Immunolinguistics

In the Immunolingo Environment, we are studying the adaptive immune system through the multidisciplinary lens of immunology, linguistics, machine learning, and statistics.

  • Mai Ha Vu, Rahmad Akbar, Philippe A. Robert, Bartlomiej Swiatczak, Geir Kjetil Sandve, Victor Greiff, and Dag Trygve Truslew Haug. Linguistically inspired roadmap for building biologically reliable protein language models. Nature Machine Intelligence, ISSN 2522-5839. [doi] [arXiv] [preprint pdf]
  • Philippe A. Robert, Rahmad Akbar, Robert Frank, Milena Pavlović, Michael Widrich, Igor Snapkov, Andrei Slabodkin, Maria Chernigovskaya, Lonneke Scheffer, Eva Smorodina, Puneet Rawat, Brij Bhushan Mehta, Mai Ha Vu, Ingvild Frøberg Mathisen, Aurél Prósz, Krzysztof Abram, Alex Olar, Enkelejda Miho, Dag Trygve Tryslew Haug, Fridtjof Lund-Johansen, Sepp Hochreiter, Ingrid Hobæk Haff, Günter Klambauer, Geir Kjetil Sandve, and Victor Greiff. Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. Nature Computational Science, 2(12):845- 865. ISSN 2662-8457. [doi]
  • Mai Ha Vu, Philippe A. Robert, Rahmad Akbar, Bartlomiej Swiatczak, Geir Kjetil Sandve, Dag Trygve Truslew Haug, and Victor Greiff. 2022. Immunolingo: Linguistics-based formalization of the antibody language. ArXiv preprint [arXiv] [pdf]
  • Rahmad Akbar, Habib Bashour, Puneet Rawat, Philippe A. Robert, Eva Smorodina, Tudor-Stefan Cotet, Karine Flem-Karlsen, Robert Frank, Brij Bhushan Mehta, Mai Ha Vu, Talip Zengin, Jose Gutierrez-Marcos, Fridtjof Lund-Johansen, Jan Terje Andersen, and Victor Greiff (2022). Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies., mAbs, 14:1 [doi] [pdf]


Computational characterization of the syntax-prosody interface

In collaboration with Dr. Aniello De Santo and Dr. Hossep Dolatian, we study syntax-prosody mapping with mathematical linguistic tools, such as logical transductions. Our work on ditransitive typology highlights the parts of the syntax-prosody interface that so far are underspcified and require further empirical study.

  • Mai Ha Vu, Aniello De Santo, and Hossep Dolatian (2022). Logical Transductions for the Typology of Ditransitive Prosody. In Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, pages 29-38, Seattle, Washington. Association for Computational Linguistics. [html] [pdf]
  • Mai Ha Vu, Aniello De Santo, and Hossep Dolatian (2022). Logical Transductions for the Typology of Ditransitive Prosody. Presentation at the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, Seattle, Washington. Association for Computational Linguistics. [slides]


NPI licensing and deep neural language models

In collaboration with Dr. So Young Lee, we investigate how well pre-trained language models such as BERT fare in learning NPI licensing constraints. We are especially interested in whether language models exhibit the same psycholinguistic behavior such as grammatical illusion effects (as found in Xiang et al. (2009) for humans) and in whether language models are capable of learning cross-linguistic NPI licensing constraints.

  • Mai Ha Vu and So Young Lee (2022). Comparing neural-network based language models to human sentence processing: choice of task matters. Poster presentation at Human Sentence Processing, San Diego, CA [abstract] [slides]


A Computational Characterization of Negative Polarity Items

In my dissertation, I investigate the nature of NPI-licensing and Negative Concord Items. My work aims to give an empirically and computationally informed characterization that can account for typological differences. The typological study includes deeper studies of English and Hungarian, but also touches on other languages in the literature through the lens of a quantifier-based theory, as advocated for by Dr. Anastasia Giannakidou. For the computational part of the work, I aim to determine the necessary computational complexity of these dependencies, in particular, whether they can fit in the subregular region of the Chomsky-hierarchy. This computational work draws heavily on Dr. Jeffrey Heinz's and Dr. Thomas Graf's work.

  • Mai Ha Vu (2018). Towards a formal description of NPI-licensing patterns. Proceedings of the Society for Computation in Linguistics 1(17) [pdf]
  • Mai Ha Vu (2018). Towards a formal description of NPI-licensing patterns. Poster presentation at the Society of Computation in Linguistics, Salt Lake City, UT [pdf]
  • Mai Ha Vu, Nazila Shafiei, and Thomas Graf (2019). Case assignment in TSL syntax: a case study. Proceedings of the Society for Computation in Linguistics 2(28) [pdf]
  • Mai Ha Vu, Nazila Shafiei, and Thomas Graf (2019). Case assignment in TSL syntax: a case study. Poster presentation at the Society of Computation in Linguistics, New York City, NY [pdf]
  • Mai Ha Vu (2019). Quantificational force of Hungarian NPIs: evidence from adverbial scope. Poster presentation at the Linguistic Society of America Annual Meeting, New York City, NY [pdf]
  • Mai Ha Vu (2019). A quantifier-based approach to NPI-licensing typology: Empirical and computational investigations. PhD defense presentation. [pdf]
  • Mai Ha Vu (2019). A quantifier-based approach to NPI-licensing typology: Empirical and computational investigations. University of Delaware PhD thesis. [pdf]


Grounded Early Adaptive Rehabilitation (GEAR)

This is a collaboration between John Hopkins University, the Cooperative Robotics Lab and the Pediatric Mobility Lab & Design Studio at University of Delaware, and Dr. Jeffrey Heinz and his students at the Lingusitics Departments at University of Delaware and Stony Brook University to develop a socially interactive robot capable of learning from its experiences and modifying its behavior to improve physical therapy outcomes for young children with motor disabilities (e.g., Downs Syndrome). We are currently testing different robot behaviors in a controlled physical therapy environment that includes multiple play stations monitored by video and infrared cameras. In parallel, we are evaluating and developing machine learning algorithms informed by existing work in computational linguistics, and applying it to robot learning. This research is supported by the National Institutes of Health grant 1R01HD087133-01.

