Teaching and supervision

Courses taught by Saeed Salehi at Linköping University and Chalmers, PhD supervision, and pedagogical training.

Current courses at Linköping University

I am examiner, course coordinator and main teacher for two Master’s-level courses.

Applied Computational Fluid Dynamics

TMMV59 · 6 credits · Master’s level

Practical training in CFD for complex flow and heat transfer problems: the full workflow from modelling strategy, choice of physical models and numerical methods, and meshing to verification and validation. Students also learn to manage simulation projects, assess errors and uncertainties, automate workflows for high-performance computing, and communicate results. The course combines lectures, workshops, computer exercises and project work with input from industry.

Course page at LiU

Machine Learning for Mechanical Engineering

TMMV64 · 6 credits · Master’s level

Data-driven modelling and machine learning for mechanical engineering. Students process, analyse and visualise data from mechanical and energy systems and implement predictive and classification models in Python. Lectures and hands-on labs end in a project that applies the methods to a real engineering problem.

Course page at LiU

Other teaching

  • 2020 – presentCFD with OpenSource Software (7.5 ECTS), lecturer
    Chalmers University of Technology · PhD level
  • 2021 – presentBasic Usage of OpenFOAM (2 ECTS), lecturer
    Chalmers University of Technology · PhD level
  • 2022Introduction to fluid dynamics in water turbines (2 ECTS), main teacher and examiner
    Swedish Hydropower Centre (SVC) research school at KTH Royal Institute of Technology · PhD level
  • 2018 – 2019Introduction to Turbomachinery, main teacher and examiner
    University of Science and Culture, Tehran · Bachelor level
  • 2013 – 2017Teaching assistant in Turbomachinery Lab, Turbulent Flows, Heat Transfer and Fluid Mechanics
    University of Tehran · Bachelor and Master level

PhD supervision

  • From autumn 2026Doctoral student, Linköping University, principal supervisor
    Enabling flexible hydropower operation by AI-based active flow control (project page)
  • 2023 – presentMohammad Sheikholeslami, Chalmers University of Technology, co-supervisor
    Multi-fidelity physics-informed neural networks for solving partial differential equations
  • 2023 – 2025Martina Nobilo, Chalmers University of Technology, co-supervisor
    CFD for hydropower lifetime analysis. Licentiate degree, 2025.
  • 2020 – 2024Jonathan Fahlbeck, Chalmers University of Technology, co-supervisor
    Flow in contra-rotating pump-turbines at stationary, transient and cavitating conditions (EU Horizon 2020 project ALPHEUS). PhD, 2024.

I also supervise MSc and BSc thesis projects. See Opportunities for current proposals.

Pedagogical training

  • Diploma in Teaching and Learning in Higher Education (15 ECTS), Chalmers University of Technology, 2023. Designed to meet the learning outcomes of the Association of Swedish Higher Education Institutions (SUHF), including a final pedagogical project.
  • Supervising Research Students (3 ECTS), Chalmers University of Technology, 2022.
  • Higher Education Pedagogy for PhD Supervisors (4 credits), Linköping University, 2025.

In 2024 I presented CFD with OpenSource Software: a case study of project-based learning in an international PhD course at the Chalmers Conference on Teaching and Learning (KUL).