Scientific Machine Learning Researcher

Anas Jnini

Scientific Machine Learning researcher working on physics-informed neural networks, neural operators, optimization, and computational fluid dynamics.

About

I work in scientific machine learning, with a focus on physics-informed neural networks, neural operators, optimization, and computational fluid dynamics. My research aims to develop accurate, stable, and scalable learning methods for physics-based systems.

Education

  • PhD in Industrial Innovation, cum laude — University of Trento, 2026
  • Master’s degree in Mechanical Engineering, Automation and Control — EPFL, 2021
  • Bachelor’s degree in Mechanical Engineering — EPFL, 2018

Research Interests

Scientific Machine Learning
Physics-Informed Neural Networks
Neural Operators
Computational Fluid Dynamics
Optimization Algorithms
High-Performance Computing
Surrogate Modeling
Scientific Computing

Publications & Preprints

Workshop Papers & Related Outputs

Industry Experience

  • Leonardo Labs — Visiting Researcher, 2025
  • Akkodis — Aerospace Engineer, 2022
  • ATR Aircraft — Aerospace Simulation Engineer Intern, 2020

Talks & Activities

  • Speaker at PINN-PAD: Physics Informed Neural Networks in Padova
  • Poster presentation at MSML 2025
  • Poster presentation at NeurIPS 2024 Workshop ML4PS
  • Poster presentation at ICLR 2024 Workshop on AI for Differential Equations
  • Research talks and workshop presentations in scientific machine learning and CFD

Contact

Email: anas.jnini@gmail.com

GitHub: github.com/anasjnini

Google Scholar: Profile