Intelligent Control
Reinforcement learning and data-driven control, compared rigorously against classical designs such as PID.
Electrical Engineering · Control Systems
Mohammad Sina Heidaripour
Machine Learning • Reinforcement Learning • Intelligent Control
Undergraduate control engineer focused on dynamic modeling and learning-based control, benchmarking modern methods against classical controllers. Long-term goal: guidance, navigation and control of aerospace and space systems.
B.Sc. · 2022 – presentElectrical Engineering (Control), Ferdowsi University of Mashhad
3 projectsReinforcement learning, deep learning and classical ML
MATLAB · Python · C++Core toolchain
STM32Embedded hardware experience
Areas of interest
Dynamic Modeling
Mathematical models of mechanical systems and their simulation in MATLAB/Simulink and Python.
Aerospace & Space Systems
Attitude control, state estimation and optimal control — the long-term direction of my studies.
Deep Learning
Architectures built from first principles in PyTorch — from sequence models to Transformers.
Selected work
Projects
Reinforcement Learning–Based Control of an Inverted Pendulum
Designed a mathematical model of an inverted pendulum in MATLAB/Simulink. Implemented and benchmarked a DQN-based reinforcement learning controller against a classical PID controller in Python to evaluate dynamic stabilization.
Human Activity Recognition using Transformer Networks
Implemented a custom Transformer architecture from scratch using raw PyTorch tensor operations, achieving robust sensor-based activity classification on the PAMAP2 dataset.
Classical Machine Learning Implementations
Engineered and evaluated predictive models including linear/logistic regression, SVM and KNN using Scikit-Learn to solve fundamental classification and regression challenges.
Toolchain
Technical skills
- Programming languages
- PythonC++
- Simulation & modeling
- MATLABSimulink
- Deep learning & architectures
- PyTorchTransformersSequence models
- Scientific computing & ML
- NumPySciPyMatplotlibScikit-Learn
- Embedded systems
- STM32 microcontrollers
- Software engineering
- Object-oriented programmingGitGitHub
- Operating systems
- Linux
- Languages
- English (intermediate)
Background
Education
2022 – Present · In progress
Bachelor’s Degree in Electrical Engineering (Control Engineering)
Ferdowsi University of Mashhad, Iran
Undergraduate program centred on control systems, dynamic modeling and artificial intelligence, applied through hands-on simulation and machine-learning projects.
Academic focus & where I apply it
Control Systems
Feedback design and stability analysis, applied by benchmarking a learned controller against a classical PID.
Pendulum project →Dynamic Modeling
Deriving mathematical models of mechanical systems and simulating them in MATLAB/Simulink and Python.
See simulation work →Artificial Intelligence
Deep learning from first principles in PyTorch, plus classical machine-learning methods for prediction.
Transformer & ML projects →Software & Embedded
Python and C++ tooling, Git-based workflows, and STM32 microcontrollers as the path from simulation to hardware.
Toolchain →Languages
English — intermediate
Contact
Let’s talk
Open to internships, research collaborations and projects in control engineering, intelligent control and aerospace systems. Email is the fastest way to reach me.
Open to
- Internships
- Research collaboration
- Control & GNC simulation
- ML for dynamical systems