Antonio Stanziola


A smart, kind and curious being

and me.

I am currently a Research Fellow in Teorectical and Computational Acoustics at the 🐛 Biomedical Ultrasound Group of UCL. I am also member of the Maths4DL programme.

Previously, I was briefly a consultant at TTP in the Health Tech division, after being a Research Fellow at the Biomedical Ultrasound Group, working on Deep Learning for Transcranial Ultrasound Neurostimulation. I have a PhD in Biomedical Engineering, from Imperial College with a specialization in ultrasound vascular imaging and beamforming with contrast agents.

My experience is in various areas more or less related to ultrasound and deep learning, such as acoustics, ultrasound imaging and beamforming, signal processing, numerical methods. I also have background in differentiable programming, PDE modeling, deep learning for scientific computing, medical imaging and inverse problems, computer vision, and image analysis.

I also like dogs and my parent’s golden retriever Spritz.


Feb 13, 2024 I will be at the 2024 SIAM Conference on Imaging Science to talk about Differentiable acoustic simulators and their application beyond imaging!
Feb 16, 2023 The paper describing jwave is available on SoftwareX
Dec 9, 2022 Our latest two papers have been published on Arxiv. The first one proposed a Learned Born Series for fast simulation on high-scattering media, and the second one proposes and auto-diff based method for uncertainty quantification in transcranial ultrasound.

selected publications

  1. Physics-Based Acoustic Holograms
    Antonio StanziolaBen T. CoxBradley E. Treeby, and Michael D. Brown
  2. j-Wave: An open-source differentiable wave simulator
    Antonio StanziolaSimon R. ArridgeBen T. Cox, and Bradley E. Treeby
    SoftwareX 2023
  3. A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound
    Antonio StanziolaSimon R. ArridgeBen T. Cox, and Bradley E. Treeby
    Journal of Computational Physics 2021