Jongin Kim

PhD in Computer Science, Boston University
Curriculum Vitae

Jongin Kim

I am a first-year PhD student in Computer Science at Boston University, where I am advised by Prof. Derry Wijaya.

My research interest is Multilingual/Crosslingual NLP.
My goal is to develop NLP systems that work well across different languages, so that langauge technologies are easily accessible to diverse and/or disadvantaged users who may need them most.

I have done some research towards this research direction. (publications)
Also, I plan to further broaden my research topics in the future while I pursue my Ph.D. !



Future Research Directions

  1. Efficient Way of Building Dataset for Low-Resource languages
    • Ways to efficiently build monolingual labeled dataset for low-resource languages
      (Particularly, data that contain knowledge that cannot be transferred from other high-resoure languages)
      • Active Learning, Human-in-the-loop machine learning
  2. Ways to efficiently crowdsource/collect Parallel texts
    (for Multilingual Neural Machine Translation)
    • Annotation using Image or GIFs as pivots
    • Collect Parallel(Comparable) texts from Web and Filter out noise
  3. Multilingual Benchmark Datasets that enable more comprehensive evaluation of Multilingual Models
    • Inclusion of typologically diverse languages
    • Inclusion of more challenging NLU/NLG tasks
  4. Novel Methods for Pre-Training Multilingual Language Models for more accurate alignment accross different languages (for better multilingual representations)
    • Multilingual subword tokenizer
    • Encourage explicit attention between languages
    • Augmenting the model with linguistic knowledge
      (= incorporating linguistic knowledge into the model)
  5. Explore Ways to improve Cross-Lingual Transfer Learning
    • Improving zero-shot cross-lingual transfer (Direct Model Transfer)
      • Intermediate task training
    • Overcoming Word Order Difference
    • Annotation Projection
  6. Applying Cross-Lingual Transfer Learning to Other Tasks
    (Would like to explore ways to apply Cross-lingual Transfer Learning to more challenging Tasks)
    • Crossingual IR, including QA, Text Summarization
  7. Multilingual Neural Machine Translation

Copyright © Jongin Kim 2021
Last updated December 20 2021