Noel Elias

ML @ Otter.ai


About Me

I am currently a Machine Learning Engineer at Otter.ai. I graduated from the University of Texas at Austin with a double major in Computer Science and Mathematics. During my time at UT, I was fortunate to be advised by Dr. Sriram Vishwanath and Dr. David Wu. My research interests lie in theoretical computer science, particularly cryptography and quantum computing.

Previously, I was a Software Engineering Intern at Apple, a Machine Learning Intern at the Applied Research Laboratories, and a Software Developer at Thinkery.

Feel free to reach out using the contact information below!



Publications | Projects


COVID-19 Dashboard

A neural network based web-app prediction model

    2025

  1. MultiTok: Variable-Length Tokenization for Efficient LLMs Adapted from LZW Compression
    Noel Elias, Homa Esfahanizadeh, Kaan Kale, Sriram Vishwanath, Muriel Medard
    Submitted to IEEE International Symposium on Information Theory (ISIT) 2026
    [PDF] | [Code]

  2. Pairing-Based Batch Arguments for NP with a Linear-Size CRS
    Binyi Chen, Noel Elias, David Wu
    International Conference on the Theory and Application of Cryptology and Information Security (ASIACRYPT) 2025
    [PDF]

  3. Lova: A Novel Framework for Verifying Mathematical Proofs with Incrementally Verifiable Computation
    Noel Elias
    Conference on Data and Application Security and Privacy (CODASPY) 2025
    CIFRIS: Topics in Applied Cryptography 2024
    [PDF] | [Code]

  4. 2024

  5. TexShape: Information Theoretic Sentence Embedding for Language Models
    Kaan Kale, Homa Esfahanizadeh, Noel Elias, Oguzhan Baser, Muriel Medard, Sriram Vishwanath
    IEEE International Symposium on Information Theory (ISIT) 2024
    [PDF] | [Code]

  6. 2023

  7. A Novel Score-CAM based Denoiser for Spectrographic Signature Extraction without Ground Truth
    Noel Elias
    IEEE International Joint Conference on Neural Networks (IJCNN) 2023
    [PDF]

  8. 2022

  9. Audio Classification of Low Feature Spectrograms Utilizing Convolutional Neural Networks
    Noel Elias
    IEEE International Conference on Machine Learning and Applications (ICMLA) 2022
    [PDF]

  10. 2020

  11. Robust Estimation of Bacterial Cell Count from Optical Density
    Jacob Beal, Natalie G. Farny, Traci Haddock-Angelli, Vinoo Selvarajah, Geoff S. Baldwin, Russell Buckley-Taylor, Markus Gershater, Daisuke Kiga, John Marken, Vishal Sanchania, Abigail Sison, Christopher T. Workman & iGEM Interlab Study Contributors
    Nature Communications Journal 2020
    [PDF]



Updated

© Noel Elias 2021