  • Mai Ha Vu, Ashkan Zehfroosh, Kristina Strother-Garcia, Michael Sebok, Jeffrey Heinz, and Herbert G. Tanner (2018). Statistical relational learning with unconventional string models. Frontiers in Robotics and AI 5, 76 [html]


WH-questions and additives in Finnish, Hungarian, and English

In collaboration with Dr. Karoliina Lohiniva, we are investigating a series of questions related to multiple wh-questions and additives comparing Finnish, Hungarian, and English. In the core, we use Kotek's framework of Q particles to analyze the syntax and semantics of multiple wh-questions in these languages with and without additives. The questions we seek to answer are: What does the additive particle do in Finnish and Hungarian wh-questions, syntactically, semantically, and pragmatically? What are possible meanings and combinations of wh-, d-linked wh-, and aggressively non-d-linked wh-words in multiple wh-questions?

  • Mai Ha Vu and Karoliina Lohiniva (2018). In-situ Hungarian wh-hell: evidence against an intervention account. Poster presentation at the 28th Colloquium of Generative Grammar, Tarragona, Spain [pdf]
  • Mai Ha Vu and Karoliina Lohiniva (2018). In situ wh-hell: The view from Hungarian. Poster presentation at the 49th Annual Meeting of the Northeast Linguistic Society, Ithaca, NY [pdf]
  • Mai Ha Vu and Karoliina Lohiniva (2019). In situ wh-hell: The view from Hungarian. In M. Baird and J. Pesetsky (Eds.), NELS 49: Proceedings of the Forty-Ninth Annual Meeting of the North East Linguistic Society: Volume 3, Amherst, MA, pp. 275 – 284. GLSA [pdf]


Causativization in Hungarian

In collaboration with Jinwoo Jo, we are investigating the nature and typology of the productive causative morpheme in Hungarian, Japanese, and Korean. We argue contrary to Horvath and Siloni's (2011) split-lexicalist theory, and claim that this type of causativization is always syntactic: it occupies a head position of CauseP. We extend Pylkannen's (2008) typology by proposing that Hungarian causatives select for active VoiceP, Korean select for VoiceP, and Japanese select for TP.

  • Jinwoo Jo and Mai Ha Vu (2017). Typology of morphological causatives: A syntactic account. Poster presentation at the 19th Seoul International Conference on Generative Grammar, Seoul, Korea [pdf]
  • Jinwoo Jo and Mai Ha Vu (2017). A syntactic account of morphological causatives in Japanese and Korean. Poster presentation at the 25th Japanese/Korean Linguistics Conference, Honolulu, HI [pdf]
  • Jinwoo Jo and Mai Ha Vu (2018). A syntactic account of morphological causatives in Japanese and Korean. In M. S. K. Shin Fukuda and M.-J. Park (Eds.), Proceedings of the 25th Japanese/Korean Linguistics Conference, Poster Papers. CSLI Publications [pdf]


Hungarian Negation

This project investigates three different negative word orders in Hungarian declarative sentences: pre-verbal negation, focus negation, and verbal particle+verb negation. Pre-verbal negation and focus negation have both been analyzed as NegP projecting over the clause in the literature. I argue that focus negation patterns with verbal particle+verb in that they are both are actually constituent negation. I base my argument on coordination facts, where focus negation behaves similar to constituent negation in English, and Klima's (1964) tests. I hypothesize that constituent negation has to always be focused in languages that have constituent negation.

  • Mai Ha Vu (2017). Focus negation is constituent negation in Hungarian. Poster presentation at Linguistic Society of America Annual Meeting, Austin, TX [pdf]

A formal analysis of Correspondence Theory

In collaboration with Amanda Payne and Jeffrey Heinz, we evaluate the computational complexity of Correspondence Theory, which explicitly recognizes the correspondence between underlying and surface elements. We have three distinct results. First, we show that the GEN function, assuming Correspondence Theory, is not definable using Monadic Second Order logic (MSO). On the other hand, we show that the set of output candidates for a given input is in fact definable not only in MSO-logic, but we suspect it is doable in First-Order (FO) logic too. Lastly, we find that typical underlying representation (UR) to surface representation (SR) mappings can be directly described with FO logic without recourse to optimization.

  • Amanda Payne, Mai Ha Vu, and Jeffrey Heinz (2016). A formal analysis of Correspondence Theory. Poster presentation at the Annual Meeting of Phonology, Los Angeles, CA [pdf]
  • Amanda Payne, Mai Ha Vu, and Jeffrey Heinz (2017). A formal analysis of correspondence theory. In Proceedings of the Annual Meetings on Phonology, Volume 4. LSA [pdf]


Extreme Locality in Balinese Complex Sentences

In collaboration with Justin Rill, we investigated complex sentences in Balinese. Based on evidence from adverb positioning, we concluded that in Balinese what looks like simple argumetn raising is in fact remnant movement.

  • Justin Rill and Mai Ha Vu (2015). Extreme locality in Balinese complex sentences. Poster presentation at the Linguistic Society of America Annual Meeting, Portland, OR [pdf]