Muhammad Izzatullah

PhD Candidate, King Abdullah University of Science and Technology (KAUST), Saudi Arabia

Crafting cutting-edge deep generative models and quantifying uncertainties in waveform imaging and inversion, and more.


I am a PhD candidate at KAUST in the Physical Science and Engineering division and affiliate with the Seismic Wave Analysis Group, Deep Imaging Group, and Extreme Computing Research Center.

I specialize in deep generative modelling, Bayesian inference and uncertainty quantification. My research contributions spanned across the fields of waveform imaging and inversion through the development of novel deep generative modelling approach and scalable Bayesian inference methods aimed at quantifying the uncertainties of subsurface imaging and inversion products. I am working closely under supervision of Tariq Alkhalifah and Matteo Ravasi.

I am also actively involve with philanthropist works, and I actively support cerebral palsy, autism, and cancer organisations in Malaysia and Russia.

Research Activities

Deep-learning for geophysical inverse problems

Precondition physics-driven inverse problems with non-linear dimensionality reduction networks.


Novel objective functions for full waveform inversion

Use of optimal transport and deep learning to increase the sensitivity of full-waveform inversion cost functions to target areas.



Machine Learning in Geoscience