Hey, I'm Yahya, an applied mathematician and research engineer. I have experience in building and analyzing machine learning models for scientific computing and engineering problems.

I am genuinely passionate about pushing the boundaries of what is machine computable. I developed a new spectral-learning framework for solving Schrödinger equations that describe vibrations of molecules and built software that eases the adoption of this framework in practical applications (not that the framework is widely adopted but getting there :v).

In more industrial applications, I've built test automation and data-fixture tooling for banking systems, prototyped AI-agent integrations with the Model Context Protocol (MCP), and worked on cloud deployment of machine learning models.

• Inducing Riesz Bases in L² via Composition Operators
  Y. Saleh, A. Iske · Complex Analysis and Operator Theory 20 (2026) · paper · arXiv
• Convergence theory for Hermite approximations under adaptive coordinate transformations
  Y. Saleh · arXiv preprint (2026) · arXiv
• Computing Excited States of Molecules Using Normalizing Flows
  Y. Saleh, Á. F. Corral, E. Vogt, A. Iske, J. Küpper, A. Yachmenev · Journal of Chemical Theory and Computation 21 (2025) · paper · arXiv
• Bounds on the Generalization Error in Active Learning
  V. Menden, Y. Saleh, A. Iske · Proceedings of the 6th Northern Lights Deep Learning Conference (NLDL) 265 (2025) · paper · arXiv
• Active learning of potential-energy surfaces of weakly bound complexes with regression-tree ensembles
  Y. Saleh, V. Sanjay, A. Iske, A. Yachmenev, J. Küpper · The Journal of Chemical Physics 155 (2021) · paper · code

• 2026 · Learning, sharing, and using optimized vibrational coordinates — ExoMol 2026, University College London, United Kingdom (invited)
• 2026 · Learning bases via normalizing flows, applications to solving molecular Schrödinger equations and image compression — International Conference on Scientific Computing and Machine Learning, Bath, United Kingdom
• 2025 · Normalizing flows: from learning probability distributions to basis-set discovery — Linköping University, Sweden (invited)
• 2025 · Learning basis sets using unitary and bounded bijective operators — International Conference in Numerical Mathematics and Scientific Computing, Uppsala University, Sweden
• 2025 · Bounds on the generalization error in active learning — 6th Northern Lights Deep Learning Conference (NLDL), Tromsø, Norway (poster)

20 talks and posters in total, 6 of them invited — full list.

_{This profile is generated from the same data as my website and CV.}