic Embedding of Medical Ontologies
    Qiuhao Lu, Nisansa de Silva, Sabin Kafle, Jiazhen Cao, Dejing Dou, Thien Huu Nguyen, Prithviraj Sen, Brent Hailpern, Berthold Reinwald and Yunyao Li
    Proceedings of the 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB 2019), New York, September 2019
    [PAPER]    
  • Rumor Detection in Social Networks via Deep Contextual Modeling
    Amir Pouran Ben Veyseh, My T. Thai, Thien Huu Nguyen and Dejing Dou
    Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019), Vancouver, Canada, August 2019
    [PAPER]    
  • Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings
    Linh The Nguyen, Linh Van Ngo, Khoat Than and Thien Huu Nguyen
    Proceedings of ACL 2019, Florence, Italy, August 2019
    [PAPER]    
  • Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
    Amir Pouran Ben Veyseh, Thien Huu Nguyen and Dejing Dou
    Proceedings of ACL 2019, Florence, Italy, August 2019
    [PAPER]    
  • Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control
    Amir Pouran Ben Veyseh, Thien Huu Nguyen and Dejing Dou
    Proceedings of IJCAI 2019, Macao, China, August 2019
    [PAPER]    
  • BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop
    Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen and Yoshua Bengio
    Proceedings of ICLR 2019, New Orleans, Louisiana, May 2019
    [PAPER]    
  • Systematic Generalization: What Is Required and Can It Be Learned?
    Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries and Aaron Courville
    Proceedings of ICLR 2019, New Orleans, Louisiana, May 2019
    [PAPER]    
  • One for All: Neural Joint Modeling of Entities and Events
    Trung Minh Nguyen and Thien Huu Nguyen
    Proceedings of AAAI 2019, Honolulu, Hawaii, January 2019
    [PAPER]    

2018

  • A Case Study on Learning a Unified Encoder of Relations
    Lisheng Fu, Bonan Min, Thien Huu Nguyen and Ralph Grishman
    Proceedings of the 4th Workshop on Noisy User-generated Text (W-NUT 2018) at EMNLP 2018
    [PAPER]    
  • Similar but not the Same: Word Sense Disambiguation Improves Event Detection via Neural Representation Matching
    Weiyi Lu and Thien Huu Nguyen
    Proceedings of EMNLP 2018, Brussels, Belgium, November 2018
    [PAPER]    
  • Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs
    Minh Nguyen and Thien Huu Nguyen
    Proceedings of COLING 2018, Santa Fe, New-Mexico, August 2018
    [PAPER]    
  • A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing
    Minh Nguyen, Toan Nguyen and Thien Huu Nguyen
    International Workshop on Security and Privacy Analytics - Anti Phishing Shared Task (IWSPA-AP), March 2018
    [PAPER]    
  • Graph Convolutional Networks with Argument-Aware Pooling for Event Detection
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of AAAI 2018, New Orleans, Lousiana, February 2018
    [PAPER]    
  • Deep Learning for Information Extraction
    Thien Huu Nguyen
    Ph.D. Thesis, New York University, January 2018.
    [PAPER]    

2017

  • Domain Adaptation for Relation Extraction with Domain Adversarial Neural Networks
    Lisheng Fu, Thien Huu Nguyen, Bonan Min and Ralph Grishman
    Proceedings of IJCNLP 2017, Taipei, Taiwan, November 2017
    [PAPER]    

2016

  • New York University 2016 System for KBP Event Nugget: A Deep Learning Approach
    Thien Huu Nguyen, Adam Meyers and Ralph Grishman
    Proceedings of Text Analysis Conference (TAC), Gaithersburg, Maryland, USA, November 2016
    [PAPER]

  • Joint Learning of Local and Global Features for Entity Linking via Neural Networks
    Thien Huu Nguyen, Nicolas Fauceglia, Mariano Rodriguez Muro, Oktie Hassanzadeh, Alfio Massimiliano Gliozzo and Mohammad Sadoghi
    Proceedings of COLING 2016, Osaka, Japan, December 2016
    [PAPER]

  • Modeling Skip-Grams for Event Detection with Convolutional Neural Networks
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of EMNLP 2016, Austin, Texas, November 2016
    [PAPER]

