Farzaneh Tatari

Control Software Architect · Stellantis · AI/ML for vehicle software · Ph.D., Michigan State University

prof_pic.jpg

Michigan, USA

I’m an AI-driven Control Engineer and Researcher with 10+ years of experience integrating machine learning, reinforcement learning, and control theory for real-world applications in automotive, robotics, and research environments.

In August 2026, I’m joining Stellantis as a Control Software Architect, focusing on integrating AI into vehicle software development.

Most recently (April 2023 – August 2026), I was a Senior Control & AI Engineer at Drive System Design in Farmington Hills, MI, where I led control-system design and data-driven virtual-sensor development for electrified powertrains and managed interdisciplinary engineering teams across the US and Europe.

Previously, I completed my Ph.D. in Mechanical Engineering (Control) at Michigan State University, researching stochastic and deterministic finite-time learning systems under NSF and ONR funding. Before that, I was a postdoctoral researcher at the KIOS Center of Excellence, University of Cyprus, and an Assistant Professor of Control Systems at Semnan University, Iran.

Research interests

  • Safe reinforcement learning and hybrid RL–MPC control for autonomous vehicles
  • System identification with finite-time and fixed-time convergence guarantees
  • Data-driven modeling of electric motors and powertrains (thermal, condition monitoring)
  • Multi-agent systems, cooperative control, and distributed learning
  • Vehicle dynamics and connected-and-automated-vehicle (CAV) control
  • AI/ML for the automotive industry — production-ready ML pipelines, virtual sensors, embedded deployment
  • Integrating AI into vehicle software development — bringing modern ML tooling and workflows into automotive SW processes

Selected recognition

  • Fitch Beach Medal for Outstanding Graduate Research, Michigan State University, 2023
  • GOF and DCF Fellowships, MSU (2022–2023)
  • Guest Associate Editor, Frontiers in Control Engineering
  • Reviewer for Automatica, IEEE TNNLS, and other control/ML journals

Full publication list on Google Scholar. Code and open-source projects on GitHub.

latest posts

Sep 13, 2026 Three ways to combine RL and MPC, and what each actually guarantees
Aug 21, 2026 From DDPG to SAC: a lineage of fixes

selected publications

  1. arXiv
    A Hybrid End-to-End and Modular Control Architecture Toward Safe Vehicle Lateral Control: Combining Soft Actor-Critic with Model Predictive Control
    Farzaneh Tatari
    2026
    HTML
  2. GVSETS
    Deep Learning-Based Rotor Temperature Estimation for Rare-Earth-Free Motors
    Farzaneh Tatari and M. M. Aligoudarzi
    In NDIA Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), 2026
    HTML
  3. IEEE T-SMC
    Online Learning of Noisy Functions via a Data-Regularized Gradient-Descent Approach
    Farzaneh Tatari, Reza Esmzad, and Hamidreza Modares
    IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2025
    HTML
  4. IEEE ITEC
    Data-driven Thermal Modeling for Electrically Excited Synchronous Motors—A Supervised Machine Learning Approach
    Farzaneh Tatari, D. Trapp, J. Schneider, and 1 more author
    In IEEE Transportation Electrification Conference & Expo (ITEC), 2024
    HTML
  5. IEEE TNNLS
    Fixed-Time System Identification Using Concurrent Learning
    Farzaneh Tatari, Kyriakos G. Vamvoudakis, and Majid Mazouchi
    IEEE Transactions on Neural Networks and Learning Systems, 2021