Shailee Jain

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Hi there! I am a {fifth/final} year CS PhD candidate at the Huth Lab at UT Austin working at the intersection of machine learning, computational neuroscience and NLP. My research focuses on jointly interpreting how systems like the human brain and neural NLP models process language, and is currently supported by the Dingwall Foundations of Language fellowship. During my PhD, I have also collaborated with researchers at Google AI Language and Intel Brain-Inspired Computing Lab.

Before arriving at UT, I did my undergrad at NITK, Surathkal and spent some time with the ML group at Leuphana University, Germany. My Bachelor’s thesis was on discovering cognitive learning patterns through web-user data. I also did a minor thesis on CNNs for visual saliency.

I can most effectively be contacted through email (shailee at cs.utexas.edu). I also tweet sometimes (working on it!) (well, I guess it’s mastodon now). You can find my CV here.

Recent News

Publications

(*equal contribution)

  1. Semantic reconstruction of continuous language from non-invasive brain recordings
    J. Tang, A. LeBel, S. Jain and A. G. Huth
    Nature Neuroscience (to appear) [PDF]
  2. Computational language modeling and the promise of in silico experimentation
    S. Jain, V. A. Vo, L. Wehbe and A. G. Huth
    Neurobiology of Language 2022 (to appear)
  3. Self-supervised models of audio effectively explain human cortical responses to speech
    A. Vaidya, S. Jain and A. G. Huth
    International Conference on Machine Learning (ICML) 2022 [PDF]
  4. Voxelwise encoding models show that cerebellar language representations are highly conceptual
    A. LeBel, S. Jain and A. G. Huth
    Journal of Neuroscience 2021 [PDF]
  5. Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech
    S. Jain, V. A. Vo, S. Mahto, A. LeBel, J. S. Turek and A. G. Huth
    Advances in Neural Information Processing Systems (NeurIPS) 2020 [PDF]
  6. Approximating stacked and bidirectional recurrent architectures with the delayed recurrent neural network
    J. S. Turek, S. Jain, V. A. Vo, M. Capota, A. G. Huth and T. L. Willke
    Proceedings of the 37th International Conference on Machine Learning (ICML) 2020 [PDF]
  7. Incorporating context into language encoding models for fMRI
    S. Jain and A. G. Huth
    Advances in Neural Information Processing Systems (NeurIPS) 2018 [PDF] [Video] [Poster]
  8. Spatial language representation with multi-Level geocoding
    S. Kulkarni*, S. Jain*, M. J. Hosseini, J. Baldridge, E. Ie and L. Zhang
    Second International Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics (SpLU-RoboNLP) @ACL-IJCNLP 2021 [PDF]
  9. Mining user trajectories in electronic text books
    A. Boubekki, S. Jain and U. Brefeld
    Proceedings of the Eleventh Annual International Conference on Educational Data Mining (EDM) 2018 [PDF]

Manuscripts in submission and preparation

(*equal contribution)

  1. A natural language fMRI dataset with voxelwise encoding models
    A. LeBel, L. Wagner, S. Jain, A. Adhikari-Desai, B. Gupta, A. Morgenthal, J. Tang, L. Xu and A. G. Huth (in revision) [PDF]
  2. A unifying computational account of temporal processing in natural speech across cortex
    V. A. Vo*, S. Jain*, N. M. Beckage, H. S. Chien, C. Obinwa and A. G. Huth (in preparation)
  3. Discovering distinct patterns of semantic integration across cortex using natural language encoding models for fMRI
    S. Jain and A. G. Huth (in preparation)

Conference Abstracts

  1. Mapping the timescales of language representations in the cerebellum
    LeBel, A., S. Jain, Ivry, R. and A. G. Huth
    Society for the Neurobiology of Language (SNL) 2022
  2. Semantic reconstruction of continuous language from non-invasive brain recordings
    J. Tang, A. LeBel, S. Jain and A. G. Huth
    Society for the Neurobiology of Language (SNL) 2022
  3. Discovering distinct patterns of semantic integration across cortex using natural language encoding models for fMRI
    S. Jain and A. G. Huth [Best poster award]
    Combinatorics, Leipzig Lectures on Language 2021
  4. A unifying computational account of temporal processing in natural speech across cortex
    S. Jain, V. A. Vo, N. M. Beckage, H. S. Chien, C. Obinwa and A. G. Huth
    Society for the Neurobiology of Language (SNL) 2021
  5. Uncovering compositional semantics in fMRI language encoding with transformers
    S. Jain, A. LeBel and A. G. Huth
    From Neuroscience to Artificially Intelligent Systems (NAISyS), CSHL 2020
  6. Natural language encoding models for fMRI reveal distinct patterns of semantic integration across cortex
    S. Jain, A. LeBel and A. G. Huth
    Society for the Neurobiology of Language (SNL) 2020
  7. Contextualized Language Information Yields Massive Improvements in Encoding Models for Human fMRI
    S. Jain and A. G. Huth
    Asilomar 2019
  8. Improving language encoding for fMRI with transformers
    S. Jain, A. LeBel and A. G. Huth
    Society for Neuroscience (SfN) 2019
  9. Voxelwise encoding models of the cerebellum during natural speech processing
    A. LeBel, S. Jain and A. G. Huth
    Society for Neuroscience (SfN) 2019
  10. Phonological feature and pitch classification with a branched convolutional neural network
    I. M. Griffith, A. LeBel, S. Jain, A. G. Huth, and L. S. Hamilton
    Society for Neuroscience (SfN) 2019 and Advances and Perspectives in Auditory Neuroscience (APAN) 2019

Teaching

  1. CS 342 Neural Networks with Dr. Alex Huth - TA + Guest lecturer
    • Recurrent Neural Networks
    • Language Models [Slides]
  2. NSC 110H Mapping the human cortex with Dr. Alex Huth - Guest lecturer
    • Temporal organization of language in the brain [Slides]

Service

  1. NeurIPS, ICLR, ICML - Reviewer
  2. How Can Findings About The Brain Improve AI Systems? @ICLR - Workshop Organizer (2021)
  3. Context & Compositionality in Biological and Artificial Neural Systems @NeurIPS - Workshop Organizer (2019)
  4. Women In Computer Science (WiCS) @UT Austin - Graduate Mentor (2019, 2020)

In the Press