Jonah Casebeer

I am a Research Scientist at Adobe Research, and am interested in machine learning for audio (or other) signal processing. I earned a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign, where I was advised by Prof. Paris Smaragdis. My thesis was on adaptive filtering and proposed a new paradigm called meta-adaptive filtering. I also did my B.S. at the University of Illinois Urbana-Champaign in Statistics and Computer Science. Feel free to check out my publications page or my Google Scholar to see what I’ve been up to lately.

I am enthusiastic about collaborating with students through research internships at Adobe Research in San Francisco. The internship program spans 3-4 months during the summer. If you are passionate about applying machine learning, deep learning, or signal processing to audio, I encourage you to get in touch. Please send me your CV along with a brief explanation of your research interests. My Adobe page is here.

news

Mar, 2024 My Ph.D. thesis is now available here.
Nov, 2023 I’m helping organize the Hands-free Speech Communication and Microphone Arrays (HSCMA) workshop at ICASSP! Website here.
Nov, 2023 I’ve joined the Audio Research team at Adobe Research!
Oct, 2023 I’ve successfully defended my Ph.D. thesis on meta-learning for adaptive filtering!
Nov, 2022 I’ll be giving a talk at the Stanford CCRMA DSP Seminar on 11/18/2022! Details here.

selected publications

  1. Scaling Up Adaptive Filter Optimizers
    Casebeer, Jonah, Bryan, Nicholas J, and Smaragdis, Paris
    arXiv preprint arXiv:2403.00977 2024
    arXiv Code Website
  2. Meta-AF: Meta-Learning for Adaptive Filters
    Casebeer, Jonah, Bryan, Nicholas J, and Smaragdis, Paris
    IEEE/ACM Transactions on Audio, Speech, and Language Processing 2023
    arXiv Code Website
  3. Meta-Learning for Adaptive Filters with Higher-Order Frequency Dependencies
    Wu, Junkai, Casebeer, Jonah, Bryan, Nicholas J., and Smaragdis, Paris
    In IEEE International Workshop on Acoustic Signal Enhancement (IWAENC) 2022
    arXiv Code Website
  4. Auto-DSP: Learning to Optimize Acoustic Echo Cancellers
    Casebeer, Jonah, Bryan, Nicholas J, and Smaragdis, Paris
    In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 2021
    arXiv Code Website
  5. Enhancing Into the Codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders
    Casebeer, Jonah, Vale, Vinjai, Isik, Umut, Valin, Jean-Marc, Giri, Ritwik, and Krishnaswamy, Arvindh
    In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2021
    arXiv
  6. Deep Tensor Factorization for Spatially-Aware Scene Decomposition
    Casebeer, Jonah, Colomb, Michael, and Smaragdis, Paris
    In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 2019
    arXiv Website