Welcome to my homepage!

I am a Research Scientist in the Central Applied Science team at Meta working on computational methods to study interesting latent structures extracted from observed data. My current interests lie in developing methodologies and building systems to understand the uncertainty in human labels and to better leverage human labels in various applications.

Before joining Meta, I obtained my Ph.D. in Computer Science from the University of Maryland, College Park, where I was co-advised by Prof. Philip Resnik and Prof. Jordan Boyd-Graber. My dissertation research focused on developing probabilistic topic models for applications in natural language processing and computational social science. I received my B.Eng. in Computer Science from Nanyang Technological University (NTU), Singapore.

I grew up in Hanoi, Vietnam. The correct spelling of my name in Vietnamese is Nguyễn Việt An. I usually go by An for short.

Publications (Google Scholar & DBLP)

Efficient Online Crowdsourcing with Complex Annotations
Reshef Meir, Viet-An Nguyen, Xu Chen, Jagdish Ramakrishnan, Udi Weinsberg
AAAI 2024
[PDF] [Full version] [Acceptance rate = 23.75% (2342/9862)]

From Labels to Decisions: A Mapping-Aware Annotator Model
Evan Yao, Jagdish Ramakrishnan, Xu Chen, Viet-An Nguyen, Udi Weinsberg
KDD 2023 (Applied Data Science Track)
[ACM URL] [PDF] [Bibtex] [Acceptance rate = 25% (184/725)]

Crowdsourcing with Contextual Uncertainty
Viet-An Nguyen, Peibei Shi, Jagdish Ramakrishnan, Narjes Torabi, Nimar S. Arora, Udi Weinsberg, Michael Tingley
KDD 2022 (Applied Data Science Track)
Meta Research Blog
[ACM URL] [Meta Research URL] [PDF] [Bibtex] [Oral presentation, Slides] [Acceptance rate = 26% (196/753)]

CLARA: Confidence of Labels and Raters
Viet-An Nguyen, Peibei Shi, Jagdish Ramakrishnan, Udi Weinsberg, Henry C. Lin, Steve Metz, Neil Chandra, Jane Jing, Dimitris Kalimeris
KDD 2020 (Applied Data Science Track)
Meta Research Blog
[ACM URL] [Meta Research URL] [Code] [PDF] [Bibtex] [Oral presentation, Slides] [Acceptance rate = 16% (121/756) (~5.8% for oral presentation)]

Guided Probabilistic Topic Models for Agenda-setting and Framing
Viet-An Nguyen
Ph.D. Dissertation, 2015
[URL] [PDF] [Slides]

Tea Party in the House: A Hierarchical Ideal Point Topic Model and Its Application to Republican Legislators in the 112th Congress
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, Kristina Miler
ACL-IJCNLP 2015
[PDF] [Code] [Talk] [Bibtex] [Acceptance rate = 25% (173/692)]

Beyond LDA: Exploring Supervised Topic Modeling for Depression-Related Language in Twitter
Philip Resnik, William Armstrong, Leonardo Claudino, Thang Nguyen, Viet-An Nguyen, and Jordan Boyd-Graber
CLPsych Workshop at NAACL 2015
[PDF] [Bibtex]

Learning a Concept Hierarchy from Multi-labeled Documents
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, Jonathan Chang
NIPS 2014
[PDF] [Poster] [Bibtex] [Acceptance rate = 24.7% (414/1678)]

Sometimes Average is Best: The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik
EMNLP 2014 (short paper)
[PDF] [Poster] [Bibtex] [Acceptance rate = 27.8% (70/252)]

Modeling Topic Control to Detect Influence in Conversations using Nonparametric Topic Models
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik, Deborah A. Cai, Jennifer E. Midberry, Yuanxin Wang
Machine Learning Journal, 95(3): 381-421, June 2014
[URL] [Manuscript] [Bibtex]

Tree-based Label Dependency Topic Models
Viet-An Nguyen, Jordan Boyd-Graber, Jonathan Chang, Philip Resnik
Topic Models Workshop at NIPS 2013
[PDF] [Poster]

