I am a machine learning researcher working across academic research and applied AI.
I’m interested in philosophy, knowledge representation, leadership, and politics.
Born and raised in Ethiopia, I lived in Cameroon and Turkey before moving to Kazakhstan. Along the way, I have learned five languages and worked with people across cultures and fields. More about me
Research
I currently work on scientific machine learning and its applications in computational fluid dynamics.
My published work focuses mainly on two-phase flow in porous media, including physics-informed models, training methods, and inverse modelling.
My personal interests, however, lie in knowledge representation, causality, and cognitive AI. I am still developing this research and have not yet published work on these questions.
Read about my researchWriting
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Open the writing archiveSelected publications
Coupled pressure and saturation prediction for two-phase flow in porous media using physics-informed neural networks (PINNs)
One physics-informed network trained on both the pressure and water-saturation equations got pressure right but misplaced the water front. Bigger networks and reweighting didn’t fix it; a small diffusion term with tuned weights did.
Computer Methods in Applied Mechanics and Engineering
Performance and stability of physics-informed Kolmogorov-Arnold networks for two-phase transport in porous media: A comparative study with physics-informed neural networks
Kolmogorov–Arnold networks promise accuracy with fewer parameters. On a sharp water front, ours used a third of the parameters but needed over twice the smoothing and about 50 times the training time.
Results in Engineering