Here To Help

I'm a research scientist at the JHU HLTCOE interested in natural language processing and machine learning. I also have an appointment in the Department of Computer Science and work closely with PhD students and faculty at the Center for Language and Speech Processing.

PhD students:
    David Mueller (co-advised by Mark Dredze)
    Aleem Khan (co-advised by Benjamin Van Durme)
    Sophia Hager (co-advised by Kevin Duh)

About me: I obtained my PhD from JHU in 2015, advised by Jason Eisner and Mark Dredze. Before that, I worked at BBN Technologies. Fun facts: I grew up in England and Switzerland, speak French, and I'm an avid cyclist.

News / Highlights

  • [Funded summer opportunity] The 2022 SCALE summer research workshop will be on authorship analysis. If you are a researcher or student interested in modeling writing style, deep metric learning, uncertainty estimation, graph embeddings, or explainability for text models, please consider applying.
  • Paper on universal author embeddings with Aleem, Marcus, and colleages at Lawrence Livermore National Labs accepted to EMNLP 2021!
  • Paper with Aleem, Noah, Elizabeth, and Marcus accepted to NAACL 2021!
  • Paper with Steven and David accepted to EMNLP 2020!
  • Led the SCALE 2019 workshop on NER. With over 50 participants, this was the largest SCALE to date. Thanks everyone, especially the students!


  • Learning Universal Authorship Representations. EMNLP (2021)
    Rafael Rivera-Soto, Olivia Miano, Juanita Ordonez, Barry Chen, Aleem Khan, Marcus Bishop and Nicholas Andrews
  • A Deep Metric Learning Approach to Account Linking. NAACL (2021)
    Aleem Khan, Elizabeth Fleming, Noah Schofield, Marcus Bishop, Nicholas Andrews
    [aclweb] [arxiv] [code + data]
  • Ensemble Distillation for Structured Prediction: Calibrated, Accurate, Fast - Choose Three. EMNLP (2020)
    Steven Reich, David Mueller, Nicholas Andrews
    [aclweb] [arxiv] [code]
  • Sources of Transfer in Multilingual Named Entity Recognition. ACL (2020)
    David Mueller, Nicholas Andrews, Mark Dredze
    [aclweb] [paper] [bib] [arxiv] [video]
  • Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning. RepL4NLP (2020)
    Mitchell A Gordon, Kevin Duh, Nicholas Andrews
    [aclweb] [paper] [bib] [arxiv] [video]
  • Learning Invariant Representations of Social Media Users. EMNLP (2019)
    Nicholas Andrews and Marcus Bishop
    [aclweb] [arxiv] [code] [data] [video]
  • Convolutions Are All You Need (For Classifying Character Sequences). EMNLP WNUT (2018)
    Zach Wood-Doughty, Nicholas Andrews, and Mark Dredze
  • Predicting Twitter User Demographics from Names Alone. NAACL PEOPLES (2018)
    Zach Wood-Doughty, Nicholas Andrews, Rebecca Marvin, and Mark Dredze
  • Bayesian Modeling of Lexical Resources for Low-Resource Settings. ACL (2017)
    Nicholas Andrews, Mark Dredze, Benjamin Van Durme, and Jason Eisner
    [pdf] [code] [slides]
  • Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation.
    SocialNLP (2016)
    Mark Dredze, Nicholas Andrews and Jay DeYoung
  • Generative Non-Markov Models for Information Extraction. Dissertation (2015)
    Nicholas Andrews (advised by Jason Eisner and Mark Dredze)
  • Robust Entity Clustering via Phylogenetic Inference. ACL (2014)
    Nicholas Andrews, Jason Eisner, and Mark Dredze
    [pdf] [full paper] [bib] [code] [slides]
  • PARMA: A Predicate Argument Aligner. ACL (2013)
    Travis Wolfe, Benjamin Van Durme, Mark Dredze, Nicholas Andrews, Charley Beller, Chris Callison-Burch, Jay DeYoung, Justin Snyder, Jonathan Weese, Tan Xu, and Xuchen Yao
    [pdf] [bib]
  • Name Phylogeny: A Generative Model of String Variation. EMNLP (2012)
    Nicholas Andrews, Jason Eisner, and Mark Dredze
    [pdf] [bib]
  • Entity Clustering Across Languages. NAACL (2012)
    Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze,
    and Christopher D. Manning
    [pdf] [bib]
  • Transformation Process Priors. NeuIPS NP Bayes (2011)
    Nicholas Andrews and Jason Eisner
    [pdf] [bib]
  • Cross-lingual Coreference Resolution. TR (2011)
    Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze,
    and Christopher D. Manning
  • Seeded Discovery of Base Relations in Large Corpora. EMNLP (2008)
    Nicholas Andrews and Naren Ramakrishnan
    [pdf] [bib]
  • Recent Developments in Document Clustering. TR (2008)
    Nicholas Andrews and Edward A. Fox


  • NeurIPS (2015, 2017, 2018, 2019, 2021)
  • ICML (2015, 2016, 2017, 2018, 2020, 2021)
  • EMNLP (2015, 2016, 2017, 2019, 2020, 2021)
  • AISTATS (2017, 2018, 2019, 2020)
  • AAAI (2018, 2020, 2021)
  • NAACL (2013, 2016, 2021)
  • ACL (2017, 2018, 2020, 2021)
  • EACL (2017)
  • ICLR (2021)