Mans Hulden
Also known as Måns Huldén
Mans Hulden is a computer scientist whose work connects finite-state language processing with machine learning and neural NLP. He earned a Ph.D. from the University of Arizona in 2009 and presented Foma, a finite-state compiler and library, at EACL in 2009. Before moving to Colorado in 2014, he did Marie Curie postdoctoral work in Helsinki and served as an Ikerbasque visiting professor; he later taught at Colorado before moving to New College in 2024. His work includes a 2018 neural analyzer for Arapaho verbs, PyFoma in 2024, and a 2026 method for inducing transducers from a recurrent neural network. As of October 2026, he is associate professor of computer science at New College of Florida.
- Now at
- New College of Florida
Timeline
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2009
A University of Arizona PhD
He earns a Ph.D. from the University of Arizona in 2009.
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2009
The Foma finite-state toolkit
At EACL in 2009, he presents Foma, a finite-state compiler and library. The toolkit supports natural language processing and research in automata theory.
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By 2014
Marie Curie and Ikerbasque posts
Before moving to the University of Colorado in 2014, he completes postdoctoral work at the University of Helsinki as a Marie Curie Fellow and serves as an Ikerbasque visiting professor in Computer Science at the University of the Basque Country.
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2014–2024
Associate professor at Colorado
In 2014, he moves to the University of Colorado Boulder. He serves as an associate professor of linguistics and a faculty fellow at the Institute of Cognitive Science, then teaches computational linguistics, phonetics, and phonology before his move to New College in 2024.
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2018
A neural analyzer for Arapaho verbs
In 2018, he and his coauthors train an encoder-decoder neural model to mimic an existing finite-state morphological grammar for Arapaho verbs. It generalizes to unseen forms with 98.68% accuracy for unambiguous verbs and 92.90% for all verbs.
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2024
The PyFoma Python toolkit
In 2024, he and three coauthors publish PyFoma, an open-source Python module for building weighted and unweighted finite-state transducers and automata from regular expressions and string rewriting rules. It includes algorithms for linguistic and NLP applications.
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2026
Neural induction of transducers
In 2026, he and coauthors publish a method that constructs unweighted finite-state transducers from the hidden state geometry learned by a recurrent neural network. They evaluate it on morphological inflection, grapheme-to-phoneme prediction, and historical normalization.
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As of October 2026
Associate professor at New College
He is Associate Professor of Computer Science in the Natural Sciences Division at New College of Florida. His research focuses on machine learning for natural language processing, finite automata, neural models for NLP and their interpretability, and neural models for low-resource learning.
Career
- NowNew College of FloridaAssociate Professor of Computer Science
- Until 2014University of HelsinkiMarie Curie Fellow
- Until 2014University of the Basque CountryVisiting Professor
- 2014–2024University of Colorado BoulderAssociate Professor of Linguistics
Education
- 2009University of ArizonaPhD
Sources and credits
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- Directory - New College of Florida
- Foma: a Finite-State Compiler and Library - ACL Anthology
- foma/foma/README at master · mhulden/foma · GitHub
- Mans Hulden - Wikipedia
- Mans Hulden
- A Neural Morphological Analyzer for Arapaho Verbs Learned from a Finite State Transducer - ACL Anthology
- PyFoma: a Python finite-state compiler module - ACL Anthology
- Neural Induction of Finite-State Transducers - ACL Anthology

