About me

I am a 4th year undergraduate student at Johns Hopkins University. I major in Computer Science, Cognitive Science (linguistics focus), and Applied Mathematics (statistics focus). I'm intereted in using computational methods to model and potentially discover cognitive processes.

My research interests: Natural Language Processing, Computational Sociolinguistics, Multilingual/Cross-lingual NLP, Low-Resource Machine Translation, Human-Centered NLP, Ethical NLP

I am in the process of applying to post-bac and PhD programs. Please contact me at sli136@jhu.edu if you are interested in my work!

  • Click here to download my CV (updated Nov. 22)

     
  • Current Projects

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      Multilingual L2 Translation

      We develop a multilingual translation system from "broken" source language to target languages to investigate the differences between human language acquisition and machine language acquisition.

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      Speech to Sign Language

      We attempt to trian a distillation model conditioned on speech signals to translate speech to animated ASL sign language.

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      Quantum Language Modeling

      We integrate VQCs into a lite Transformer architecture for fast and secure language model pre-training. We currently only simulate quantum models on classical hardware.

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      Language-Agnostic Acoustic Modeling

      We investigate cross-lingual generalizability of English SSL models and perform phonology-semantic separation for language-agnostic acoustic modeling.

    News

    1. 11/14/2022

      Check out our new paper "Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns."

    2. 10/21/2022

      Check out our new paper "A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters."

    3. 10/07/2022

      Check out our new paper "PQLM - Multilingual Decentralized Portable Quantum Language Model for Privacy Protection."

    4. 09/26/2022

      Check out our new paper "End-to-End Lyrics Recognition with Self-supervised Learning."

    5. 07/09/2022

      Best Presentation Award at the GI Workshop @ GECCO 2022. Link to my talk here.

    6. 04/25/2022

      Check out our workshop paper "Genetic improvement in the shackleton framework for optimizing LLVM pass sequences" accepted to GECCO'22.

    7. 03/24/2022

      Check out our paper "Optimizing LLVM Pass Sequences with Shackleton: A Linear Genetic Programming Framework" accepted to GECCO'22.

    Experience

  • Click here to download my CV (updated Nov. 22)

     
  • Education

    1. Johns Hopkins University

      2019 — 2023 | Baltimore, MD

      B.S. in Computer Science

      Advised by Philipp Koehn and Kenton Murray.

      Thesis: Learning from Gibberish: Code-Mixing Data Augmentation for Sentiment Analysis

      Other Majors: Cognitive Science (linguistics focus), Applied Mathematics (statistics focus)

      Minor: Mathematics

      Cumulative GPA: 3.99/4.0, Major GPA: 4.0/4.0

    2. Stanford Online High School

      2018 — 2019 | Palo Alto, CA

      Dual enrollment program with a focus in advanced mathematics

      GPA (unweighted): 4.0/4.0

    3. Robert Louis Stevenson School

      2016 — 2019 | Pebble Beach, CA

      Awards & Leadership: Cum Laude Society, USABO Semifinalist, USAMO Qualified, Bausch & Lomb National Science Award, Math Madness Silver Medalist, Math Team Captain, Spanish National Honor Society, Varsity Volleyball

      GPA (unweighted): 3.98/4.0

    Teaching/TA Experience

    1. Human-Computer Interaction: Course Assistant

      2022 Fall

      EN.601.490 (undergrad) & EN.601.690 (grad)

    2. Computer Ethics: Head Course Assistant

      2022 Summer

      EN.601.104

    3. Introduction to Statistics: Teaching Assistant

      2020 Spring, 2021 Fall, 2022 Spring

      EN.503.430 (undergrad) & EN.503.630 (grad) & EN.503.431 (honors)

    4. Intermediate Programming: Course Assistant

      2020 Spring, 2021 Fall, 2022 Spring

      EN.601.220

    Work Experience

    1. Yext: Software Engineering Intern

      2022 Summer | Arlington, VA

      Integrated client data to Yext platform for real-time site information updates using Go.

      Created a Figma Style Picker to improve developer workflow and scalability using ReactJS.

    2. Michigan State University: Research Intern

      2021 Summer | East Lansing, MI

      Advised by Wolfgang Banzhaf.

      Designed and implemented novel GP algorithm for LLVM compiler flag optimization (20%).

      Published work at GECCO; second author of GP paper; first author of GI paper.

    3. Bytedance AI Lab: Research Intern

      2020 Summer | Beijing, China

      Trained neural networks for text normalization in text-to-speech tasks.

      Implemented statistical information-retrieval algorithms for theme clustering and complexity ranking for TikTok videos.

    4. Johns Hopkins Language and Cognition Lab: Research Assistant

      2020 - 2022 | Baltimore, MD

      Advised by Barbara Landau.

      Investigated developmental spatial cognition using Lego Block building.

      Created ML model for movement prediction and stability analysis using motion sensor data.

    5. IBM AI Doctor: Data Science Intern

      2019 Summer | Beijing, China

      Created ML models to predict diseases diagnosis from symptoms using EHR records.

      Improved classification accuracy from 74% to 99% with a hybrid algorithm of GA with SVM.

    Publications

    Photography

    Contact

    I am in the process of applying to post-bac and PhD programs in ML/NLP.

    Please contact me at sli136@jhu.edu if you have open positions or if you are interested in my work!