CV

Control Software Architect

Stellantis

Software architecture for electrified propulsion systems.

Guest Associate Editor

Frontiers in Control Engineering

Guest Associate Editor. Reviewer for Automatica, IEEE Transactions on Neural Networks and Learning Systems, and other journals.

Senior Control & AI Engineer

Drive System Design

• Designed, implemented, and validated embedded control systems for electrified powertrains across MIL, SIL, HIL, and vehicle-level testing.
• Developed data-driven CAE models using supervised machine learning and deep learning for thermal estimation in electrically excited and rare-earth-free synchronous motors, enabling reduced sensor count and improved energy management in production powertrain controllers.
• Technical lead of a team of 8 engineers across the US and North Africa, automating systems engineering analysis of diagnostic default-action disclosure reports for production embedded software.
• Managed a team of 4 engineers across the US and UK developing embedded control and diagnostic software for production powertrain controllers.
• Designed automation pipelines in MATLAB/Simulink that reduced controls software analysis and report-generation time.
• Partnered with OEM and supplier customers on production-ready embedded controls software, diagnostics, and validation deliverables.
• Collaborated on Design Failure Mode and Effects Analysis (DFMEA) for powertrain control systems in support of safety-related design analyses.

Research Assistant (Ph.D.)

Michigan State University

• Conducted NSF- and ONR-funded research on stochastic and deterministic learning systems, focusing on finite-time system identification and online learning under uncertainty.
• Developed algorithms for data-regularized concurrent learning and adaptive control with formal convergence guarantees, validated on vehicle and robotic dynamics case studies.
• Published several IEEE journal papers on learning-based control, system identification, and stability analysis of dynamic systems.

Postdoctoral Researcher

KIOS Center of Excellence, University of Cyprus

• Designed finite-time distributed learning and estimation algorithms for nonlinear interconnected systems, with relevance to multi-subsystem powertrain and energy networks.
• Collaborated with multi-disciplinary teams on cyber-physical system modeling, networked control, and robust estimation.

Assistant Professor, Control Systems

Semnan University

• Led research on distributed optimal and adaptive control of multi-agent networked systems using reinforcement learning and game theory.
• Taught modern, nonlinear, and optimal control; supervised graduate research in control of complex dynamic systems.

Ph.D.

Michigan State University

Mechanical Engineering (Control)

• Dissertation: Stochastic and Deterministic Finite-time System Identification

Ph.D.

Ferdowsi University of Mashhad

Electrical Engineering (Control)

• Dissertation: Online Optimal Control in Differential Graphical Games Using Reinforcement Learning

M.Sc.

Ferdowsi University of Mashhad

Electrical Engineering (Control)

B.Sc.

Shahrood University of Technology

Electrical Engineering (Control)

Fitch Beach Medal for Outstanding Graduate Research

Michigan State University

Awarded for outstanding graduate research.

GOF and DCF Fellowships

Michigan State University

Graduate Office Fellowship and Dissertation Completion Fellowship.

A Hybrid End-to-End and Modular Control Architecture Toward Safe Vehicle Lateral Control

arXiv preprint arXiv:2608.17258

Combining Soft Actor-Critic with Model Predictive Control for safe vehicle lateral control.

Deep Learning-Based Rotor Temperature Estimation for Rare-Earth-Free Motors

NDIA Ground Vehicle Systems Engineering and Technology Symposium (GVSETS)

GRU and LSTM virtual sensors for rotor temperature estimation in a 190 kW EESM.

Online Learning of Noisy Functions via a Data-Regularized Gradient-Descent Approach

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Online learning under measurement noise, with robotics and vehicle dynamics case studies.

Data-driven Thermal Modeling for Electrically Excited Synchronous Motors — A Supervised Machine Learning Approach

IEEE Transportation Electrification Conference & Expo (ITEC)

Supervised ML for sensorless thermal estimation in EV traction motors.

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Identification of nonlinear discrete-time systems with provable fixed-time convergence.

IEEE Transactions on Neural Networks and Learning Systems

Concurrent-learning-based system identification with fixed-time convergence guarantees.

Hybrid MPC + Learned Control Architecture

• Preprint on arXiv:2608.17258
• Open-source implementation with reproducible experiments

Data-driven Thermal Management for Electric Powertrains

• Published at IEEE ITEC (2024) and NDIA GVSETS (2026)
• Open-source reference implementation on the public Paderborn PMSM dataset

Distributed Adaptive Control of Networked Systems

Online Stochastic Learning for Vehicle & Robot Dynamics