  • Joint Event Extraction via Recurrent Neural Networks
    Thien Huu Nguyen, Kyunghyun Cho and Ralph Grishman
    Proceedings of NAACL 2016, San Diego, June 2016
    [PAPER][CODE]

  • A Two-stage Approach for Extending Event Detection to New Types via Neural Networks
    Thien Huu Nguyen, Lisheng Fu, Kyunghyun Cho and Ralph Grishman
    Proceedings of ACL Workshop on Representation Learning for NLP, Berlin, Germany, 2016
    [PAPER]

  • Combining Neural Networks and Log-linear Models to Improve Relation Extraction
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of IJCAI Workshop on Deep Learning for Artificial Intelligence, New York, USA, 2016
    [PAPER][CODE]

  • Toward Mention Detection Robustness with Recurrent Neural Networks
    Thien Huu Nguyen, Avirup Sil, Georgiana Dinu, and Radu Florian
    Proceedings of IJCAI Workshop on Deep Learning for Artificial Intelligence, New York, USA, 2016
    [PAPER]

2015

  • Improving Event Detection with Abstract Meaning Representation
    Xiang Li, Thien Huu Nguyen, Kai Cao, and Ralph Grishman
    Proceedings of ACL-IJCNLP Workshop on Computing News Storylines (CNewS 2015), Beijing, China, July, 2015
    [PAPER]

  • Event Detection and Domain Adaptation with Convolutional Neural Networks
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of ACL-IJCNLP 2015, Beijing, China, July, 2015
    [PAPER]

  • Semantic Representations for Domain Adaptation: A Case Study on the Tree Kernel-based Method for Relation Extraction
    Thien Huu Nguyen, Barbara Plank and Ralph Grishman
    Proceedings of ACL-IJCNLP 2015, Beijing, China, July, 2015
    [PAPER][CODE]

  • Relation Extraction: Perspective from Convolutional Neural Networks
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of NAACL Workshop on Vector Space Modeling for NLP, Denver, Colorado, June, 2015
    [PAPER][CODE]

2014

  • New York University 2014 Knowledge Base Population Systems
    Thien Huu Nguyen, Yifan He, Maria Pershina, Xiang Li, and Ralph Grishman
    Proceedings of Text Analysis Conference (TAC), Gaithersburg, Maryland, USA, November 2014
    [PAPER]

  • Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction
    Thien Huu Nguyen and Ralph Grishman
    Proceedings of ACL 2014, Baltimore, Maryland, USA, June 2014
    [PAPER]

2013 and before

  • Combining Proper Name-Coreference with Conditional Random Fields for Semi-supervised Named Entity Recognition in Vietnamese Text
    Rathany Chan Sam, Huong Thanh Le, Thuy Thanh Nguyen, and Thien Huu Nguyen
    Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Shenzhen, China, May, 2011
    [PAPER]

STUDENTS

I am fortunate to work with the following students: and many other student collaborators.

TEACHING

  • CIS 313 - Intermediate Data Structures (W19, W20)
  • CIS 607 - Seminar on Deep Learning for Natural Language Processing (W19, W20)
  • CIS 472/572 - Machine Learning (S19, S20)
  • CIS 410/510 - Natural Language Processing (F19)

PROFESSIONAL SERVICES

  • Reviewer: Neural Computation Journal, Transactions on Asian and Low-Resource Language Information Processing, Computational Linguistics
  • Program Committee: NAACL (2016, 2018, 2019), COLING (2016, 2018, 2020), ACL (2017, 2018, 2019, 2020), EMNLP (2017, 2018, 2019, 2020), IJCAI (2017), NeurIPS (2020), LREC (2018, 2020), Rep4NLP (2017, 2018, 2019, 2020)
  • Senior Program Committee: AAAI (2020)

AWARDS

  • IBM Ph.D. Fellowship, 2016
  • Dean's Dissertation Fellowship, Graduate School of Arts and Science, NYU, 2016-2017
  • Harold Grad Prize, Courant Institute of Mathematical Science, NYU, 2016
  • Henry MacCracken Fellowship, New York University, 2012 - 2017
  • Second Prize in Student Scientific Research Conference, by Ministry of Education and Training, Vietnam, 2012


NEWS