Lexical and Hierarchical Topic Regression
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik
NIPS 2013
[PDF] [Appendix] [Bibtex] [Poster] [Acceptance rate = 25.4% (360/1420)]

Argviz: Interactive Visualization of Topic Dynamics in Multi-party Conversations
Viet-An Nguyen, Yuening Hu, Jordan Boyd-Graber, Philip Resnik
NAACL-HLT 2013 (demo track)
[PDF] [Poster] [Bibtex]

Dirichlet Mixtures, the Dirichlet Process, and the Structure of Protein Space
Viet-An Nguyen, Jordan Boyd-Graber, Stephen F. Altschul
Journal of Computational Biology, 20(1): 1-18, January 2013
[URL] [Manuscript] [Bibtex]

SITS: A Hierarchical Nonparametric Model using Speaker Identity for Topic Segmentation in Multiparty Conversations
Viet-An Nguyen, Jordan Boyd-Graber, Philip Resnik
ACL 2012
[PDF] [Slides] [Bibtex] [Appendix] [Code] [Acceptance rate = 19%]

Visual Analysis of Temporal Trends in Social Networks Using Edge Color Coding and Metric Timelines
Udayan Khurana, Viet-An Nguyen, Hsueh-Chien Cheng, Jae-wook Ahn, Xi (Stephen) Chen, Ben Shneiderman
SocialCom 2011
[URL] [Bibtex] [Technical Report]

Modeling Link Formation Behaviors in Dynamic Social Networks
Viet-An Nguyen, Cane Wing-Ki Leung, Ee-Peng Lim
SBP 2011
[PDF] [URL] [Bibtex]

Detecting Product Review Spammers using Rating Behaviors
Ee-Peng Lim, Viet-An Nguyen, Bing Liu, Nitin Jindal, Hady Wirawan Lauw
CIKM 2010
[PDF] [URL] [Bibtex] [Acceptance rate = 13.4% (127/945)]

Messaging Behavior Modeling in Mobile Social Networks
Byung-Won On, Ee-Peng Lim, Jing Jiang, Freddy Chong Tat Chua, Viet-An Nguyen, Loo-Nin Teow
SIN Workshop at SocialCom 2010
[URL] [Bibtex]

Do You Trust to Get Trust? A Study of Trust Reciprocity Behaviors and Reciprocal Trust Prediction
Viet-An Nguyen, Ee-Peng Lim, Hwee-Hoon Tan, Jing Jiang, Aixin Sun
SDM 2010
[PDF] [Bibtex] [Acceptance rate = 23.4% (82/351)]

To Trust or Not to Trust? Predicting Online Trusts using Trust Antecedent Framework
Viet-An Nguyen, Ee-Peng Lim, Aixin Sun, Jing Jiang, Hwee-Hoon Tan
ICDM 2009
[PDF] [URL] [Slides] [Bibtex] [Acceptance rate = 17.7% (139/786)]

Trust Relationship Prediction Using Online Product Review Data
Nan Ma, Ee-Peng Lim, Viet-An Nguyen, Aixin Sun, Haifeng Liu
CNIKM Workshop at CIKM 2009
[URL] [Slides] [Bibtex]

Rule Evolution Approach for Mining Multivariate Time Series Data
Viet-An Nguyen, Vivekanand Gopalkrishnan
ICEIS 2008
[Bibtex]

Academic Services

  • Area Co-chair: NAACL (2016)
  • Conference PC Member / Reviewer: ACL (2014-2021), EMNLP (2012-2020), NAACL (2013-2021), COLING (2016-2018), NeurIPS (2012-2020), ICML (2012-2023), AISTATS (2012-2013, 2021), ICLR (2021-2022), EACL (2021), KDD (2023)
  • Journal Reviewer: Transactions of the Association for Computational Linguistics (2019), Science Advances (2018), Computer Speech and Language (2016), Machine Learning Journal (2016), Journal of Artificial Intelligence Research (2013)